Mocking Python modules across multiple test scripts



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1















In my implementation script I have a line which logs a metric:



from datadog import statsd

def some_function:
statsd.increment('some_metric')


From my test script, I assert that statsd.increment() is called by mocking out the datadog module:



datadog = Mock()
sys.modules['datadog'] = datadog

def test():
some_function()
datadog.statsd.increment.assert_called()


This works fine and passes. But as soon as I add ANOTHER script which calls some_function() without mocking datadog, that script runs beforehand and loads the real datadog module into the cache. The above test then fails because some_function() is no longer using the mock datadog, it uses the real (cached) datadog.



How can I address this? Is it possible to remove the module from the cache?










share|improve this question
























  • Are you saying it's failing because it's getting the "mock datadog" instead of the "real datadog"?

    – Matt Messersmith
    Nov 15 '18 at 22:03











  • It passed when getting the mock datadog, now it fails because a previous running test has executed it, giving it the real datadog, which is then cached (so the mock cannot be used later on)

    – FBryant87
    Nov 16 '18 at 9:49

















1















In my implementation script I have a line which logs a metric:



from datadog import statsd

def some_function:
statsd.increment('some_metric')


From my test script, I assert that statsd.increment() is called by mocking out the datadog module:



datadog = Mock()
sys.modules['datadog'] = datadog

def test():
some_function()
datadog.statsd.increment.assert_called()


This works fine and passes. But as soon as I add ANOTHER script which calls some_function() without mocking datadog, that script runs beforehand and loads the real datadog module into the cache. The above test then fails because some_function() is no longer using the mock datadog, it uses the real (cached) datadog.



How can I address this? Is it possible to remove the module from the cache?










share|improve this question
























  • Are you saying it's failing because it's getting the "mock datadog" instead of the "real datadog"?

    – Matt Messersmith
    Nov 15 '18 at 22:03











  • It passed when getting the mock datadog, now it fails because a previous running test has executed it, giving it the real datadog, which is then cached (so the mock cannot be used later on)

    – FBryant87
    Nov 16 '18 at 9:49













1












1








1








In my implementation script I have a line which logs a metric:



from datadog import statsd

def some_function:
statsd.increment('some_metric')


From my test script, I assert that statsd.increment() is called by mocking out the datadog module:



datadog = Mock()
sys.modules['datadog'] = datadog

def test():
some_function()
datadog.statsd.increment.assert_called()


This works fine and passes. But as soon as I add ANOTHER script which calls some_function() without mocking datadog, that script runs beforehand and loads the real datadog module into the cache. The above test then fails because some_function() is no longer using the mock datadog, it uses the real (cached) datadog.



How can I address this? Is it possible to remove the module from the cache?










share|improve this question
















In my implementation script I have a line which logs a metric:



from datadog import statsd

def some_function:
statsd.increment('some_metric')


From my test script, I assert that statsd.increment() is called by mocking out the datadog module:



datadog = Mock()
sys.modules['datadog'] = datadog

def test():
some_function()
datadog.statsd.increment.assert_called()


This works fine and passes. But as soon as I add ANOTHER script which calls some_function() without mocking datadog, that script runs beforehand and loads the real datadog module into the cache. The above test then fails because some_function() is no longer using the mock datadog, it uses the real (cached) datadog.



How can I address this? Is it possible to remove the module from the cache?







python pytest






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Nov 16 '18 at 10:17







FBryant87

















asked Nov 15 '18 at 16:22









FBryant87FBryant87

1,79012441




1,79012441












  • Are you saying it's failing because it's getting the "mock datadog" instead of the "real datadog"?

    – Matt Messersmith
    Nov 15 '18 at 22:03











  • It passed when getting the mock datadog, now it fails because a previous running test has executed it, giving it the real datadog, which is then cached (so the mock cannot be used later on)

    – FBryant87
    Nov 16 '18 at 9:49

















  • Are you saying it's failing because it's getting the "mock datadog" instead of the "real datadog"?

    – Matt Messersmith
    Nov 15 '18 at 22:03











  • It passed when getting the mock datadog, now it fails because a previous running test has executed it, giving it the real datadog, which is then cached (so the mock cannot be used later on)

    – FBryant87
    Nov 16 '18 at 9:49
















Are you saying it's failing because it's getting the "mock datadog" instead of the "real datadog"?

– Matt Messersmith
Nov 15 '18 at 22:03





Are you saying it's failing because it's getting the "mock datadog" instead of the "real datadog"?

– Matt Messersmith
Nov 15 '18 at 22:03













It passed when getting the mock datadog, now it fails because a previous running test has executed it, giving it the real datadog, which is then cached (so the mock cannot be used later on)

– FBryant87
Nov 16 '18 at 9:49





It passed when getting the mock datadog, now it fails because a previous running test has executed it, giving it the real datadog, which is then cached (so the mock cannot be used later on)

– FBryant87
Nov 16 '18 at 9:49












2 Answers
2






active

oldest

votes


















0














Have you tried to mock the datalog module inside your function test? As long as your other scripts are not running concurrently with your test, this may work. That way the mock itself will be set only when the function is called, instead of being set in your script scope.






share|improve this answer























  • The tests aren't running concurrently but it's the ordering that's the problem. A test which doesn't mock the module runs first and caches the module, so that it can't be mocked by any test running after that.

