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    "info": {
        "author": "Uwe L. Korn",
        "author_email": "fletcher@uwekorn.com",
        "bugtrack_url": null,
        "classifiers": [
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6"
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        "description": "# fletcher\n\n[![CircleCI](https://circleci.com/gh/xhochy/fletcher/tree/master.svg?style=svg)](https://circleci.com/gh/xhochy/fletcher/tree/master)\n[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)\n[![FOSSA Status](https://app.fossa.io/api/projects/git%2Bgithub.com%2Fxhochy%2Ffletcher.svg?type=shield)](https://app.fossa.io/projects/git%2Bgithub.com%2Fxhochy%2Ffletcher?ref=badge_shield)\n\nA library that provides a generic set of Pandas ExtensionDType/Array\nimplementations backed by Apache Arrow. They support a wider range of types\nthan Pandas natively supports and also bring a different set of constraints and\nbehaviours that are beneficial in many situations.\n\n## Usage\n\nTo use `fletcher` in Pandas DataFrames, all you need to do is to wrap your data\nin a `FletcherArray` object. Your data can be of either `pyarrow.Array`,\n`pyarrow.ChunkedArray` or a type that can be passed to `pyarrow.array(\u2026)`.\n\n\n```\nimport fletcher as fr\nimport pandas as pd\n\ndf = pd.DataFrame({\n    'str': fr.FletcherArray(['a', 'b', 'c'])\n})\n\ndf.info()\n\n# RangeIndex: 3 entries, 0 to 2\n# Data columns (total 1 columns):\n# str    3 non-null fletcher[string]\n# dtypes: fletcher[string](1)\n# memory usage: 100.0 bytes\n```\n\n## Development\n\nWhile you can use `fletcher` in pip-based environments, we strongly recommend\nusing a `conda` based development setup with packages from `conda-forge`.\n\n```\n# Create the conda environment with all necessary dependencies\nconda create -y -q -n fletcher python=3.6 \\\n    black=18.5b0 \\\n    codecov \\\n    flake8 \\\n    numba \\\n    pandas \\\n    pip \\\n    pyarrow \\\n    pytest \\\n    pytest-cov \\\n    pytest-flake8 \\\n    six \\\n    -c conda-forge\n\n# Activate the newly created environment\nsource activate fletcher\n\n# Install fletcher into the current environment\npip install -e .\n\n# Run the unit tests (you should do this several times during development)\npy.test\n```\n\nCode formatting is done using black. This should keep everything in a\nconsistent styling and the formatting can be automatically adjusted using\n`black .`. Note that we have pinned the version of `black` to ensure that\nthe formatting is reproducible.\n\n\n## License\n[![FOSSA Status](https://app.fossa.io/api/projects/git%2Bgithub.com%2Fxhochy%2Ffletcher.svg?type=large)](https://app.fossa.io/projects/git%2Bgithub.com%2Fxhochy%2Ffletcher?ref=badge_large)\n\n",
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        "keywords": "",
        "license": "MIT",
        "maintainer": "",
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        "name": "fletcher",
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