How do I test the following code with unittest.mock:
def testme(filepath):
with open(filepath) as f:
return f.read()
Python 3
Patch builtins.open and use mock_open, which is part of the mock framework. patch used as a context manager returns the object used to replace the patched one:
from unittest.mock import patch, mock_open
with patch("builtins.open", mock_open(read_data="data")) as mock_file:
assert open("path/to/open").read() == "data"
mock_file.assert_called_with("path/to/open")
If you want to use patch as a decorator, using mock_open()'s result as the new= argument to patch can be a little bit weird. Instead, use patch's new_callable= argument and remember that every extra argument that patch doesn't use will be passed to the new_callable function, as described in the patch documentation:
patch() takes arbitrary keyword arguments. These will be passed to the Mock (or new_callable) on construction.
#patch("builtins.open", new_callable=mock_open, read_data="data")
def test_patch(mock_file):
assert open("path/to/open").read() == "data"
mock_file.assert_called_with("path/to/open")
Remember that in this case patch will pass the mocked object as an argument to your test function.
Python 2
You need to patch __builtin__.open instead of builtins.open and mock is not part of unittest, you need to pip install and import it separately:
from mock import patch, mock_open
with patch("__builtin__.open", mock_open(read_data="data")) as mock_file:
assert open("path/to/open").read() == "data"
mock_file.assert_called_with("path/to/open")
The way to do this has changed in mock 0.7.0 which finally supports mocking the python protocol methods (magic methods), particularly using the MagicMock:
http://www.voidspace.org.uk/python/mock/magicmock.html
An example of mocking open as a context manager (from the examples page in the mock documentation):
>>> open_name = '%s.open' % __name__
>>> with patch(open_name, create=True) as mock_open:
... mock_open.return_value = MagicMock(spec=file)
...
... with open('/some/path', 'w') as f:
... f.write('something')
...
<mock.Mock object at 0x...>
>>> file_handle = mock_open.return_value.__enter__.return_value
>>> file_handle.write.assert_called_with('something')
With the latest versions of mock, you can use the really useful mock_open helper:
mock_open(mock=None, read_data=None)
A helper function to create a
mock to replace the use of open. It works for open called directly or
used as a context manager.
The mock argument is the mock object to configure. If None (the
default) then a MagicMock will be created for you, with the API
limited to methods or attributes available on standard file handles.
read_data is a string for the read method of the file handle to
return. This is an empty string by default.
>>> from mock import mock_open, patch
>>> m = mock_open()
>>> with patch('{}.open'.format(__name__), m, create=True):
... with open('foo', 'w') as h:
... h.write('some stuff')
>>> m.assert_called_once_with('foo', 'w')
>>> handle = m()
>>> handle.write.assert_called_once_with('some stuff')
To use mock_open for a simple file read() (the original mock_open snippet already given on this page is geared more for write):
my_text = "some text to return when read() is called on the file object"
mocked_open_function = mock.mock_open(read_data=my_text)
with mock.patch("__builtin__.open", mocked_open_function):
with open("any_string") as f:
print f.read()
Note as per docs for mock_open, this is specifically for read(), so won't work with common patterns like for line in f, for example.
Uses python 2.6.6 / mock 1.0.1
The top answer is useful but I expanded on it a bit.
If you want to set the value of your file object (the f in as f) based on the arguments passed to open() here's one way to do it:
def save_arg_return_data(*args, **kwargs):
mm = MagicMock(spec=file)
mm.__enter__.return_value = do_something_with_data(*args, **kwargs)
return mm
m = MagicMock()
m.side_effect = save_arg_return_array_of_data
# if your open() call is in the file mymodule.animals
# use mymodule.animals as name_of_called_file
open_name = '%s.open' % name_of_called_file
with patch(open_name, m, create=True):
#do testing here
Basically, open() will return an object and with will call __enter__() on that object.
To mock properly, we must mock open() to return a mock object. That mock object should then mock the __enter__() call on it (MagicMock will do this for us) to return the mock data/file object we want (hence mm.__enter__.return_value). Doing this with 2 mocks the way above allows us to capture the arguments passed to open() and pass them to our do_something_with_data method.
