I am trying to use pytest and monkeypatch to unit test a method that has uses a third party data integration package.
Here is some example pseudo code:
from third_party.data_integration import Account
def fetch_data():
account_id = "123"
account_token = "234"
account = Account(account_id, account_token)
account.download('path')
return True
I am hoping to do some like blow in my test file to monkeypatch the download instance function:
def test_fetch_data(monkeypatch):
def download():
return '123'
with monkeypatch.context() as m:
m.setattr('third_party.data_integration.Account.download', download)
assert fetch_data() == True
Obviously, m.setattr('third_party.data_integration.Account.download', download) would only work for static method instead of instanced method or class method. What is the best practice to do test like this to monkey patch a third party native package instance method?
Since you're calling the constructor of the Account class & the method you want to mock is an attribute of the return value of that constructor, you need to mock the return value of the constructor and then monkeypatch the download attribute of the mock.
Here's how I would do it:
#mock.patch('third_party.data_integration.Account')
def test_fetch_data(mock_account):
def download():
return '123'
acc = MagicMock()
acc.download = download
mock_account.return_value = acc
assert fetch_data() == True
Related
I have a fixture mocking an external library like so, using pytest-mock, which is a wrapper around unittest.mock.
# client.py
import Test as TestLibrary
class LibraryName():
def get_client():
return TestLibrary.Library()
# library_service.py
def using_library():
'''
Edited note: Library().attribute behind the scenes is set to
self.attribute = Attribute()
so this may be affecting the mocking
'''
client = LibraryName.get_client()
return client.attribute.method()
# conftest.py
#pytest.fixture
def library_client_mock(mocker):
import Test as TestLibrary
return mocker.patch.object(TestLibrary, 'Library')
# test_library_service.py
def test_library_method(library_client_mock):
result = using_library()
I can mock a return value like so:
def test_library_method(library_client_mock):
library_client_mock.return_value.attribute.return_value.method.return_value = "test"
result = using_library()
assert result == "test"
but I can't mock throwing an Exception with side_effect
def test_library_method(library_client_mock):
library_client_mock.return_value.attribute.return_value.method.side_effect = TypeError # doesn't work
library_client_mock.return_value.attribute.return_value.method.side_effect = TypeError() # doesn't work
attrs = { 'attribute.method.side_effect': TypeError }
library_client_mock.configure_mock(**attrs) # doesn't work
with pytest.raises(TypeError):
using_library() # fails assertion
what I missing here?
These are the errors in your code:
Change:
library_client_mock.return_value.attribute.return_value.method.return_value = "test"
To:
library_client_mock.return_value.attribute.method.return_value = "test"
Change:
library_client_mock.return_value.attribute.return_value.method.side_effect = TypeError
To:
library_client_mock.return_value.attribute.method.side_effect = TypeError
Explanation
The .return_value must only be used for callable objects e.g. a function as documented:
return_value
Set this to configure the value returned by calling the mock:
>>> mock = Mock()
>>> mock.return_value = 'fish'
>>> mock()
'fish'
Thus, you can use .return_value only for the following:
TestLibrary.Library()
TestLibrary.Library().attribute.method()
But not for:
TestLibrary.Library().attribute
Because .attribute is not a callable e.g. TestLibrary.Library().attribute().
Warning
The way you are patching Library is via its source location at Test.Library (or aliased as TestLibrary.Library). specifically via:
import Test as TestLibrary
return mocker.patch.object(TestLibrary, 'Library')
It works currently because the way you import and use it is via the root path.
# client.py
import Test as TestLibrary
...
return TestLibrary.Library()
...
But if we change the way we imported that library and imported a local version to client.py:
# client.py
from Test import Library # Instead of <import Test as TestLibrary>
...
return Library() # Instead of <TestLibrary.Library()>
...
It will now fail. Ideally, you should patch the specific name that is used by the system under test, which here is client.Library.
import client
return mocker.patch.object(client, 'Library')
Unless you are sure that all files that will use the library will import only the root and not a local version.
#Niel Godfrey Ponciano set me on the right path with this syntax for the side_effect
library_client_mock.return_value.attribute.method.side_effect = TypeError
but it wasn't enough.
In
# conftest.py
#pytest.fixture
def library_client_mock(mocker):
import Test as TestLibrary
return mocker.patch.object(TestLibrary, 'Library')
I had to add an extra mock:
# conftest.py
#pytest.fixture
def library_client_mock(mocker):
import Test as TestLibrary
mock_library_client = mocker.patch.object(TestLibrary, 'Library')
# option 1
mock_attribute = Mock()
# option 2, path to Library.attribute = Attribute()
mock_attribute = mocker.patch.object(TestLibrary.services, 'Attribute', autospec=True)
mock_library_client.attach_mock(mock_attribute, "attribute")
return mock_library_client
and then both of the following statements worked as expected. Although I am not sure why return_value works out of the box without an attached mock, but side_effect does not.
