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    "info": {
        "author": "Tom White",
        "author_email": "tom.e.white@gmail.com",
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        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "Intended Audience :: Information Technology",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: Apache Software License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.6"
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        "description": "# Zappy - distributed processing with NumPy and Zarr\n\nZappy is for distributed processing of chunked NumPy arrays on engines like [Pywren], Apache Spark, and Apache Beam.\n\n[![Build Status](https://travis-ci.org/lasersonlab/zappy.svg?branch=master)](https://travis-ci.org/lasersonlab/zappy)\n[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)\n[![Coverage Status](https://coveralls.io/repos/github/lasersonlab/zappy/badge.svg)](https://coveralls.io/github/lasersonlab/zappy)\n[![PyPI version shields.io](https://img.shields.io/pypi/v/zappy.svg)](https://pypi.python.org/pypi/zappy/)\n\nThe `zappy.base` module defines a `ZappyArray` class that exposes the same interface as `numpy.ndarray`, and which\nis backed by distributed storage and processing. The array is broken into chunks, and is typically loaded from [Zarr],\nand each chunk is processed independently.\n\nThere are a few engines provided:\n* **direct** - for eager in-memory processing\n* **spark** - for processing using Spark\n* **beam** - for processing using Beam or Google Dataflow\n* **executor** - for processing using Python's [concurrent.futures.Executor], of which [Pywren] is a notable implementation\n\nBeam currently only runs on Python 2.\n\nFull coverage of the `numpy.ndarray` interface is _not_ provided. Only enough has been implemented to support running\nparts of [Scanpy], as demonstrated in the [Single Cell Experiments] repo.\n\n## Installation\n\n```\npip install zappy\n```\n\nAlternatively, zappy can be installed using [Conda](https://conda.io/docs/) (most easily obtained via the [Miniconda Python distribution](https://conda.io/miniconda.html)):\n\n```\nconda install -c conda-forge zappy\n```\n\n## Demo\n\nTake a look at the rendered [demo Jupyter notebook](demo.ipynb), or try it out yourself as follows.\n\nCreate and activate a Python 3 virtualenv, and install the requirements:\n\n```\npython3 -m venv venv\n. venv/bin/activate\npip install -r requirements.txt\npip install -e .\npip install s3fs jupyter\n```\n\nThen run the notebook with:\n\n```\njupyter notebook demo.ipynb\n```\n\n## Testing\n\nThere is a test suite for all the engines, covering both Python 2 and 3.\n\nRun everything in one go with tox:\n\n```\npip install tox\ntox\n```\n\nFormatting:\n\n```\npip install black\nblack zappy tests/* *.py\n```\n\nCoverage:\n\n```\npip install pytest-cov\npytest --cov-report html --cov=zappy\nopen htmlcov/index.html\n```\n\n## Publishing\n\n```\npip install twine\npython setup.py sdist\ntwine upload -r pypi dist/zappy-0.1.0.tar.gz\n```\n\nIf successful, the package will be available on [PyPI].\n\n[Scanpy]: https://scanpy.readthedocs.io/\n[Single Cell Experiments]: https://github.com/lasersonlab/single-cell-experiments\n[concurrent.futures.Executor]: https://docs.python.org/3/library/concurrent.futures.html#concurrent.futures.Executor\n[PyPI]: https://pypi.org/project/zappy/\n[Pywren]: http://pywren.io/\n[Zarr]: https://zarr.readthedocs.io/",
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