{
    "info": {
        "author": "Andrew Kelleher",
        "author_email": "keats.kelleher@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "Topic :: Scientific/Engineering :: Information Analysis",
            "Topic :: Scientific/Engineering :: Mathematics"
        ],
        "description": "An implementation of Leskovec et. al's algorithm for inferring latent social networks while exploiting the convexity of the problem",
        "description_content_type": null,
        "docs_url": null,
        "download_url": "UNKNOWN",
        "downloads": {
            "last_day": -1,
            "last_month": -1,
            "last_week": -1
        },
        "home_page": "http://www.github.com/akellehe/pyconnie",
        "keywords": "pyconnie leskovec connie ConNIe convexity latent social network inference",
        "license": "UNKNOWN",
        "maintainer": null,
        "maintainer_email": null,
        "name": "pyconnie",
        "package_url": "https://pypi.org/project/pyconnie/",
        "platform": "UNKNOWN",
        "project_url": "https://pypi.org/project/pyconnie/",
        "project_urls": {
            "Download": "UNKNOWN",
            "Homepage": "http://www.github.com/akellehe/pyconnie"
        },
        "release_url": "https://pypi.org/project/pyconnie/1.0/",
        "requires_dist": null,
        "requires_python": null,
        "summary": "An implementation of the ConNIe",
        "version": "1.0"
    },
    "last_serial": 1185500,
    "releases": {
        "1.0": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "0819c99451b773780c4ad5d440a5eb63",
                    "sha256": "f505431bbbbbabd5538329732d8dc3d436bf44dcd6fe7b95381fc8112eb6a171"
                },
                "downloads": -1,
                "filename": "pyconnie-1.0.tar.gz",
                "has_sig": false,
                "md5_digest": "0819c99451b773780c4ad5d440a5eb63",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 4425,
                "upload_time": "2014-08-10T11:12:44",
                "url": "https://files.pythonhosted.org/packages/bc/0d/6ca68db6ad79715477d181e5f859a655116419fd43056bbc7435fab3ba2d/pyconnie-1.0.tar.gz"
            }
        ]
    },
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "md5": "0819c99451b773780c4ad5d440a5eb63",
                "sha256": "f505431bbbbbabd5538329732d8dc3d436bf44dcd6fe7b95381fc8112eb6a171"
            },
            "downloads": -1,
            "filename": "pyconnie-1.0.tar.gz",
            "has_sig": false,
            "md5_digest": "0819c99451b773780c4ad5d440a5eb63",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 4425,
            "upload_time": "2014-08-10T11:12:44",
            "url": "https://files.pythonhosted.org/packages/bc/0d/6ca68db6ad79715477d181e5f859a655116419fd43056bbc7435fab3ba2d/pyconnie-1.0.tar.gz"
        }
    ]
}