I passed an entire mock file as a string to open() and my do_something_with_data looked like this:
def do_something_with_data(*args, **kwargs):
return args[0].split("\n")
This transforms the string into a list so you can do the following as you would with a normal file:
for line in file:
#do action
I might be a bit late to the game, but this worked for me when calling open in another module without having to create a new file.
test.py
import unittest
from mock import Mock, patch, mock_open
from MyObj import MyObj
class TestObj(unittest.TestCase):
open_ = mock_open()
with patch.object(__builtin__, "open", open_):
ref = MyObj()
ref.save("myfile.txt")
assert open_.call_args_list == [call("myfile.txt", "wb")]
MyObj.py
class MyObj(object):
def save(self, filename):
with open(filename, "wb") as f:
f.write("sample text")
By patching the open function inside the __builtin__ module to my mock_open(), I can mock writing to a file without creating one.
Note: If you are using a module that uses cython, or your program depends on cython in any way, you will need to import cython's __builtin__ module by including import __builtin__ at the top of your file. You will not be able to mock the universal __builtin__ if you are using cython.
If you don't need any file further, you can decorate the test method:
#patch('builtins.open', mock_open(read_data="data"))
def test_testme():
result = testeme()
assert result == "data"
To patch the built-in open() function with unittest:
This worked for a patch to read a json config.
class ObjectUnderTest:
def __init__(self, filename: str):
with open(filename, 'r') as f:
dict_content = json.load(f)
The mocked object is the io.TextIOWrapper object returned by the open() function
#patch("<src.where.object.is.used>.open",
return_value=io.TextIOWrapper(io.BufferedReader(io.BytesIO(b'{"test_key": "test_value"}'))))
def test_object_function_under_test(self, mocker):
I'm using pytest in my case, and the good news is that in Python 3 the unittest library can also be imported and used without issue.
Here is my approach. First, I create a conftest.py file with reusable pytest fixture(s):
from functools import cache
from unittest.mock import MagicMock, mock_open
import pytest
from pytest_mock import MockerFixture
class FileMock(MagicMock):
def __init__(self, mocker: MagicMock = None, **kwargs):
super().__init__(**kwargs)
if mocker:
self.__dict__ = mocker.__dict__
# configure mock object to replace the use of open(...)
# note: this is useful in scenarios where data is written out
_ = mock_open(mock=self)
#property
def read_data(self):
return self.side_effect
#read_data.setter
def read_data(self, mock_data: str):
"""set mock data to be returned when `open(...).read()` is called."""
self.side_effect = mock_open(read_data=mock_data)
#property
#cache
def write_calls(self):
"""a list of calls made to `open().write(...)`"""
handle = self.return_value
write: MagicMock = handle.write
return write.call_args_list
#property
def write_lines(self) -> str:
"""a list of written lines (as a string)"""
return ''.join([c[0][0] for c in self.write_calls])
#pytest.fixture
def mock_file_open(mocker: MockerFixture) -> FileMock:
return FileMock(mocker.patch('builtins.open'))
Where I decided to make the read_data as a property, in order to be more pythonic. It can be assigned in a test function with whatever data that open() needs to return.
In my test file, named something like test_it_works.py, I have a following test case to confirm intended functionality:
from unittest.mock import call
def test_mock_file_open_and_read(mock_file_open):
mock_file_open.read_data = 'hello\nworld!'
with open('/my/file/here', 'r') as in_file:
assert in_file.readlines() == ['hello\n', 'world!']
mock_file_open.assert_called_with('/my/file/here', 'r')
def test_mock_file_open_and_write(mock_file_open):
with open('/out/file/here', 'w') as f:
f.write('hello\n')
f.write('world!\n')
f.write('--> testing 123 :-)')
mock_file_open.assert_called_with('/out/file/here', 'w')
assert call('world!\n') in mock_file_open.write_calls
assert mock_file_open.write_lines == """\
hello
world!
--> testing 123 :-)
""".rstrip()
Check out the gist here.
Sourced from a github snippet to patch read and write functionality in python.
