To mock an imported function with Jest we use the jest. mock() function. jest. mock() is called with one required argument - the import path of the module we're mocking.
If you want to mock an object for the duration of your entire test function, you can use patch() as a function decorator. These functions are now in their own file, separate from their tests. Next, you'll re-create your tests in a file called tests.py .
To mock an ES6 module import using Jest, we can call the jest. mock method. For instance, we write: import myModule from './myModule'; import dependency from './dependency'; jest.
There are two ways to mock functions: Either by creating a mock function to use in test code, or writing a manual mock to override a module dependency.
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__
tobuiltins
(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.
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.)
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.
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 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
)
sys.modules['herp']
exist? Else import it. If still not ImportError
sys.modules['herp.derp']
exist? Else import it. If still not ImportError
foo
of sys.modules['herp.derp']
. Else ImportError
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')
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 0.002sOK
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.
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