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        "author": "Greg Echelberger",
        "author_email": "greg@keystonetowersystems.com",
        "bugtrack_url": null,
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            "Intended Audience :: Developers",
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            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3 :: Only",
            "Topic :: Scientific/Engineering",
            "Topic :: Software Development :: Libraries"
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        "description": "# fuzzyfloat\n\n[![PyPI version](https://badge.fury.io/py/fuzzyfloat.svg)](https://badge.fury.io/py/fuzzyfloat)\n[![Build Status](https://travis-ci.com/keystonetowersystems/fuzzyfloat.svg?branch=master)](https://travis-ci.com/keystonetowersystems/fuzzyfloat)\n\nA utility library that provides transparent floating point types with tolerances for equality comparison.\n\n# Getting Started\n\n```python\n>>>from fuzzyfloat import rel_fp\n>>>value = rel_fp(100)\n>>>value == 100\nTrue\n>>>value == 99.99999999\nTrue\n>>>value == 100.00000001\nTrue\n>>>value = 1000\n>>>value == 1000.0000001\nTrue\n>>>value = 10000\n>>>value == 10000.000001\nTrue\n>>>value = 100000\n>>>value == 100000.00001\nTrue\n```\n```python\n>>>from fuzzyfloat import abs_fp\n>>>value = abs_fp(100)\n>>>value = 100000\n>>>value == 100000.00001\nFalse\n>>>value == 100000.00000001\nTrue\n```\n\n# Setting different tolerances\n\n```python\nfrom fuzzyfloat import FuzzyFloatMeta\n\nclass my_fp(metaclass=FuzzyFloatMeta, rel_tol=1e-05, atol=0.01):\n    pass\n```\n\n# Using a different underlying type\n\n```python\nimport numpy as np\nfrom fuzzyfloat import FuzzyFloatMeta\n\nclass np_fp(metaclass=FuzzyFloatMeta, ftype=np.float128):\n    pass\n\nclass c_fp(metaclass=FuzzyFloatMeta, ftype=complex):\n    pass\n```\n\n# Limitations\n\nAny operations provided by the operators module will propogate the class type (and therefore the tolerances).\nHowever, there are many other functions, especially those that touch c extensions, where the type information will\nbe lost, such as ```math.sqrt()```.\n\n\n",
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