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        "author": "Seth M. Morton",
        "author_email": "drtuba78@gmail.com",
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        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "Intended Audience :: Financial and Insurance Industry",
            "Intended Audience :: Information Technology",
            "Intended Audience :: Science/Research",
            "Intended Audience :: System Administrators",
            "License :: OSI Approved :: MIT License",
            "Natural Language :: English",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Scientific/Engineering :: Information Analysis",
            "Topic :: Text Processing",
            "Topic :: Text Processing :: Filters",
            "Topic :: Utilities"
        ],
        "description": "fastnumbers\n===========\n\n.. image:: https://img.shields.io/pypi/v/fastnumbers.svg\n    :target: https://pypi.org/project/fastnumbers/\n\n.. image:: https://img.shields.io/pypi/pyversions/fastnumbers.svg\n    :target: https://pypi.org/project/fastnumbers/\n\n.. image:: https://img.shields.io/pypi/l/fastnumbers.svg\n    :target: https://github.com/SethMMorton/fastnumbers/blob/master/LICENSE\n\n.. image:: https://img.shields.io/travis/SethMMorton/fastnumbers/master.svg?label=travis-ci\n    :target: https://travis-ci.org/SethMMorton/fastnumbers\n\n.. image:: https://ci.appveyor.com/api/projects/status/5ahtcvmt3aoui3mw/branch/master?svg=true\n    :target: https://ci.appveyor.com/project/SethMMorton/fastnumbers/branch/master\n\n.. image:: https://codecov.io/gh/SethMMorton/fastnumbers/branch/master/graph/badge.svg\n    :target: https://codecov.io/gh/SethMMorton/fastnumbers\n\n.. image:: https://api.codacy.com/project/badge/Grade/7221f3d2be3147e9a975d604f1770cfb\n    :target: https://www.codacy.com/app/SethMMorton/fastnumbers\n\nSuper-fast and clean conversions to numbers.\n\n    - Source Code: https://github.com/SethMMorton/fastnumbers\n    - Downloads: https://pypi.org/project/fastnumbers/\n    - Documentation: http://fastnumbers.readthedocs.io/\n\n``fastnumbers`` is a module with the following three objectives:\n\n    #. Provide drop-in replacements for the Python built-in ``int`` and\n       ``float`` that on average are up to 2x faster. These functions\n       should behave *identically* to the Python built-ins except for a few\n       specific corner-cases as mentioned in the\n       `API documentation <http://fastnumbers.readthedocs.io/en/master/api.html>`_.\n    #. Provide a set of convenience functions that wrap the above\n       ``int`` and ``float`` replacements and provides easy, concise,\n       powerful, fast and flexible error handling.\n    #. Provide a set of functions that can be used to rapidly identify if\n       an input *could* be converted to *int* or *float*.\n\n**NOTICE**: The first major version release after Jan 1, 2020 will drop support for Python 2.7.\n\nExamples\n--------\n\nThe below examples showcase the ``fast_float`` function, which is\na fast conversion function with error-handling.\nPlease see the\n`API Documentation <http://fastnumbers.readthedocs.io/en/master/api.html>`_\nfor other functions that are available from ``fastnumbers``.\n\n.. code-block:: python\n\n    >>> from fastnumbers import fast_float, float as fnfloat\n    >>> # Convert string to a float\n    >>> fast_float('56.07')\n    56.07\n    >>> # Unconvertable string returned as-is by default\n    >>> fast_float('bad input')\n    'bad input'\n    >>> # Unconvertable strings can trigger a default value\n    >>> fast_float('bad input', default=0)\n    0\n    >>> # 'default' is also the first optional positional arg\n    >>> fast_float('bad input', 0)\n    0\n    >>> # Integers are converted to floats\n    >>> fast_float(54)\n    54.0\n    >>> # One can ask inf or nan to be substituted with another value\n    >>> fast_float('nan')\n    nan\n    >>> fast_float('nan', nan=0.0)\n    0.0\n    >>> fast_float(float('nan'), nan=0.0)\n    0.0\n    >>> fast_float('56.07', nan=0.0)\n    56.07\n    >>> # The default built-in float behavior can be triggered with\n    >>> # \"raise_on_invalid\" set to True. \n    >>> fast_float('bad input', raise_on_invalid=True) #doctest: +IGNORE_EXCEPTION_DETAIL\n    Traceback (most recent call last):\n      ...