The source link is over here
import configparser
import pytest
simpleconfig = """[section]\nkey = value\n\n"""
def test_monkeypatch_open_read(mockopen):
filename = 'somefile.txt'
mockopen.write(filename, simpleconfig)
parser = configparser.ConfigParser()
parser.read(filename)
assert parser.sections() == ['section']
def test_monkeypatch_open_write(mockopen):
parser = configparser.ConfigParser()
parser.add_section('section')
parser.set('section', 'key', 'value')
filename = 'somefile.txt'
parser.write(open(filename, 'wb'))
assert mockopen.read(filename) == simpleconfig
SIMPLE #patch with assert
If you're wanting to use #patch. The open() is called inside the handler and is read.
#patch("builtins.open", new_callable=mock_open, read_data="data")
def test_lambda_handler(self, mock_open_file):
lambda_handler(event, {})
Related
How am I supposed to write this test? I've tried the various options listed but each returns the same failed test:
import zipfile
from mock import Mock, patch
def unzip_file(fp):
with zipfile.ZipFile(fp, 'r') as z:
z.extractall('dir')
#patch('zipfile.ZipFile')
def test_unzip_file(m_zipfile):
# I have tried the following...
# m_zipfile.__enter__.extractall = Mock()
# m_zipfile.extractall = Mock()
# m_zipfile.return_value.__enter__.return_value = Mock()
m_zipfile.return_value.__enter__.return_value.extractall = Mock()
unzip_file('test')
m_zipfile.assert_called_with('test', 'r') # this test passes
m_zipfile.extractall.assert_called_with('dir') # this test fails
I tried to use this answer as a guide but I'm still lost as to how to properly do this. The actual function in our code is more complex with additional parameters but I am trying to start at the base first.
The failure...
E AssertionError: expected call not found.
E Expected: extractall('dir')
E Actual: not called.
You're pretty close, you just need a reference to the mock within the context manager to assert against
#patch('zipfile.ZipFile')
def test_unzip_file(m_zipfile):
m_extractall = Mock()
m_zipfile.return_value.__enter__.return_value.extractall = m_extractall
unzip_file('test')
m_zipfile.assert_called_with('test', 'r') # this test passes
m_extractall.assert_called_with('dir') # and this one does, too
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.
While using mockito for unit testing in python, I came across an issue that I cannot find a solution for. I am trying to patch the usage of io.BytesIO in a given class method. The following code shows a simplified version where the issue occurs:
from mockito import mock, patch, when
from io import BytesIO
class Foo:
def bar(self):
buffer = io.BytesIO()
# ...
return buffer.getvalue()
def test_foo():
bytesIO_mock = mock(strict=True)
when(bytesIO_mock).getvalue().thenReturn('data')
patch(BytesIO.__new__, lambda: bytesIO_mock)
result = Foo().bar()
assert result == 'data'
I am getting the following error when I execute the test:
/venv/lib/python3.6/site-packages/mockito/mockito.py:270: in patch
when2(fn, Ellipsis).thenAnswer(replacement)
/venv/lib/python3.6/site-packages/mockito/mockito.py:245: in when2
return invocation.StubbedInvocation(theMock, name)(*args, **kwargs)
/venv/lib/python3.6/site-packages/mockito/invocation.py:284: in __call__
self.mock.stub(self.method_name)
/venv/lib/python3.6/site-packages/mockito/mocking.py:117: in stub
self.replace_method(method_name, original_method)
/venv/lib/python3.6/site-packages/mockito/mocking.py:108: in replace_method
self.set_method(method_name, new_mocked_method)
self = <mockito.mocking.Mock object at 0x10d50cb38>, method_name = '__new__'
new_method = <function Mock.replace_method.<locals>.new_mocked_method at 0x10d753e18>
def set_method(self, method_name, new_method):
> setattr(self.mocked_obj, method_name, new_method)
E TypeError: can't set attributes of built-in/extension type '_io.BytesIO'
/venv/lib/python3.6/site-packages/mockito/mocking.py:74: TypeError
Is there any solution to this issue, or is it just the case it is not possible to mock certain objects in python?