    – FBryant87
    Nov 16 '18 at 10:10


















0














You could use unittest.mock.patch. If you are using pytest you can do the same with the monkeypatch fixture.



from datadog import statsd
from unittest.mock import Mock, patch

def some_function():
statsd.increment()

def test_some_function():
with patch('datadog.statsd', Mock()) as mock_statsd:
some_function()
mock_statsd.increment.assert_called()

test_some_function()





share|improve this answer























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    2 Answers
    2






    active

    oldest

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    2 Answers
    2






    active

    oldest

    votes









    active

    oldest

    votes






    active

    oldest

    votes









    0














    Have you tried to mock the datalog module inside your function test? As long as your other scripts are not running concurrently with your test, this may work. That way the mock itself will be set only when the function is called, instead of being set in your script scope.






    share|improve this answer























    • The tests aren't running concurrently but it's the ordering that's the problem. A test which doesn't mock the module runs first and caches the module, so that it can't be mocked by any test running after that.

      – FBryant87
      Nov 16 '18 at 10:10















    0














    Have you tried to mock the datalog module inside your function test? As long as your other scripts are not running concurrently with your test, this may work. That way the mock itself will be set only when the function is called, instead of being set in your script scope.






    share|improve this answer























    • The tests aren't running concurrently but it's the ordering that's the problem. A test which doesn't mock the module runs first and caches the module, so that it can't be mocked by any test running after that.

      – FBryant87
      Nov 16 '18 at 10:10













    0












    0








    0







    Have you tried to mock the datalog module inside your function test? As long as your other scripts are not running concurrently with your test, this may work. That way the mock itself will be set only when the function is called, instead of being set in your script scope.






    share|improve this answer













    Have you tried to mock the datalog module inside your function test? As long as your other scripts are not running concurrently with your test, this may work. That way the mock itself will be set only when the function is called, instead of being set in your script scope.







    share|improve this answer












    share|improve this answer



    share|improve this answer










    answered Nov 15 '18 at 21:58









    Aurora WangAurora Wang

    843418




    843418












    • The tests aren't running concurrently but it's the ordering that's the problem. A test which doesn't mock the module runs first and caches the module, so that it can't be mocked by any test running after that.

      – FBryant87
      Nov 16 '18 at 10:10

















    • The tests aren't running concurrently but it's the ordering that's the problem. A test which doesn't mock the module runs first and caches the module, so that it can't be mocked by any test running after that.

      – FBryant87
      Nov 16 '18 at 10:10
















    The tests aren't running concurrently but it's the ordering that's the problem. A test which doesn't mock the module runs first and caches the module, so that it can't be mocked by any test running after that.

    – FBryant87
    Nov 16 '18 at 10:10





    The tests aren't running concurrently but it's the ordering that's the problem. A test which doesn't mock the module runs first and caches the module, so that it can't be mocked by any test running after that.

    – FBryant87
    Nov 16 '18 at 10:10













    0














    You could use unittest.mock.patch. If you are using pytest you can do the same with the monkeypatch fixture.



    from datadog import statsd
    from unittest.mock import Mock, patch

    def some_function():
    statsd.increment()

    def test_some_function():
    with patch('datadog.statsd', Mock()) as mock_statsd:
    some_function()
    mock_statsd.increment.assert_called()

    test_some_function()





    share|improve this answer



























      0














      You could use unittest.mock.patch. If you are using pytest you can do the same with the monkeypatch fixture.



      from datadog import statsd
      from unittest.mock import Mock, patch

      def some_function():
      statsd.increment()

      def test_some_function():
      with patch('datadog.statsd', Mock()) as mock_statsd:
      some_function()
      mock_statsd.increment.assert_called()

      test_some_function()





      share|improve this answer

























        0












        0








        0







        You could use unittest.mock.patch. If you are using pytest you can do the same with the monkeypatch fixture.



        from datadog import statsd
        from unittest.mock import Mock, patch

        def some_function():
        statsd.increment()

        def test_some_function():
        with patch('datadog.statsd', Mock()) as mock_statsd:
        some_function()
        mock_statsd.increment.assert_called()

        test_some_function()





        share|improve this answer













        You could use unittest.mock.patch. If you are using pytest you can do the same with the monkeypatch fixture.



        from datadog import statsd
        from unittest.mock import Mock, patch

        def some_function():
        statsd.increment()

        def test_some_function():
        with patch('datadog.statsd', Mock()) as mock_statsd:
        some_function()
        mock_statsd.increment.assert_called()

        test_some_function()






        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered Nov 18 '18 at 16:50









        soundstripesoundstripe

        53038




        53038



























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