# return_value set correctly
# NOTE return_value needed after each
library_client_mock.return_value.attribute.return_value.method.return_value = "test"
# side_effect set correctly
# NOTE return_value not needed after "attribute"
library_client_mock.return_value.attribute.method.side_effect = TypeError
As the doc "Where to patch" says, we need to patch where an object is looked up, (not where it's defined); so I understand that it's not possible to - let's say - create a reusable patch for a particular path
Imagine you have several modules importing an object you'd like to mock
# file_a.py
from foo.goo.hoo import settings
# file_b.py
from foo.goo.hoo import settings
# file_c.py
from foo.goo.hoo import settings
I was wondering if there is a way to create a decorator such as:
#mock_settings
def test_whatever(self, settings_mock):
...
instead of this solution:
#patch("some_module.file_a.settings")
def test_whatever(self, settings_mock):
...
#patch("some_module.file_b.settings")
def test_whatever(self, settings_mock):
...
#patch("some_module.file_c.settings")
def test_whatever(self, settings_mock):
...
As mentioned in the question, to patch an object you have to patch its reference in the module to be tested (in case it is imported using from ...import).
To have it patched in several modules, you can patch all of these modules with the same mock, and use that mock. If you know in advance which modules you want to patch, you can just do this. If you don't know them in advance, you have to try to patch the object in all loaded modules -- this may get a bit more complicated.
I will show an example using pytest and a pytest fixture, as this is more compact; you could wrap that in a decorator for usage in unittest, but that will not change the basics. Consider we have a class that needs to be mocked in several modules:
class_to_mock.py
class ClassToMock:
def foo(self, msg):
return msg
module1.py
from class_to_mock import ClassToMock
def do_something():
inst = ClassToMock()
return inst.foo("module1")
module2.py
from class_to_mock import ClassToMock
def do_something_else():
inst = ClassToMock()
return inst.foo("module2")
You can now write a fixture that mocks the class in all of these modules at once (here using pytest-mock for simplicity):
#pytest.fixture
def mocked_class(mocker):
mocked = Mock()
for module in ('module1', 'module2'):
mocker.patch(module + '.ClassToMock', mocked)
yield mocked
This can be used to test both modules:
def test_module1(mocked_class):
mocked_class.return_value.foo.return_value = 'mocked!'
assert module1.do_something() == 'mocked!'
def test_module2(mocked_class):
mocked_class.return_value.foo.return_value = 'mocked!'
assert module2.do_something_else() == 'mocked!'
If you want a generic version that mocks the class in all loaded modules, you can replace the fixture with something like this:
#pytest.fixture
def mocked_class(mocker):
mocked = Mock()
for name, module in list(sys.modules.items()):
if not inspect.ismodule(module):
continue
for cls_name, cls in module.__dict__.items():
try: # need that as inspect may raise for some modules
if inspect.isclass(cls) and cls_name == "ClassToMock":
mocker.patch(name + ".ClassToMock", mocked)
except Exception:
continue
yield mocked
This will work for this specific example - to generalize this, it has to consider more object types, the class shall be configurable, and there may be some more issues - opposed to the more simple version where you just enumerate the modules you want to patch, which will always work.
You could do something similar in unittest.setUp by putting the mock in an instance variable, though that is less elegant, because you are also responsible for stopping the mocking:
class ModulesTest(unittest.TestCase):
def setUp(self):
self.mocked_class = Mock()
self.mocks = []
for module in ('module1', 'module2'):
mocked = mock.patch(module + '.ClassToMock', self.mocked_class)
self.mocks.append(mocked)
mocked.start()
def tearDown(self):
for mocked in self.mocks:
mocked.stop()
def test_module1(self):
self.mocked_class.return_value.foo.return_value = 'mocked!'
assert module1.do_something() == 'mocked!'
And you can also wrap this in a decorator, to answer your original question at least partially:
def mocked_class_to_mock(f):
#wraps(f)
def _mocked_class_to_mock(*args, **kwargs):
mocked_class = Mock()
mocks = []
for module in ('module1', 'module2'):
mocked = mock.patch(module + '.ClassToMock', mocked_class)
mocks.append(mocked)
mocked.start()
kwargs['mocked_class'] = mocked_class # use a keyword arg for simplicity
f(*args, **kwargs)
for mocked in mocks:
mocked.stop()
return _mocked_class_to_mock
...
#mocked_class_to_mock
def test_module3(self, mocked_class):
mocked_class.return_value.foo.return_value = 'mocked!'
assert module3.do_something() == 'mocked!'
Of course, you can do the same with the more generic version, if needed.
Also note that I skipped the simpler case where the object is imported using import .... In this case, you have to patch the original module. In the generic fixture, you probably want to add that case always.