Instead of using patch you can simply mock the response from io.BytesIO() as follows:
def test_foo():
bytesIO_mock = mock(strict=True)
when(bytesIO_mock).getvalue().thenReturn('data')
when(io).BytesIO().thenReturn(bytesIO_mock)
result = Foo().bar()
assert result == 'data'
As a rule of thumb, all objects in Python can be mocked as everything in Python is an object. If you can not mock it, it is probably due to a limitation in the testing library/framework being used.
Function foo prints to console. I want to test the console print. How can I achieve this in python?
Need to test this function, has NO return statement :
def foo(inStr):
print "hi"+inStr
My test :
def test_foo():
cmdProcess = subprocess.Popen(foo("test"), stdout=subprocess.PIPE)
cmdOut = cmdProcess.communicate()[0]
self.assertEquals("hitest", cmdOut)
You can easily capture standard output by just temporarily redirecting sys.stdout to a StringIO object, as follows:
import StringIO
import sys
def foo(inStr):
print "hi"+inStr
def test_foo():
capturedOutput = StringIO.StringIO() # Create StringIO object
sys.stdout = capturedOutput # and redirect stdout.
foo('test') # Call unchanged function.
sys.stdout = sys.__stdout__ # Reset redirect.
print 'Captured', capturedOutput.getvalue() # Now works as before.
test_foo()
The output of this program is:
Captured hitest
showing that the redirection successfully captured the output and that you were able to restore the output stream to what it was before you began the capture.
Note that the code above in for Python 2.7, as the question indicates. Python 3 is slightly different:
import io
import sys
def foo(inStr):
print ("hi"+inStr)
def test_foo():
capturedOutput = io.StringIO() # Create StringIO object
sys.stdout = capturedOutput # and redirect stdout.
foo('test') # Call function.
sys.stdout = sys.__stdout__ # Reset redirect.
print ('Captured', capturedOutput.getvalue()) # Now works as before.
test_foo()
This Python 3 answer uses unittest.mock. It also uses a reusable helper method assert_stdout, although this helper is specific to the function being tested.
import io
import unittest
import unittest.mock
from .solution import fizzbuzz
class TestFizzBuzz(unittest.TestCase):
#unittest.mock.patch('sys.stdout', new_callable=io.StringIO)
def assert_stdout(self, n, expected_output, mock_stdout):
fizzbuzz(n)
self.assertEqual(mock_stdout.getvalue(), expected_output)
def test_only_numbers(self):
self.assert_stdout(2, '1\n2\n')
Note that the mock_stdout arg is passed automatically by the unittest.mock.patch decorator to the assert_stdout method.
A general-purpose TestStdout class, possibly a mixin, can in principle be derived from the above.
For those using Python ≥3.4, contextlib.redirect_stdout also exists, but it seems to serve no benefit over unittest.mock.patch.
If you happen to use pytest, it has builtin output capturing. Example (pytest-style tests):
def eggs():
print('eggs')
def test_spam(capsys):
eggs()
captured = capsys.readouterr()
assert captured.out == 'eggs\n'
You can also use it with unittest test classes, although you need to passthrough the fixture object into the test class, for example via an autouse fixture:
import unittest
import pytest
class TestSpam(unittest.TestCase):
#pytest.fixture(autouse=True)
def _pass_fixtures(self, capsys):
self.capsys = capsys
def test_eggs(self):
eggs()
captured = self.capsys.readouterr()
self.assertEqual('eggs\n', captured.out)
Check out Accessing captured output from a test function for more info.
You can also use the mock package as shown below, which is an example from
https://realpython.com/lessons/mocking-print-unit-tests.
from mock import patch
def greet(name):
print('Hello ', name)
#patch('builtins.print')
def test_greet(mock_print):
# The actual test
greet('John')
mock_print.assert_called_with('Hello ', 'John')
greet('Eric')
mock_print.assert_called_with('Hello ', 'Eric')
The answer of #Acumenus says:
It also uses a reusable helper method assert_stdout, although this helper is specific to the function being tested.
