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        "author": "Michael Seifert",
        "author_email": "michaelseifert04@yahoo.de",
        "bugtrack_url": null,
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            "Development Status :: 3 - Alpha",
            "Operating System :: MacOS :: MacOS X",
            "Operating System :: Microsoft :: Windows",
            "Operating System :: POSIX :: Linux",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: System :: Benchmark",
            "Topic :: Utilities"
        ],
        "description": "simple_benchmark\n================\n\nA simple benchmarking package.\n\nDocumentation\n-------------\n\n.. image:: https://readthedocs.org/projects/simple-benchmark/badge/?version=stable\n   :target: http://simple-benchmark.readthedocs.io/en/stable/?badge=stable\n   :alt: Documentation Status\n\n.. image:: https://readthedocs.org/projects/simple-benchmark/badge/?version=latest\n   :target: http://simple-benchmark.readthedocs.io/en/latest/?badge=latest\n   :alt: Documentation Status\n\n\nDownloads\n---------\n\n.. image:: https://img.shields.io/pypi/v/simple_benchmark.svg\n   :target: https://pypi.python.org/pypi/simple_benchmark\n   :alt: PyPI Project\n\n.. image:: https://img.shields.io/github/release/MSeifert04/simple_benchmark.svg\n   :target: https://github.com/MSeifert04/simple_benchmark/releases\n   :alt: GitHub Project\n\n\nInstallation\n------------\n\nUsing ``pip``:\n\n.. code::\n\n   python -m pip install simple_benchmark\n\nOr installing the most recent version directly from ``git``:\n\n.. code::\n\n   python -m pip install git+https://github.com/MSeifert04/simple_benchmark.git\n\nTo utilize the all features of the library (for example visualization) you need to\ninstall the optional dependencies:\n\n- `NumPy <http://www.numpy.org/>`_\n- `pandas <https://pandas.pydata.org/>`_\n- `matplotlib <https://matplotlib.org/>`_\n\nOr install them automatically using:\n\n.. code::\n\n   python -m pip install simple_benchmark[optional]\n\nGetting started\n---------------\n\nSuppose you want to compare how NumPys sum and Pythons sum perform on lists\nof different sizes::\n\n    >>> from simple_benchmark import benchmark\n    >>> import numpy as np\n    >>> funcs = [sum, np.sum]\n    >>> arguments = {i: [1]*i for i in [1, 10, 100, 1000, 10000, 100000]}\n    >>> argument_name = 'list size'\n    >>> aliases = {sum: 'Python sum', np.sum: 'NumPy sum'}\n    >>> b = benchmark(funcs, arguments, argument_name, function_aliases=aliases)\n\nThe result can be visualized with ``pandas`` (needs to be installed)::\n\n    >>> b\n              Python sum  NumPy sum\n    1       9.640884e-08   0.000004\n    10      1.726930e-07   0.000004\n    100     7.935484e-07   0.000008\n    1000    7.040000e-06   0.000042\n    10000   6.910000e-05   0.000378\n    100000  6.899000e-04   0.003941\n\nOr with ``matplotlib`` (has to be installed too)::\n\n    >>> b.plot()\n\nTo save the plotted benchmark as PNG file::\n\n    >>> import matplotlib.pyplot as plt\n    >>> plt.savefig('sum_example.png')\n\n.. image:: ./docs/source/sum_example.png",
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        "keywords": "performance timing timeit",
        "license": "Apache License Version 2.0",
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        "name": "simple-benchmark",
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