I have a python method like
import external_object
from external_lib1 import ExternalClass1
from external_lib2 import Hook
class MyClass(self):
def my_method(self):
ExternalClass.get('arg1') #should be mocked and return a specific value with this arg1
ExternalClass.get('arg2') #should be mocked and return a specific value with this arg2
def get_hook(self):
return Hook() # return a mock object with mocked method on it
def my_method(self):
object_1 = external_object.instance_type_1('args') # those are two different object instanciate from the same lib.
object_2 = external_object.instance_type_2('args')
object_1.method_1('arg') # should return what I want when object_1 mocked
object_2.method_2 ('arg') # should return what I want when object_2 mocked
In my test I would like to realise what I put in comments.
I could manage to do it, but every time it gets really messy.
I use to call flexmock for some stuff (by example ExternalClass.get('arg1') would be mock with a flexmock(ExternalClass).should_return('arg').with_args('arg') # etc...) but I'm tired of using different test libs to mock.
I would like to use only the mock library but I struggle to find a consistent way of doing it.
I like to use python's unittest lib. Concretely the unittest.mock which is a great lib to customize side effects and return value in unit tested functions.
They can be used as follows:
class Some(object):
"""
You want to test this class
external_lib is an external component we cannot test
"""
def __init__(self, external_lib):
self.lib = external_lib
def create_index(self, unique_index):
"""
Create an index.
"""
try:
self.lib.create(index=unique_index) # mock this
return True
except MyException as e:
self.logger.error(e.__dict__, color="red")
return False
class MockLib():
pass
class TestSome(unittest.TestCase):
def setUp(self):
self.lib = MockLib()
self.some = Some(self.lib)
def test_create_index(self):
# This will test the method returns True if everything went fine
self.some.create_index = MagicMock(return_value={})
self.assertTrue(self.some.create_index("test-index"))
def test_create_index_fail(self):
# This will test the exception is handled and return False
self.some.create_index = MagicMock(side_effect=MyException("error create"))
self.assertFalse(self.some.create_index("test-index"))
Put the TestSome() class file somewhere like your-codebase-path/tests and run:
python -m unittest -v
I hope it's useful.
Here I am using unittest framework and Python.
def getsomevalue(name):
client = hvac.Client(url ="http://1.2.3.4:31485",token = "abcdefghijkkk")
sampledata= client.read('secret/data/somedata')
return sampledata
So pretty much what I did was create a mock hvac client class and then patch to replace the vault client instance in your code.
in other words it is something like this:
def mock_vault_read(*args, **kwargs):
class MockVault:
def read(self, **kwargs):
return {some_data}
and then for your test you can write:
#patch("hvac.Client", side_effect=mock_vault_read):
def test_read(self, mock_vault):
name = "test"
result = getsomevalue(name)
self.assertEquals(result, {some_data})
What this is doing is creating a magic mock mock_vault and replacing all instances of hvac.Client that it can find with that magic mock. The mock_vault_read is a side_effect of that magic mock, essentially saying that when you call the magic mock, call the mock_vault_read function. This can be further customized for any function need for hvac.
I need to write a unit test for credential checking module looks something like below. I apologize I cannot copy the exact code.. but I tried my best to simplify as an example.
I want to patch methodA so it returns False as a return value and test MyClass to see if it is throwing error. cred_check is the file name and MyClass is the class name. methodA is outside of MyClass and the return value checkedcredential is either True or False.
def methodA(username, password):
#credential check logic here...
#checkedcredential = True/False depending on the username+password combination
return checkedcredential
class MyClass(wsgi.Middleware):
def methodB(self, req):
username = req.retrieve[constants.USER]
password = req.retrieve[constants.PW]
if methodA(username,password):
print(“passed”)
else:
print(“Not passed”)
return http_exception...
The unit test I currently have looks like...
import unittest
import mock
import cred_check import MyClass
class TestMyClass(unittest.Testcase):
#mock.patch('cred_check')
def test_negative_cred(self, mock_A):
mock_A.return_value = False
#not sure what to do from this point....
The part I want to write in my unittest is return http_exception part. I am thinking of doing it by patching methodA to return False. After setting the return value, what would be the proper way of writing the unittest so it works as intended?
What you need to do in your unittest to test http_exception return case is:
patch cred_check.methodA to return False
Instantiate a MyClass() object (you can also use a Mock instead)
Call MyClass.methodB() where you can pass a MagicMock as request and check if the return value is an instance of http_exception
Your test become:
#mock.patch('cred_check.methodA', return_value=False, autospec=True)
def test_negative_cred(self, mock_A):
obj = MyClass()
#if obj is a Mock object use MyClass.methodB(obj, MagicMock()) instead
response = obj.methodB(MagicMock())
self.assertIsInstance(response, http_exception)
#... and anything else you want to test on your response in that case
import unittest
import mock
import cred_check import MyClass
class TestMyClass(unittest.Testcase):
#mock.patch('cred_check.methodA',return_value=False)
#mock.patch.dict(req.retrieve,{'constants.USER':'user','constants.PW':'pw'})
def test_negative_cred(self, mock_A,):
obj=MyClass(#you need to send some object here)
obj.methodB()
It should work this way.