问题
How do I test the following code with mocks (using mocks, the patch decorator and sentinels provided by Michael Foord's Mock framework):
def testme(filepath):
with open(filepath, 'r') as f:
return f.read()
回答1:
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')
回答2:
mock_open is part of mock framework and is very simple to use. patch used as context returns the object used to replace the patched one: you can use it to make your test simpler.
Python 3.x
Use builtins
instead of __builtin__
.
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")
Python 2.7
mock
is not part of unittest
and you should patch __builtin__
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")
Decorator case
If you would use patch
as decorator using mock_open()
's result as the new
patch
's argument can be a little bit weird.
In this case is better to use the new_callable
patch
's argument and remember that every extra arguments that patch
doesn't use will be passed to new_callable
function as described in patch documentation.
patch() takes arbitrary keyword arguments. These will be passed to the Mock (or new_callable) on construction.
For instance decorated version for Python 3.x is:
@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 add the mock object as argument of you test function.
回答3:
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')
回答4:
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
回答5:
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.
回答6:
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
来源:https://stackoverflow.com/questions/1289894/how-do-i-mock-an-open-used-in-a-with-statement-using-the-mock-framework-in-pyth