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    "info": {
        "author": "Kyle Marek-Spartz",
        "author_email": "kyle.marek.spartz@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 2.7"
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        "description": "Props\n=====\n\nProperty-based testing for Python \u00e0 la\n`QuickCheck <http://en.wikipedia.org/wiki/QuickCheck>`__.\n\n``for_all``\n-----------\n\n``for_all`` takes a list of generators (see below) and a property. It\nthen tests the property for arbitrary values of the generators.\n\nHere\u2019s an example testing the commutative and associative properties of\n``int``\\ s:\n\n.. code:: python\n\n   for_all(int, int)(lambda a, b: a + b == b + a)\n   for_all(int, int)(lambda a, b: a * b == b * a)\n   for_all(int, int, int)(lambda a, b, c: c * (a + b) == a * c + b * c)\n\nProperties\n----------\n\nProperties are functions which take instances of generators and return\n``True`` if their condition is met:\n\n.. code:: python\n\n   def prop_associative(a, b, c):\n       return a + (b + c) == (a + b) + c\n\n   for_all(int, int, int)(prop_associative)\n   for_all(float, float, float)(prop_associative)  # Warning: float isn't actually associative!\n\nProperties can also fail early by raising ``AssertionError``:\n\n.. code:: python\n\n   def prop_list_append_pop(list, element):\n       if element not in list:\n           list.append(element)\n           assert element in list\n           list.pop()\n           return element not in list\n       return element in list\n\n   for_all(list, int)(prop_list_append_pop)\n\nGenerators\n----------\n\n*Note:* These are not the same as Python generators. We should rename\nthem. Generaters? Blech.\n\nA generator is a specification of a set of possible Python objects. A\ngenerator is either:\n\n-  One of the following built-in types:\n\n   -  ``None``, ``bool``, ``int``, ``float``, ``long``, ``complex``,\n      ``str``, ``tuple``, ``set``, ``list``, or ``dict``\n\n-  A class that implements the ``ArbitraryInterface``\n-  Or constructed using the generator combinators.\n\nCombinators\n~~~~~~~~~~~\n\n-  ``maybe_a``\n\n   -  Generates either an arbitrary value of the specified generator or\n      ``None``.\n\n-  ``maybe_an``\n\n   -  An alias for ``maybe_a``. Provided for syntactic convenience.\n\n-  ``one_of``\n\n   -  Generates an arbitrary value of one of the specified generators.\n\n-  ``tuple_of``\n\n   -  Generates a tuple by generating values for each of the specified\n      generators.\n\n-  ``set_of``\n\n   -  Generates a homogeneous set of the specified generator. You can\n      generate non-homogeneous sets using ``set``.\n\n-  ``list_of``\n\n   -  Generates a homogeneous list of the specified generator. You can\n      generate non-homogeneous lists using ``list``.\n\n-  ``dict_of``\n\n   -  Generates a homogeneous dict of the specified generators using\n      kwargs. You can generate non-homogeneous dicts using ``dict``.\n\n``arbitrary``\n-------------\n\n``arbitrary`` takes a generator and returns a single instance of the\ngenerator.\n\nArbitraryInterface\n------------------\n\nWe provide a mixin with one classmethod, ``arbitrary``, which raises\n``NotImplementedError``. To implement generators for your own classes,\nplease inherit from ArbitraryInterface and provide an implementation for\n``arbitrary``.\n\nHere\u2019s an example implementation of a Binary Tree class:\n\n.. code:: python\n\n   class BinaryTree(ArbitraryInterface):\n       ...\n       @classmethod\n       def arbitrary(cls):\n           return arbitrary(one_of(Leaf, Node))\n\n   class Leaf(BinaryTree):\n       ...\n       @classmethod\n       def arbitrary(cls):\n           return cls(...)  # an instance of Leaf.\n\n   class Node(BinaryTree):\n       ...\n       @classmethod\n       def arbitrary(cls):\n           return cls(\n               ...\n               # This is equivalent:\n               arbitrary(BinaryTree),\n               # to this:\n               BinaryTree.arbitrary()\n           )  # an instance of Node with two subtrees.\n\nAbstractTestArbitraryInterface\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nWe also provide an ``AbstractTestArbitraryInterface`` with you can mixin\nto your test cases for each class that implements ``ArbitraryInterface``\nto ensure the ``arbitrary`` method is implemented:\n\n.. code:: python\n\n   class TestBinaryTree(AbstractTestArbitraryInterface,\n                        TestCase):\n       def setUp(self):\n           self.cls = BinaryTree\n\nTo Do\n=====\n\n-  all built in types: http://docs.python.org/2/library/stdtypes.html\n-  ranges\n-  import some faker generators for more semantic random values\n\n\n",
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