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        "author": "Dmitry Orlov <me@mosquito.su>",
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        "description": "Object Cacher\n=============\n\nSimple cacher for your objects. Store copy of objects in memory (or pickle in file) and returns copy of that objects. Function arguments it is a cache key.\n\n    >>> from object_cacher import ObjectCacher\n    >>> @ObjectCacher(timeout=5)\n    ... def test(*args):\n    ...     print ('Real call')\n    ...     return args\n    ...\n    >>> test(1,2,3)\n    Real call\n    (1, 2, 3)\n\n    >>> test(1,2,3)\n    (1, 2, 3)\n\n    >>> test(1,2,3,4)\n    Real call\n    (1, 2, 3, 4)\n\n    >>> test(1,2,3,4)\n    ... (1, 2, 3, 4)\n\nMakes cache for results of hard functions or methods.\nFor example you have remote RESTful api with a lot of dictionaries. You may cache it:\n\n    >>> from urllib import urlopen\n    >>> from object_cacher import ObjectCacher\n    >>> @ObjectCacher(timeout=60)\n    ... def get_api():\n    ...     print \"This real call\"\n    ...     return urlopen('https://api.github.com/').read()\n    ...\n    >>> get_api()\n    This real call\n    '{\"current_user_url\":\"https://api.github.com/user\", ...'\n    >>> get_api()\n    '{\"current_user_url\":\"https://api.github.com/user\", ...'\n\nAs result you made http request only once.\n\nFor methods you may use it like this:\n\n    >>> from urllib import urlopen\n    >>> from object_cacher import ObjectCacher\n    >>> class API(object):\n    ...     @ObjectCacher(timeout=60, ignore_self=True)\n    ...     def get_methods(self):\n    ...         print \"Real call\"\n    ...         return urlopen('https://api.github.com/').read()\n    ...\n    >>> a = API()\n    >>> a.get_methods()\n    Real call\n    '{\"current_user_url\":\"https://api.github.com/user\", ...'\n    >>> b = API()\n    >>> b.get_methods()\n    '{\"current_user_url\":\"https://api.github.com/user\", ...'\n\nIf ignore_self parameter is set, cache will be shared by all instances. Otherwise cache for instances will be split.\n\nAlso you may use persistent cache.\nThe \"ObjectPersistentCacher\" class-decorator makes file-based pickle-serialized cache storage.\nWhen you want to keep cache after rerun you must determine cache id:\n\n    >>> from urllib import urlopen\n    >>> from object_cacher import ObjectCacher\n    >>> class API(object):\n    ...     @ObjectPersistentCacher(timeout=60, ignore_self=True, oid='com.github.api.listofmethods')\n    ...     def get_methods(self):\n    ...         print \"Real call\"\n    ...         return urlopen('https://api.github.com/').read()\n    ...\n    >>> a = API()\n    >>> a.get_methods()\n    Real call\n    '{\"current_user_url\":\"https://api.github.com/user\", ...'\n    >>> b = API()\n    >>> b.get_methods()\n    '{\"current_user_url\":\"https://api.github.com/user\", ...'\n\nThat is keep cache after rerun.\n\nYou may change cache dir for ObjectPersistentCacher via changing 'CACHE_DIR' class-property.\n\n    >>> ObjectPersistentCacher.CACHE_DIR = '/var/tmp/my_cache'\n\n\nInstallation\n++++++++++++\n\nYou may install from pypi\n\n        pip install object_cacher\n\nor manual\n\n        python setup.py install",
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