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AttributeError: while using monkeypatch of pytest

src/mainDir/mainFile.py
contents of mainFile.py
import src.tempDir.tempFile as temp
data = 'someData'
def foo(self):
ans = temp.boo(data)
return ans
src/tempDir/tempFile.py
def boo(data):
ans = data
return ans
Now I want to test foo() from src/tests/test_mainFile.py and I want to mock temp.boo(data) method in foo() method
import src.mainDir.mainFile as mainFunc
testData = 'testData'
def test_foo(monkeypatch):
monkeypatch.setattr('src.tempDir.tempFile', 'boo', testData)
ans = mainFunc.foo()
assert ans == testData
but I get error
AttributeError: 'src.tempDir.tempFile' has no attribute 'boo'
I expect ans = testData.
I would like to know if I am correctly mocking my tempDir.boo() method or I should use pytest's mocker instead of monkeypatch.

You're telling monkeypatch to patch the attribute boo of the string object you pass in.
You'll either need to pass in a module like monkeypatch.setattr(tempFile, 'boo', testData), or pass the attribute as a string too (using the two-argument form), like monkeypatch.setattr('src.tempDir.tempFile.boo', testData).

My use case was was slightly different but should still apply. I wanted to patch the value of sys.frozen which is set when running an application bundled by something like Pyinstaller. Otherwise, the attribute does not exist. Looking through the pytest docs, the raising kwarg controls wether or not AttributeError is raised when the attribute does not already exist. (docs)
Usage Example
import sys
def test_frozen_func(monkeypatch):
monkeypatch.setattr(sys, 'frozen', True, raising=False)
# can use ('fq_import_path.sys.frozen', ...)
# if what you are trying to patch is imported in another file
assert sys.frozen

Update: mocking function calls can be done with monkeypatch.setattr('package.main.slow_fun', lambda: False) (see answer and comments in https://stackoverflow.com/a/44666743/3219667) and updated snippet below
I don't think this can be done with pytest's monkeypatch, but you can use the pytest-mock package. Docs: https://github.com/pytest-dev/pytest-mock
Quick example with the two files below:
# package/main.py
def slow_fun():
return True
def main_fun():
if slow_fun():
raise RuntimeError('Slow func returned True')
# tests/test_main.py
from package.main import main_fun
# Make sure to install pytest-mock so that the mocker argument is available
def test_main_fun(mocker):
mocker.patch('package.main.slow_fun', lambda: False)
main_fun()
# UPDATE: Alternative with monkeypatch
def test_main_fun_monkeypatch(monkeypatch):
monkeypatch.setattr('package.main.slow_fun', lambda: False)
main_fun()
Note: this also works if the functions are in different files

Mocking an entire class

Long story short, I'm perfectly able to mock class method, when it's just that method that's replaced by mock object, but I'm unable to mock that method when I'm trying to replace the whole class by the mock object
The #mock.patch.object successfully mocks the scan method but #mock.patch fails to do so. I've followed the example at
https://docs.python.org/3/library/unittest.mock.html#unittest.mock.patch
but apparently I'm doing something wrong.
I'm mocking the lexicon module in the same namespace in both cases (it's imported by import lexicon in the sentence_parser) but the mock_lexicon is lexicon.lexicon check fails
#!python
import sys;
sys.path.append('D:\python\lexicon');
import lexicon;
import sentence_parser;
import unittest2 as unittest;
import mock;
class ParserTestCases(unittest.TestCase) :
def setUp(self) :
self.Parser = sentence_parser.Parser();
#mock.patch('lexicon.lexicon')
def test_categorizedWordsAreAssigned_v1(self, mock_lexicon) :
print "mock is lexicon:";
print mock_lexicon is lexicon.lexicon + "\n";
instance = mock_lexicon.return_value;
instance.scan.return_value = "anything";
self.Parser.categorize_words_in_sentence("sentence");
instance.scan.assert_called_once_with("sentence");
#mock.patch.object(lexicon.lexicon, 'scan')
def test_categorizedWordsAreAssigned_v2(self, mock_scan) :
mock_scan.return_value = "anything";
self.Parser.categorize_words_in_sentence("sentence");
mock_scan.assert_called_once_with("sentence");
if (__name__ == '__main__') :
unittest.main()
Output :
mock is lexicon:
False
======================================================================
FAIL: test_categorizedWordsAreAssigned_v1 (__main__.ParserTestCases)
----------------------------------------------------------------------
Traceback (most recent call last):
File "D:\python\get_img\getImage_env\lib\site-packages\mock\mock.py", line 1305, in patched
return func(*args, **keywargs)
File "./test_sentence_parser.py", line 26, in test_categorizedWordsAreAssigned_v1
instance.scan.assert_called_once_with("sentence");
File "D:\python\get_img\getImage_env\lib\site-packages\mock\mock.py", line 947, in assert_called_once_with
raise AssertionError(msg)
AssertionError: Expected 'scan' to be called once. Called 0 times.
----------------------------------------------------------------------
Ran 2 tests in 0.009s
FAILED (failures=1)
EDIT :
To clarify, the Parser is defined as follows
#!python
import sys;
sys.path.append('D:\python\lexicon');
import lexicon;
class Parser(object) :
my_lexicon = lexicon.lexicon()
def __init__(self) :
self.categorized_words = ['test'];
def categorize_words_in_sentence(self, sentence) :
self.categorized_words = self.my_lexicon.scan(sentence);
if (__name__ == '__main__') :
instance = Parser();
instance.categorize_words_in_sentence("bear");
print instance.categorized_words;

