{
    "info": {
        "author": "Hsiaoming Yang",
        "author_email": "me@lepture.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Environment :: Web Environment",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: BSD License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Topic :: Internet :: WWW/HTTP :: Dynamic Content",
            "Topic :: Software Development :: Libraries :: Python Modules"
        ],
        "description": "hentry\n======\n\nParse a well designed webpage with microformats markup. If you have no\nknowledge about microformats, take a look at\nhttp://microformats.org/wiki/hentry.\n\nA hentry schema looks like::\n\n    <article class=\"hentry\">\n        <h1 class=\"entry-title\">Article title</h1>\n        <time class=\"updated\" datetime=\"2014-11-06T20:00:00Z\" pubdate>2014-11-06</time>\n        <div class=\"entry-content\">\n            <p>Here is the content</p>\n        </div>\n        <div class=\"entry-tags\">\n            <a href=\"#tag1\" rel=\"tag\">tag1</a>\n            <a href=\"#tag2\" rel=\"tag\">tag2</a>\n        </div>\n        <div class=\"vcard author\">\n            <span class=\"fn\">Author Name</span>\n        </div>\n    </article>\n\nWith this library **hentry.py**, you can parse the html into meta data::\n\n    hentry.parse_html(text, format='html')\n\nInstallation\n------------\n\nInstall hentry with pip::\n\n    $ pip install hentry\n\nBasic Usage\n-----------\n\nParse a webpage with a url::\n\n    hentry.parse_url(url)\n\nParse a webpage with html content::\n\n    hentry.parse_html(content)\n\nThe result is a dict which contains:\n\n1. title\n2. content\n3. author\n4. pubdate\n5. tags\n6. categories\n7. image",
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        "license": "BSD",
        "maintainer": null,
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        "name": "hentry",
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        "summary": "Parse hentry from microformats.",
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