Module A includes import B at its top. However under test conditions I’d like to mock B in A (mock A.B) and completely refrain from importing B.

In fact, B isn’t installed in the test environment on purpose.

A is the unit under test. I have to import A with all its functionality. B is the module I need to mock. But how can I mock B within A and stop A from importing the real B, if the first thing A does is import B?

(The reason B isn’t installed is that I use pypy for quick testing and unfortunately B isn’t compatible with pypy yet.)

How could this be done?

You can assign to sys.modules['B'] before importing A to get what you want:

test.py:

import sys
sys.modules['B'] = __import__('mock_B')
import A

print(A.B.__name__)

A.py:

import B

Note B.py does not exist, but when running test.py no error is returned and print(A.B.__name__) prints mock_B. You still have to create a mock_B.py where you mock B‘s actual functions/variables/etc. Or you can just assign a Mock() directly:

test.py:

import sys
sys.modules['B'] = Mock()
import A

The builtin __import__ can be mocked with the ‘mock’ library for more control:

# Store original __import__
orig_import = __import__
# This will be the B module
b_mock = mock.Mock()

def import_mock(name, *args):
    if name == 'B':
        return b_mock
    return orig_import(name, *args)

with mock.patch('__builtin__.__import__', side_effect=import_mock):
    import A

Say A looks like:

import B

def a():
    return B.func()

A.a() returns b_mock.func() which can be mocked also.

b_mock.func.return_value = 'spam'
A.a()  # returns 'spam'

Note for Python 3: As stated in the changelog for 3.0, __builtin__ is now named builtins:

Renamed module __builtin__ to builtins (removing the underscores, adding an ‘s’).

The code in this answer works fine if you replace __builtin__ by builtins for Python 3.

How to mock an import, (mock A.B)?

Module A includes import B at its top.

Easy, just mock the library in sys.modules before it gets imported:

if wrong_platform():
    sys.modules['B'] = mock.MagicMock()

and then, so long as A doesn’t rely on specific types of data being returned from B’s objects:

import A

should just work.

You can also mock import A.B:

This works even if you have submodules, but you’ll want to mock each module. Say you have this:

from foo import This, That, andTheOtherThing
from foo.bar import Yada, YadaYada
from foo.baz import Blah, getBlah, boink

To mock, simply do the below before the module that contains the above is imported:

sys.modules['foo'] = MagicMock()
sys.modules['foo.bar'] = MagicMock()
sys.modules['foo.baz'] = MagicMock()

(My experience: I had a dependency that works on one platform, Windows, but didn’t work on Linux, where we run our daily tests. So I needed to mock the dependency for our tests. Luckily it was a black box, so I didn’t need to set up a lot of interaction.)

Mocking Side Effects

Addendum: Actually, I needed to simulate a side-effect that took some time. So I needed an object’s method to sleep for a second. That would work like this:

sys.modules['foo'] = MagicMock()
sys.modules['foo.bar'] = MagicMock()
sys.modules['foo.baz'] = MagicMock()
# setup the side-effect:
from time import sleep

def sleep_one(*args): 
    sleep(1)

# this gives us the mock objects that will be used
from foo.bar import MyObject 
my_instance = MyObject()
# mock the method!
my_instance.method_that_takes_time = mock.MagicMock(side_effect=sleep_one)

And then the code takes some time to run, just like the real method.

I realize I’m a bit late to the party here, but here’s a somewhat insane way to automate this with the mock library:

(here’s an example usage)

import contextlib
import collections
import mock
import sys

def fake_module(**args):
    return (collections.namedtuple('module', args.keys())(**args))

def get_patch_dict(dotted_module_path, module):
    patch_dict = {}
    module_splits = dotted_module_path.split('.')

    # Add our module to the patch dict
    patch_dict[dotted_module_path] = module

    # We add the rest of the fake modules in backwards
    while module_splits:
        # This adds the next level up into the patch dict which is a fake
        # module that points at the next level down
        patch_dict['.'.join(module_splits[:-1])] = fake_module(
            **{module_splits[-1]: patch_dict['.'.join(module_splits)]}
        )
        module_splits = module_splits[:-1]

    return patch_dict

with mock.patch.dict(
    sys.modules,
    get_patch_dict('herp.derp', fake_module(foo='bar'))
):
    import herp.derp
    # prints bar
    print herp.derp.foo

The reason this is so ridiculously complicated is when an import occurs python basically does this (take for example from herp.derp import foo)

1. Does sys.modules['herp'] exist? Else import it. If still not ImportError
2. Does sys.modules['herp.derp'] exist? Else import it. If still not ImportError
3. Get attribute foo of sys.modules['herp.derp']. Else ImportError
4. foo = sys.modules['herp.derp'].foo

There are some downsides to this hacked together solution: If something else relies on other stuff in the module path this kind of screws it over. Also this only works for stuff that is being imported inline such as

def foo():
    import herp.derp

or

def foo():
    __import__('herp.derp')

Aaron Hall’s answer works for me. Just want to mention one important thing,

if in A.py you do

from B.C.D import E

then in test.py you must mock every module along the path, otherwise you get ImportError

sys.modules['B'] = mock.MagicMock()
sys.modules['B.C'] = mock.MagicMock()
sys.modules['B.C.D'] = mock.MagicMock()

I found fine way to mock the imports in Python. It’s Eric’s Zaadi solution found here which I just use inside my Django application.

I’ve got class SeatInterface which is interface to Seat model class. So inside my seat_interface module I have such an import:

from ..models import Seat

class SeatInterface(object):
    (...)

I wanted to create isolated tests for SeatInterface class with mocked Seat class as FakeSeat. The problem was – how tu run tests offline, where Django application is down. I had below error:

ImproperlyConfigured: Requested setting BASE_DIR, but settings are not configured. You must either define the environment variable DJANGO_SETTINGS_MODULE or call settings.configure() before accessing settings.

Ran 1 test in 0.078s

FAILED (errors=1)

The solution was:

import unittest
from mock import MagicMock, patch

class FakeSeat(object):
    pass

class TestSeatInterface(unittest.TestCase):

    def setUp(self):
        models_mock = MagicMock()
        models_mock.Seat.return_value = FakeSeat
        modules = {'app.app.models': models_mock}
        patch.dict('sys.modules', modules).start()

    def test1(self):
        from app.app.models_interface.seat_interface import SeatInterface

And then test magically runs OK :)

.
Ran 1 test in 0.002s

OK

If you do an import ModuleB you are really calling the builtin method __import__ as:

ModuleB = __import__('ModuleB', globals(), locals(), [], -1)

You could overwrite this method by importing the __builtin__ module and make a wrapper around the __builtin__.__import__method. Or you could play with the NullImporter hook from the imp module. Catching the exception and Mock your module/class in the except-block.

Pointer to the relevant docs:

docs.python.org: __import__

Accessing Import internals with the imp Module

I hope this helps. Be HIGHLY adviced that you step into the more arcane perimeters of python programming and that a) solid understanding what you really want to achieve and b)thorough understanding of the implications is important.