What is real relevant here is how categorize_words_in_sentence Parser's method use lexicon. But first of all we should remove the noise:
print mock_lexicon is lexicon.lexicon + "\n"
Is what can lead us to the wrong direction: try to replace it by
self.assertIs(mock_lexicon, lexicon.lexicon)
and you will understand that you are printing False because mock_lexicon is not lexicon.lexicon + "\n" but just lexicon.lexicon.
Now I cannot tell you why the first test doesn't work because the answer is in categorize_words_in_sentence method or more probably in sentence_parser module where I can guess you can have something like
from lexicon import lexicon
In both case take a look to Where to Patch documentation that can enlighten you on what can be the cause and what you really need to patch in your case.
The second version works just because you are patching the object and not the reference (that should be different).
Finally the more concise and general version can be:
#mock.patch('lexicon.lexicon.scan', return_value="anything")
def test_categorizedWordsAreAssigned_v3(self, mock_scan) :
self.Parser.categorize_words_in_sentence("sentence")
mock_scan.assert_called_once_with("sentence")
One more thing: remove unittest2 at least you're not using python 2.4 and you are interested on backported unittest features.
[EDIT]
Now I can stop to guess and point to you why the first version doesn't work and will never work:
class Parser(object) :
my_lexicon = lexicon.lexicon()
Parser.my_lexicon attribute is evaluated at the load time. That means when you import sentence_parser a lexicon is created and the reference associated to Parser.my_lexicon. When you patch lexicon.lexicon you leave this reference untouched and your parser object still use the original reference created when is imported.
What you can do is to patch the reference in Parser class by
#patch("sentence_parser.Parser.my_lexicon")
You can use create_autospect if you want give to your mock the same lexicon's signature.
#patch("sentence_parser.Parser.my_lexicon", create_autospec("lexicon.lexicon", instance=True))

How can I mock/patch an associative array in python

I have a module with a dictionary as associative array to implement a kind-of switch statement.
def my_method1():
return "method 1"
def my_method2():
return "method 2"
map_func = {
'0': my_method1,
'1': my_method2
}
def disptach(arg):
return map_func[arg]()
How can I mock my_method1 in tests? I've tried the following without success:
import my_module as app
#patch('my_module.my_method1')
def test_mocking_sample(self, my_mock):
my_mock.return_value = 'mocked'
assert_equal('mocked',app.dispatch('0'))
Any idea?

This piece of patch documentation says the following:
patch works by (temporarily) changing the object that a name points to
with another one. There can be many names pointing to any individual
object, so for patching to work you must ensure that you patch the
name used by the system under test.
Basically, your dispatcher won't see it, as the mapping is built to reference the original method, before the patch is applied.
The simplest thing you can do to make it mockable is to fold the mapping into the dispatch function:
def dispatch(arg):
return {
'0': my_method1,
'1': my_method2
}[arg]()
This does have the downside that it rebuilds that mapping every time you call it, so it will be slower.
Trying to get a bit clever, it seems that Python lets you swap out the actual code of a function, like so:
>>> f = lambda: "foo"
>>> a = f
>>> g = lambda: "bar"
>>> f.func_code = g.func_code
>>> a()
'bar'
I won't recommend that you do it this way, but maybe you can find a mocking framework that supports something similar.