the bold part seems a big drawback, thus I would do the following instead:
# extend unittest.TestCase with new functionality
class TestCase(unittest.TestCase):
def assertStdout(self, expected_output):
return _AssertStdoutContext(self, expected_output)
# as a bonus, this syntactical sugar becomes possible:
def assertPrints(self, *expected_output):
expected_output = "\n".join(expected_output) + "\n"
return _AssertStdoutContext(self, expected_output)
class _AssertStdoutContext:
def __init__(self, testcase, expected):
self.testcase = testcase
self.expected = expected
self.captured = io.StringIO()
def __enter__(self):
sys.stdout = self.captured
return self
def __exit__(self, exc_type, exc_value, tb):
sys.stdout = sys.__stdout__
captured = self.captured.getvalue()
self.testcase.assertEqual(captured, self.expected)
this allows for the much nicer and much more re-usable:
# in a specific test case, the new method(s) can be used
class TestPrint(TestCase):
def test_print1(self):
with self.assertStdout("test\n"):
print("test")
by using a straight forward context manager. (It might also be desirable to append "\n" to expected_output since print() adds a newline by default. See next example...)
Furthermore, this very nice variant (for an arbitrary number of prints!)
def test_print2(self):
with self.assertPrints("test1", "test2"):
print("test1")
print("test2")
is possible now.
You can also capture the standard output of a method using contextlib.redirect_stdout:
import unittest
from contextlib import redirect_stdout
from io import StringIO
class TestMyStuff(unittest.TestCase):
# ...
def test_stdout(self):
with redirect_stdout(StringIO()) as sout:
my_command_that_prints_to_stdout()
# the stream replacing `stdout` is available outside the `with`
# you may wish to strip the trailing newline
retval = sout.getvalue().rstrip('\n')
# test the string captured from `stdout`
self.assertEqual(retval, "whatever_retval_should_be")
Gives you a locally scoped solution. It is also possible to capture the standard error using contextlib.redirect_stderr().
Another variant is leaning on the logging module rather than print(). This module also has a suggestion of when to use print in the documentation:
Display console output for ordinary usage of a command line script or program
PyTest has built-in support for testing logging messages.
I have a function that creates a temporary directory, switches to that temporary directory, performs some work, and then switches back to the original directory. I am trying to write a unit test that tests this. I don't have a problem verifying that the current directory was changed to the temp dir and changed back again, but I'm having a problem verifying that the important stuff took place in between those calls.
My original idea was to abstract the function into three sub functions so that I could test the call order. I can replace each of the three sub functions with mocks to verify that they are called -- however, I am still presented with the issue of verifying the order. On a mock I can use assert_has_calls, but upon what object do I call that function?
Here is the class I'm trying to test:
import shutil
import os
import subprocess
import tempfile
import pkg_resources
class Converter:
def __init__(self, encoded_file_path):
self.encoded_file_path = encoded_file_path
self.unencoded_file_path = None
self.original_path = None
self.temp_dir = None
def change_to_temp_dir(self):
self.original_path = os.getcwd()
self.temp_dir = tempfile.mkdtemp()
os.chdir(self.temp_dir)
def change_to_original_dir(self):
os.chdir(self.original_path)
shutil.rmtree(self.temp_dir)
def do_stuff(self):
pass
def run(self):
self.change_to_temp_dir()
self.do_stuff()
self.change_to_original_dir()
This is as far as I got writing the test case:
def test_converter(self, pkg_resources, tempfile, subprocess, os, shutil):
encoded_file_path = Mock()
converter = Converter(encoded_file_path)
converter.change_to_temp_dir = Mock()
converter.do_stuff= Mock()
converter.change_to_original_dir = Mock()
assert converter.encoded_file_path == encoded_file_path
assert converter.unencoded_file_path is None
converter.run()
Now that I have each function mocked, I can verify THAT they were called, but not in what ORDER. How do I go about doing this?
One workaround would to be to create a separate mock object, attach methods to it and use assert_has_calls() to check the call order:
converter = Converter(encoded_file_path)
converter.change_to_temp_dir = Mock()
converter.do_stuff = Mock()
converter.change_to_original_dir = Mock()
m = Mock()
m.configure_mock(first=converter.change_to_temp_dir,
second=converter.do_stuff,
third=converter.change_to_original_dir)
converter.run()
m.assert_has_calls([call.first(), call.second(), call.third()])