Dynamically created method and decorator, got error 'functools.partial' object has no attribute '__module__'

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面向向阳花
面向向阳花 2020-12-31 01:58

I am currently using EndpointsModel to create a RESTful API for all my models on AppEngine. Since it is RESTful, these api have a lot of repeat code which I want to avoid.

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  •  南方客
    南方客 (楼主)
    2020-12-31 02:34

    I also stumbled upon this, I was really surprised, for me the issue was that partial objects are missing certain attributes, specifically __module__ and __name__

    Being that wraps by default uses functools.WRAPPER_ASSIGNMENTS to update attributes, which defaults to ('__module__', '__name__', '__doc__') in python 2.7.6 anyway, there are a couple ways of dealing with this ...

    Update only present attributes ...

    import functools
    import itertools
    
    def wraps_safely(obj, attr_names=functools.WRAPPER_ASSIGNMENTS):
        return wraps(obj, assigned=itertools.ifilter(functools.partial(hasattr, obj), attr_names))
    
    >>> def foo():
    ...     """ Ubiquitous foo function ...."""
    ... 
    >>> functools.wraps(partial(foo))(foo)()
    Traceback (most recent call last):
      File "", line 1, in 
      File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/functools.py", line 33, in update_wrapper
    setattr(wrapper, attr, getattr(wrapped, attr))
    AttributeError: 'functools.partial' object has no attribute '__module__'
    >>> wraps_safely(partial(foo))(foo)()
    >>> 
    

    Here we simply filter out all those attribute which aren't present.

    Another approach would be to strictly deal with partial objects only, you could fold wraps with singledispatch and create wrapped partial objects whose attributes would be taken from the deepest func attribute.

    Something along the lines:

    import functools
    
    def wraps_partial(wrapper, *args, **kwargs):
        """ Creates a callable object whose attributes will be set from the partials nested func attribute ..."""
        wrapper = wrapper.func
        while isinstance(wrapper, functools.partial):
            wrapper = wrapper.func
        return functools.wraps(wrapper, *args, **kwargs)
    
    def foo():
        """ Foo function.
        :return: None """
        pass
    
    >>> wraps_partial(partial(partial(foo)))(lambda : None).__doc__
    ' Foo Function, returns None '
    >>> wraps_partial(partial(partial(foo)))(lambda : None).__name__
    'foo'
    >>> wraps_partial(partial(partial(foo)))(lambda : None)()
    >>> pfoo = partial(partial(foo))
    >>> @wraps_partial(pfoo)
    ... def not_foo():
    ...     """ Not Foo function ... """
    ... 
    >>> not_foo.__doc__
    ' Foo Function, returns None '
    >>> not_foo.__name__
    'foo'
    >>>
    

    This is slightly better since now we can get the original functions docs which before defaulted to using the partial objects doc string.

    This can be modified to only search if the current partial object doesn't already have the set attribute, which should be slightly faster when nesting many partial objects ...

    UPDATE

    It seems that python(CPython) 3 (at least 3.4.3) doesn't have this issue, since I don't know nor should I assume all versions of python 3 or other implementations such as Jython also share this issue here is another future ready approach

    from functools import wraps, partial, WRAPPER_ASSIGNMENTS
    
    try:
        wraps(partial(wraps))(wraps)
    except AttributeError:
        @wraps(wraps)
        def wraps(obj, attr_names=WRAPPER_ASSIGNMENTS, wraps=wraps):
            return wraps(obj, assigned=(name for name in attr_names if hasattr(obj, name))) 
    

    a couple things to note:

    • we define a new wraps function only if we fail to wrap a partial, in case future versions of python2 or other versions fix this issue.
    • we use the original wraps to copy the docs and other info
    • we don't use ifilter since it was removed in python3, I've timeit with and without ifilter but the results where inconclusive, at least in python (CPython) 2.7.6, the difference was marginal at best either way...

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