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        "author": "Vanessa Sochat",
        "author_email": "vsochat@stanford.edu",
        "bugtrack_url": null,
        "classifiers": [
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            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)",
            "Operating System :: Unix",
            "Programming Language :: C",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3",
            "Topic :: Scientific/Engineering",
            "Topic :: Software Development"
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        "description": "# schemaorg Python\n\nThis module will serve functions for researchers and users to apply schema.org\ndefinitions to their datasets, software, and other worldly things. For \ndevelopment functions with Python along with the web interface that\nserves the published specifications, please see [https://www.github.com/schemaorg/schemaorg](https://www.github.com/schemaorg/schemaorg).\n\n## What is this not?\n\nThis library is not intended to provide advanced functions around querying the ontology,\nbut rather accessing the definitions and tagging content with them.\n\n## What is this for?\n\nPlease reference the [development](https://openschemas.github.io/schemaorg/) documentation\nto read about the intended use cases that we are working on.\n\n## Organization\n\nGenerally, we are extracting metadata from datasets and software, and then shoving\nthat metadata into a specification from schema.org. The final thing that we produce\nis likely to be some form of json (e.g., json-ld) that can be embedded in a web \npage or similar, intended to power search.  Since the specific needs of a particular\nwebby place may vary, along with a data type we are extracting, the module provides\n\"templates\" in the [templates](schemaorg/templates) directory. Specifically:\n\n - The subfolders represent different use cases. For example, [templates/google](schemaorg/templates/google) has a simple html template, and a requirements file (called a recipe) to produce a Dataset and SoftwareSourceCode.\n - Each subfolder, in an optional `__init__.py` file, also contains helper functions toward this goal. For example, the same google subfolder has such a file with a `make_person` function that users can quickly use to generate a person object.\n - For each corresponding subfolder, there is generally an example in the [examples](examples) folder that also helps to see how it works.\n",
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