As you've discovered, patching my_Method1() does not work. This is because map_func['0'] was defined when my_module was imported and subsequent changes to my_Method1() do not update map_func for your test. Instead, we need to patch the value in dictionary map_func for key '0' directly. The unittest.mock documentation explains how to patch a dictionary entry. Below is a working implementation of your test:
""" test_my_module.py
"""
import unittest
import unittest.mock as mock
import my_module as app
my_mock = mock.MagicMock()
class Test_mock_sample(unittest.TestCase):
#mock.patch.dict('my_module.map_func', {'0': my_mock})
def test_mocking_sample(self):
my_mock.return_value = 'mocked'
self.assertEqual('mocked', app.dispatch('0'))
if __name__ == '__main__':
unittest.main()
After changing disptach to dispatch in your original my_module...
""" my_module.py
"""
def my_method1():
return "method 1"
def my_method2():
return "method 2"
map_func = {
'0': my_method1,
'1': my_method2
}
def dispatch(arg):
return map_func[arg]()
Then the command python -m unittest test_my_module gives the following output:
.
----------------------------------------------------------------------
Ran 1 test in 0.000s
OK
It worked!

How to use Python Unittest TearDownClass with TestResult.wasSuccessful()

I wanted to call setUpClass and tearDownClass so that setup and teardown would be performed only once for each test. However, it keeps failing for me when I call tearDownClass. I only want to record 1 test result, either PASS if both tests passed or FAIL if both tests failed. If I call only setup and tearDown then all works fine:
Calling setUpClass and tearDownClass:
#!/usr/bin/python
import datetime
import itertools
import logging
import os
import sys
import time
import unittest
LOGFILE = 'logfile.txt'
class MyTest(unittest.TestCase):
global testResult
testResult = None
#classmethod
def setUpClass(self):
## test result for DB Entry:
self.dbresult_dict = {
'SCRIPT' : 'MyTest.py',
'RESULT' : testResult,
}
def test1(self):
expected_number = 10
actual_number = 10
self.assertEqual(expected_number, actual_number)
def test2(self):
expected = True
actual = True
self.assertEqual(expected, actual)
def run(self, result=None):
self.testResult = result
unittest.TestCase.run(self, result)
#classmethod
def tearDownClass(self):
ok = self.testResult.wasSuccessful()
errors = self.testResult.errors
failures = self.testResult.failures
if ok:
self.dbresult_dict['RESULT'] = 'Pass'
else:
logging.info(' %d errors and %d failures',
len(errors), len(failures))
self.dbresult_dict['RESULT'] = 'Fail'
if __name__ == '__main__':
logger = logging.getLogger()
logger.addHandler(logging.FileHandler(LOGFILE, mode='a'))
stderr_file = open(LOGFILE, 'a')
runner = unittest.TextTestRunner(verbosity=2, stream=stderr_file, descriptions=True)
itersuite = unittest.TestLoader().loadTestsFromTestCase(MyTest)
runner.run(itersuite)
sys.exit()
unittest.main(module=itersuite, exit=True)
stderr_file.close()
Error:
test1 (__main__.MyTest) ... ok
test2 (__main__.MyTest) ... ok
ERROR
===================================================================
ERROR: tearDownClass (__main__.MyTest)
-------------------------------------------------------------------
Traceback (most recent call last):
File "testTearDownClass.py", line 47, in tearDownClass
ok = self.testResult.wasSuccessful()
AttributeError: type object 'MyTest' has no attribute 'testResult'
----------------------------------------------------------------------
Ran 2 tests in 0.006s
FAILED (errors=1)

like #Marcin already pointed out, you're using the Unittest-Framework in a way it isn't intended.
To see if the tests are successful you check the given values with the expected, like you already did: assertEqual(given, expected). Unittest will then collect a summary of failed ones. you don't have to do this manually.
If you want to check that two tests need to be together successful or fail together, these should be combined in ONE Test, maybe as a additionally one, if the individual Tests need to be checked as well. This is nothing you want to save and load afterwards. The tests itself should be as stateless as possible.
When you say you want to run the SetUp and TearDown 'once per test', do you mean once per test-method or per test-run? This is different if you have more than one test-method inside your class:
setUp() Will be called before each test-method
tearDown() Will be called after each test-method
setUpClass() Will be called once per class (before the first test-method of this class)
tearDownClass() Will be called once per class (after the last test-method of this class)
Here's the official documentation
Here's a related answer

Change tearDownClass(self) to tearDownClass(cls) and setUpClass(self) to setUpClass(cls).

