Customizing unittest.mock.mock_open for iteration

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How should I customize unittest.mock.mock_open to handle this code?

file: impexpdemo.py
def import_register(register_fn):
    with open(register_fn) as f:
           


        
3条回答
  •  离开以前
    2020-12-01 11:17

    The mock_open() object does indeed not implement iteration.

    If you are not using the file object as a context manager, you could use:

    m = unittest.mock.MagicMock(name='open', spec=open)
    m.return_value = iter(self.TEST_TEXT)
    
    with unittest.mock.patch('builtins.open', m):
    

    Now open() returns an iterator, something that can be directly iterated over just like a file object can be, and it'll also work with next(). It can not, however, be used as a context manager.

    You can combine this with mock_open() then provide a __iter__ and __next__ method on the return value, with the added benefit that mock_open() also adds the prerequisites for use as a context manager:

    # Note: read_data must be a string!
    m = unittest.mock.mock_open(read_data=''.join(self.TEST_TEXT))
    m.return_value.__iter__ = lambda self: self
    m.return_value.__next__ = lambda self: next(iter(self.readline, ''))
    

    The return value here is a MagicMock object specced from the file object (Python 2) or the in-memory file objects (Python 3), but only the read, write and __enter__ methods have been stubbed out.

    The above doesn't work in Python 2 because a) Python 2 expects next to exist, not __next__ and b) next is not treated as a special method in Mock (rightly so), so even if you renamed __next__ to next in the above example the type of the return value won't have a next method. For most cases it would be enough to make the file object produced an iterable rather than an iterator with:

    # Python 2!
    m = mock.mock_open(read_data=''.join(self.TEST_TEXT))
    m.return_value.__iter__ = lambda self: iter(self.readline, '')
    

    Any code that uses iter(fileobj) will then work (including a for loop).

    There is a open issue in the Python tracker that aims to remedy this gap.

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