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        "author": "Johan Nestaas",
        "author_email": "johannestaas@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Environment :: Console",
            "Environment :: MacOS X",
            "Environment :: Win32 (MS Windows)",
            "Environment :: X11 Applications :: Qt",
            "License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)",
            "Operating System :: MacOS :: MacOS X",
            "Operating System :: Microsoft :: Windows",
            "Operating System :: POSIX",
            "Programming Language :: Python"
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        "description": "monkeytime\n==========\n\nPatch datetime to use a much quicker strptime implementation.\n\nThis **ONLY** improves strptime when the format string uses padded directives.\n\nThis is the list of supported directives (by far the most common)::\n\n    SUPPORTED_DIRECTIVES = ('%d', '%m', '%Y', '%H', '%M', '%S', '%f')\n\nCheck if your date/time format is supported by calling::\n    \n    datetime.supported_strptime(format_string)\n    # True if supported, False otherwise\n\nOn average, 4 times quicker than the stdlib version, and 40 times quicker\nwhen using pypy!\n\nUsage::\n\n    # insert this one line\n    from monkeytime import datetime\n    # Done migrating code to monkeytime!\n\n    from datetime import datetime\n\n    # Call it once with the specific format string\n    # It will build a new function to quickly parse the string, then run it on\n    # the string you passed it.\n    dt = datetime.strptime('2014-05-30T12:14:15.123456', '%Y-%m-%dT%H:%M:%S.%f')\n    \n    # Now, whenever you use that format again, it will use the function it \n    # built already! All constructed functions are memoized.\n    # Since we usually only use one or two formats in our code to parse logs\n    # and such, the performance of constructing it is negligible.\n\nAll you need is that one line \"from monkeytime import datetime\", and your\nstrptime performance will increase dramatically. \n\n**Make sure it is ABOVE your \"from datetime import datetime\" import line!**\n\nPerformance example::\n\n    $ python timeit_test.py \n    Testing builtin strptime\n    testing ('2015-01-02 03:04:05.001234', '%Y-%m-%d %H:%M:%S.%f')\n    6.80288290977 seconds\n    testing ('05-06 12:15:18', '%m-%d %H:%M:%S')\n    5.81049013138 seconds\n    testing ('2010', '%Y')\n    4.29107117653 seconds\n    testing ('1905/08/05', '%Y/%m/%d')\n    4.92634987831 seconds\n    testing ('14:05:03.123456', '%H:%M:%S.%f')\n    5.6812889576 seconds\n    Testing monkeytime strptime\n    testing ('2015-01-02 03:04:05.001234', '%Y-%m-%d %H:%M:%S.%f')\n    1.83126211166 seconds\n    testing ('05-06 12:15:18', '%m-%d %H:%M:%S')\n    1.5586848259 seconds\n    testing ('2010', '%Y')\n    0.877351999283 seconds\n    testing ('1905/08/05', '%Y/%m/%d')\n    1.24154901505 seconds\n    testing ('14:05:03.123456', '%H:%M:%S.%f')\n    1.3871409893 seconds\n    3.714860 times as fast\n    3.727816 times as fast\n    4.890935 times as fast\n    3.967906 times as fast\n    4.095682 times as fast\n    Average: 4.079440 times as fast\n\n    $ pypy timeit_test.py \n    Testing builtin strptime\n    testing ('2015-01-02 03:04:05.001234', '%Y-%m-%d %H:%M:%S.%f')\n    2.19319605827 seconds\n    testing ('05-06 12:15:18', '%m-%d %H:%M:%S')\n    1.60669994354 seconds\n    testing ('2010', '%Y')\n    0.858637809753 seconds\n    testing ('1905/08/05', '%Y/%m/%d')\n    1.19449591637 seconds\n    testing ('14:05:03.123456', '%H:%M:%S.%f')\n    1.38721394539 seconds\n    Testing monkeytime strptime\n    testing ('2015-01-02 03:04:05.001234', '%Y-%m-%d %H:%M:%S.%f')\n    0.0362730026245 seconds\n    testing ('05-06 12:15:18', '%m-%d %H:%M:%S')\n    0.0450730323792 seconds\n    testing ('2010', '%Y')\n    0.0332229137421 seconds\n    testing ('1905/08/05', '%Y/%m/%d')\n    0.0321681499481 seconds\n    testing ('14:05:03.123456', '%H:%M:%S.%f')\n    0.0355319976807 seconds\n    60.463593 times as fast\n    35.646591 times as fast\n    25.844747 times as fast\n    37.132876 times as fast\n    39.041260 times as fast\n    Average: 39.625813 times as fast",
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        "keywords": "datetime time parsing",
        "license": "GPLv3+",
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        "name": "monkeytime",
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