Weird behavior when calling load_tests()

When using the new discover feature in Python 2.7, I'm getting a weird error. I have some unit tests that require a bit of extra setup and some member data from a file. I'm trying to add my setup test cases to the current test suite that is passed to load_tests(). But because the test suite tests already contains the standard tests (including the TestCase objects in the current module), the proper setup for the automatically added testcase is not done and I get an AttributeError.
In the code below, load_tests() is used to create one test case for each line of data in a csv file. The file has three lines, but for some reason a fourth testcase is being created.
#!/usr/bin/python
import unittest
class Foo(unittest.TestCase):
def setup(self,bar):
print "Foo.setup()"
self.bar = bar
def runTest(self):
print self.bar
def load_tests(loader, tests, pattern):
f = open('data.csv') # data.csv contains three lines: "a\nb\nc"
for line in f:
tc = Foo()
tc.setup(line)
tests.addTest(tc)
return tests
unittest.main()
When I execute this code, the output shows that 4 tests were executed and one of them failed. The data file only contains three lines, and Foo.setup() was only called three times. So load_tests() created the three test cases as designed.
Foo.setup()
Foo.setup()
Foo.setup()
Ea
.b
.c
.
======================================================================
ERROR: runTest (__main__.Foo)
----------------------------------------------------------------------
Traceback (most recent call last):
File "./foo.py", line 11, in runTest
print self.bar
AttributeError: 'Foo' object has no attribute 'bar'
----------------------------------------------------------------------
Ran 4 tests in 0.002s
Is there a way to remove the TestCase that was automatically loaded in the suite? I cannot create a new empty TestSuite because I need all the other tests that are already there. I just want to add these tests to the suite.
Edit: clarified my question and code examples. I was a bit ambiguous before.

There are a couple of ways you can do this.
If you are always going to instantiate Foo, you could set up bar in the __init__ method of the class.
class Foo(unittest.TestCase):
def __init__(self, bar, *args, **kwargs):
super(Foo, self).__init__(*args, **kwargs)
self.bar = bar
def runTest(self):
print self.bar
f = Foo("some string")
I haven't used the load_tests pattern directly before -- I usually just rely on nose's auto test discovery, but all of these would work for your setup. If you later wanted to use TestSuites and unittest/nose's test autodiscovery, and wanted to use classes, you could use a class factory:
def make_foo_case(the_bar):
class Foo(unittest.TestCase):
bar = the_bar
def runTest(self):
print self.bar
return Foo
f = (make_testcase("some string"))()
or use type to subclass foo and set up the element in the members, (essentially the same as the previous) e.g.:
class Foo2(object):
def runTest(self):
print self.bar
f = (type("Tester2", (Foo2,unittest.TestCase), {"bar":"some string"}))()

Apparently I misunderstand load_tests(). According to the Python code in /usr/lib/python2.7/unittest/loader.py, the tests are loaded from the module as normal. Then, if load_tests() exist, it is called as well.
def loadTestsFromModule(self, module, use_load_tests=True):
"""Return a suite of all tests cases contained in the given module"""
tests = []
for name in dir(module):
obj = getattr(module, name)
if isinstance(obj, type) and issubclass(obj, case.TestCase):
tests.append(self.loadTestsFromTestCase(obj))
load_tests = getattr(module, 'load_tests', None)
tests = self.suiteClass(tests)
if use_load_tests and load_tests is not None:
try:
return load_tests(self, tests, None)
except Exception, e:
return _make_failed_load_tests(module.__name__, e,
self.suiteClass)
return tests
So I guess my solution is to accept the extra test case that is created, check for it, and just pass it. Much thanks to Jeff for trying to help me out.