{
    "info": {
        "author": "Daniel Richard Stromberg",
        "author_email": "strombrg@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 3"
        ],
        "description": "A pure python bloom filter (low storage requirement, probabilistic\nset datastructure) is provided.  It is known to work on CPython 2.x,\nCPython 3.x, Pypy and Jython.\n\nIncludes mmap, in-memory and disk-seek backends.\n\nThe user specifies the desired maximum number of elements and the\ndesired maximum false positive probability, and the module\ncalculates the rest.",
        "description_content_type": null,
        "docs_url": null,
        "download_url": "UNKNOWN",
        "downloads": {
            "last_day": -1,
            "last_month": -1,
            "last_week": -1
        },
        "home_page": "http://stromberg.dnsalias.org/~strombrg/drs-bloom-filter/",
        "keywords": "probabilistic set datastructure",
        "license": "MIT",
        "maintainer": null,
        "maintainer_email": null,
        "name": "drs-bloom-filter",
        "package_url": "https://pypi.org/project/drs-bloom-filter/",
        "platform": "Cross platform",
        "project_url": "https://pypi.org/project/drs-bloom-filter/",
        "project_urls": {
            "Download": "UNKNOWN",
            "Homepage": "http://stromberg.dnsalias.org/~strombrg/drs-bloom-filter/"
        },
        "release_url": "https://pypi.org/project/drs-bloom-filter/1.01/",
        "requires_dist": null,
        "requires_python": null,
        "summary": "Pure Python Bloom Filter module",
        "version": "1.01"
    },
    "last_serial": 505273,
    "releases": {
        "1.0": [],
        "1.01": []
    },
    "urls": []
}