\n    ValueError: invalid literal for float(): bad input\n    >>> # A key function can be used to return an alternate value for invalid input\n    >>> fast_float('bad input', key=len)\n    9\n    >>> fast_float(54, key=len)\n    54.0\n    >>> # Single unicode characters can be converted.\n    >>> fast_float(u'\\u2164')  # Roman numeral 5 (V)\n    5.0\n    >>> fast_float(u'\\u2466')  # 7 enclosed in a circle\n    7.0\n\n**NOTE**: If you need locale-dependent conversions, supply the ``fastnumbers``\nfunction of your choice to ``locale.atof``.\n\n.. code-block:: python\n\n    import locale\n    locale.setlocale(locale.LC_ALL, 'de_DE.UTF-8')\n    print(atof('468,5', func=fast_float))  # Prints 468.5\n\nTiming\n------\n\nJust how much faster is ``fastnumbers`` than a pure python implementation?\nPlease see the following Jupyter notebooks for timing information on various Python versions.\n\n    - https://nbviewer.jupyter.org/github/SethMMorton/fastnumbers/blob/master/TIMING_27.ipynb\n    - https://nbviewer.jupyter.org/github/SethMMorton/fastnumbers/blob/master/TIMING_35.ipynb\n    - https://nbviewer.jupyter.org/github/SethMMorton/fastnumbers/blob/master/TIMING_36.ipynb\n\nHow Is ``fastnumbers`` So Fast?\n-------------------------------\n\nCPython goes to great lengths to ensure that your string input is converted to a\nnumber *correctly* (you can prove this to yourself by examining the source code for\n`integer conversions <https://github.com/python/cpython/blob/e349bf23584eef20e0d1e1b2989d9b1430f15507/Objects/longobject.c#L2213>`_\nand for\n`float conversions <https://github.com/python/cpython/blob/e349bf23584eef20e0d1e1b2989d9b1430f15507/Python/dtoa.c#L1434>`_),\nbut this extra effort is only needed for very large\nintegers or for floats with many digits or large exponents. For integers, if the\nresult could fit into a C ``long`` then a naive algorithm of < 10 lines of C code\nis sufficient. For floats, if the number does not require high precision or does not\nhave a large exponent (such as \"-123.45e6\") then a short naive algorithm is also\npossible.\n\nThese naive algorithms are quite fast, but the performance improvement comes at the\nexpense of being unsafe (no protection against overflow or round-off errors).\n``fastnumbers`` uses a heuristic to determine if the input can be safely converted\nwith the much faster naive algorithm. These heuristics are extremely conservative -\nif there is *any* chance that the naive result would not give *exactly* the same\nresult as the built-in functions then it will fall back on CPython's conversion\nfunction. For this reason, ``fastnumbers`` is aways *at least as fast* as CPython's\nbuilt-in ``float`` and ``int`` functions, and oftentimes is significantly faster\nbecause most real-world numbers pass the heuristic.\n\nInstallation\n------------\n\nUse ``pip``!\n\n.. code-block::\n\n    $ pip install fastnumbers\n\nHow to Run Tests\n----------------\n\nPlease note that ``fastnumbers`` is NOT set-up to support ``python setup.py test``.\n\nThe recommended way to run tests is with `tox <https://tox.readthedocs.io/en/latest/>`_.\nSuppose you want to run tests for Python 3.6 - you can run tests by simply executing the\nfollowing:\n\n.. code-block:: sh\n\n    $ tox -e py36\n\n``tox`` will create virtual a virtual environment for your tests and install all the\nneeded testing requirements for you.\n\nIf you want to run testing on all of Python 2.7, 3.4, 3.5, 3.6, and 3.7 you can simply\nexecute\n\n.. code-block:: sh\n\n    $ tox\n\nIf you do not wish to use ``tox``, you can install the testing dependencies with the\n``dev-requirements.txt`` file and then run the tests manually using\n`pytest <https://docs.pytest.org/en/latest/>`_.\n\n.. code-block:: sh\n\n    $ pip install -r dev/requirements.txt\n    $ pytest\n\nAuthor\n------\n\nSeth M. Morton\n\nHistory\n-------\n\nPlease visit the `changelog <http://fastnumbers.readthedocs.io/en/master/changelog.html>`_.",
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