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        "author": "yakobu",
        "author_email": "ronenya4321@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Natural Language :: English",
            "Operating System :: POSIX",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3 :: Only",
            "Programming Language :: Python :: Implementation :: CPython",
            "Topic :: Software Development :: Pre-processors"
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        "description": "Recursive Decorator\n===================\n\n.. image:: https://img.shields.io/github/license/yakobu/recursive_decorator.svg\n    :alt: GitHub license\n    :target: https://github.com/yakobu/recursive_decorator\n.. image:: https://badge.fury.io/py/recursive-decorator.svg\n    :target: https://badge.fury.io/py/recursive-decorator\n.. image:: https://travis-ci.org/yakobu/recursive_decorator.svg?branch=master\n    :target: https://travis-ci.org/yakobu/recursive_decorator\n.. image:: https://coveralls.io/repos/github/yakobu/recursive_decorator/badge.svg?branch=master\n    :target: https://coveralls.io/github/yakobu/recursive_decorator?branch=master\n\n\n\nDecorator to apply a given decorator recursively on all function, inside a function/method, recursively.\n\nWhat is ``recursive_decorator``?\n--------------------------------\n\n``recursive_decorator`` is a decorator that allows us to **decorate/trasform all functions along the stack call** at runtime, motivated by the need to add/transform logics, to known\\unknown functions, along the stack calls.\n\nNotes:\n++++++\n* Functions/Methods will not be replaced, new instances will be returned.\n* Function/Methods cannot be wrapped more then once with same transformer/decorator.\n\n\nInstalling\n----------\n.. code-block:: console\n\n    $ pip install recursive_decorator\n\n\nUsage\n-----\nimport recursive_decorator\n\n.. code-block:: python\n\n    from recursive_decorator import recursive_decorator\n\ndefine your decorator to apply recursively on all functions.\n\n.. code-block:: python\n\n   >>> def decorator(f):\n   ...:    def wrapper(*args, **kwargs):\n   ...:        print(f.__name__)\n   ...:        return f(*args, **kwargs)\n   ...:    return wrapper\n\n\nNow using your decorator on function without using recursive_decorator will leads to the following output\n\n.. code-block:: python\n\n   >>> @decorator\n   ...:def main_function():\n   ...:   sub_function()\n\n   >>> main_function()\n   main_function\n\n\nUsing recursive_decorator leads to\n\n.. code-block:: python\n\n   >>> @recursive_decorator(decorator)\n   ...:def main_function():\n   ...:   sub_function()\n\n   >>> main_function()\n   main_function\n   sub_function\n\n\nFurthermore, if sub_function has function calls, they will decorated to\n\n.. code-block:: python\n\n   >>> def sub_function():\n   ...:    another_function()\n\n   >>> @recursive_decorator(decorator)\n   ...:def main_function():\n   ...:   sub_function()\n\n   >>> main_function()\n   main_function\n   sub_function\n   another_function\n\n\nand so on...\n\n\nExamples\n--------\n\nStop on Execption\n+++++++++++++++++\n\nWe can wrap all functions with try except...\n\n.. code-block:: python\n\n       >>> import sys\n       >>> import ipdb\n       >>> from recursive_decorator import recursive_decorator\n\n       >>> def wrap_function_with_try_except(f):\n       ...:    def transformed_func(*args, **kwargs):\n       ...:        try:\n       ...:            return f(*args, **kwargs)\n       ...:        except:\n       ...:            ipdb.set_trace(sys._getframe().f_back)\n       ...:    return transformed_func\n\n       >>> def throws_exception():\n       ...:    raise Exception\n\n\n       >>> @recursive_decorator(wrap_function_with_try_except)\n       ...:def function():\n       ...:    throws_exception()\n       ...:    pass\n\n       >>> function()\n          21     throws_exception()\n     ---> 22     pass\n          23\n\nIf function will throw an error... ipdb session will start.\n\n\nProfiler\n++++++++\n\nWe can set time profiler for all running functions.\n\n.. code-block:: python\n\n   >>> import time\n\n   >>> from recursive_decorator import recursive_decorator\n\n\n   >>> def duration_transformer(f):\n   ...:    def transformed_func(*args, **kwargs):\n   ...:        start_time = time.time()\n   ...:        value = f(*args, **kwargs)\n   ...:        end_time = time.time()\n   ...:        print(\"function {} duration is {} minutes\"\n   ...:              .format(f.__name__, end_time - start_time))\n   ...:        return value\n   ...:    return transformed_func\n\n\n   >>> def waiting_function():\n   ...:    time.sleep(5)\n\n\n   >>> @recursive_decorator(duration_transformer)\n   ...:def function():\n   ...:    waiting_function()\n\n   >>> function()\n   function waiting_function duration is 5.00511908531189 minutes\n   function function duration is 5.006134510040283 minutes\n\n\n\n",
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