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167 lines
7.5 KiB
Text
167 lines
7.5 KiB
Text
Metadata-Version: 1.1
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Name: wrapt
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Version: 1.12.1
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Summary: Module for decorators, wrappers and monkey patching.
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Home-page: https://github.com/GrahamDumpleton/wrapt
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Author: Graham Dumpleton
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Author-email: Graham.Dumpleton@gmail.com
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License: BSD
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Description: wrapt
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=====
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|Travis| |AppVeyor| |Coveralls| |PyPI|
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The aim of the **wrapt** module is to provide a transparent object proxy
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for Python, which can be used as the basis for the construction of function
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wrappers and decorator functions.
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The **wrapt** module focuses very much on correctness. It therefore goes
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way beyond existing mechanisms such as ``functools.wraps()`` to ensure that
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decorators preserve introspectability, signatures, type checking abilities
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etc. The decorators that can be constructed using this module will work in
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far more scenarios than typical decorators and provide more predictable and
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consistent behaviour.
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To ensure that the overhead is as minimal as possible, a C extension module
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is used for performance critical components. An automatic fallback to a
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pure Python implementation is also provided where a target system does not
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have a compiler to allow the C extension to be compiled.
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Documentation
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-------------
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For further information on the **wrapt** module see:
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* http://wrapt.readthedocs.org/
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Quick Start
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-----------
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To implement your decorator you need to first define a wrapper function.
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This will be called each time a decorated function is called. The wrapper
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function needs to take four positional arguments:
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* ``wrapped`` - The wrapped function which in turns needs to be called by your wrapper function.
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* ``instance`` - The object to which the wrapped function was bound when it was called.
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* ``args`` - The list of positional arguments supplied when the decorated function was called.
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* ``kwargs`` - The dictionary of keyword arguments supplied when the decorated function was called.
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The wrapper function would do whatever it needs to, but would usually in
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turn call the wrapped function that is passed in via the ``wrapped``
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argument.
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The decorator ``@wrapt.decorator`` then needs to be applied to the wrapper
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function to convert it into a decorator which can in turn be applied to
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other functions.
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::
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import wrapt
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@wrapt.decorator
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def pass_through(wrapped, instance, args, kwargs):
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return wrapped(*args, **kwargs)
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@pass_through
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def function():
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pass
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If you wish to implement a decorator which accepts arguments, then wrap the
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definition of the decorator in a function closure. Any arguments supplied
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to the outer function when the decorator is applied, will be available to
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the inner wrapper when the wrapped function is called.
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::
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import wrapt
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def with_arguments(myarg1, myarg2):
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@wrapt.decorator
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def wrapper(wrapped, instance, args, kwargs):
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return wrapped(*args, **kwargs)
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return wrapper
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@with_arguments(1, 2)
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def function():
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pass
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When applied to a normal function or static method, the wrapper function
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when called will be passed ``None`` as the ``instance`` argument.
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When applied to an instance method, the wrapper function when called will
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be passed the instance of the class the method is being called on as the
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``instance`` argument. This will be the case even when the instance method
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was called explicitly via the class and the instance passed as the first
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argument. That is, the instance will never be passed as part of ``args``.
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When applied to a class method, the wrapper function when called will be
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passed the class type as the ``instance`` argument.
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When applied to a class, the wrapper function when called will be passed
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``None`` as the ``instance`` argument. The ``wrapped`` argument in this
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case will be the class.
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The above rules can be summarised with the following example.
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::
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import inspect
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@wrapt.decorator
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def universal(wrapped, instance, args, kwargs):
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if instance is None:
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if inspect.isclass(wrapped):
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# Decorator was applied to a class.
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return wrapped(*args, **kwargs)
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else:
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# Decorator was applied to a function or staticmethod.
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return wrapped(*args, **kwargs)
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else:
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if inspect.isclass(instance):
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# Decorator was applied to a classmethod.
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return wrapped(*args, **kwargs)
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else:
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# Decorator was applied to an instancemethod.
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return wrapped(*args, **kwargs)
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Using these checks it is therefore possible to create a universal decorator
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that can be applied in all situations. It is no longer necessary to create
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different variants of decorators for normal functions and instance methods,
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or use additional wrappers to convert a function decorator into one that
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will work for instance methods.
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In all cases, the wrapped function passed to the wrapper function is called
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in the same way, with ``args`` and ``kwargs`` being passed. The
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``instance`` argument doesn't need to be used in calling the wrapped
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function.
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Repository
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----------
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Full source code for the **wrapt** module, including documentation files
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and unit tests, can be obtained from github.
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* https://github.com/GrahamDumpleton/wrapt
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.. |Travis| image:: https://travis-ci.org/GrahamDumpleton/wrapt.svg?branch=develop
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:target: https://travis-ci.org/GrahamDumpleton/wrapt
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.. |Appveyor| image:: https://ci.appveyor.com/api/projects/status/32r7s2skrgm9ubva?svg=true
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:target: https://ci.appveyor.com/project/GrahamDumpleton/wrapt/branch/develop
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.. |Coveralls| image:: https://img.shields.io/coveralls/GrahamDumpleton/wrapt/develop.svg
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:target: https://coveralls.io/github/GrahamDumpleton/wrapt?branch=develop
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.. |PyPI| image:: https://img.shields.io/pypi/v/wrapt.svg
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:target: https://pypi.python.org/pypi/wrapt
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Platform: UNKNOWN
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Classifier: Development Status :: 5 - Production/Stable
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Classifier: License :: OSI Approved :: BSD License
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Classifier: Programming Language :: Python :: 2
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Classifier: Programming Language :: Python :: 2.7
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Classifier: Programming Language :: Python :: 3
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Classifier: Programming Language :: Python :: 3.4
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Classifier: Programming Language :: Python :: 3.5
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Classifier: Programming Language :: Python :: 3.6
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Classifier: Programming Language :: Python :: 3.7
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Classifier: Programming Language :: Python :: 3.8
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Classifier: Programming Language :: Python :: Implementation :: CPython
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Classifier: Programming Language :: Python :: Implementation :: PyPy
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