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    "info": {
        "author": "Man AHL Technology",
        "author_email": "ManAHLTech@ahl.com",
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        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Framework :: Flask",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2.7",
            "Topic :: Scientific/Engineering",
            "Topic :: Scientific/Engineering :: Visualization",
            "Topic :: Utilities"
        ],
        "description": "## Pynorama\nPynorama is a tool for visualizing intricate datasets for which a simple table format is not suitable. It was created with Natural Language Processing applications in mind.\n\n[TODO: Screenshot]\n\nPynorama lets you define *views* in **python** that are rendered as interactive web applications, letting you browse, analyse and understand your data.\n\nPynorama is **open and extensible.**\nPynorama has a clean and simple architecture.\nIt makes little assumptions about your data source or data format.\nRead in the [documentation](https://pynorama.readthedocs.io) about developing extensions.\n\n## Quickstart\n\n### Install Pynorama\n\nFor a minimal install run:  \n```\npip install pynorama\n```\n\n### Using Pynorama\n\nTo create a *view*:\n * define a table describing your data records, currently supported sources are pandas dataframe and mongo queries.\n * define different stages of your data pipeline.\n * return a particular records for a given stage.\n * configure the UI\n\nIn python this would look similar to this:\n```python\nfrom pynorama import View\nfrom pynorama.table import PandasTable\n\nclass ExampleView(View):\n    def __init__(self, name, description=''):\n        super(ExampleView, self).__init__(name, description)\n        setup_data()\n\n    def get_pipeline(self):\n        return {\n            'raw_stage': {'viewer': 'raw'},\n            'tokenized': {'viewer': 'json', 'parents': ['raw_stage']}\n        }\n\n    def get_record(self, key, stage):\n        if stage == 'raw_stage':\n            return get_html(key)\n        else:\n            return get_processed_data(key)\n\n    def get_table(self):\n        return PandasTable(get_dataframe())\n```\n\nNext, register the view with pynorama:\n```python\nfrom pynorama import register_view\n\nregister_view(ExampleView('example'))\n```\n\nFinally, let Pynorama set up a *flask* server for you and start it:\n```python\nfrom pynorama import make_server\n\napp = make_server()\napp.run(host='localhost', port='5000')\n```\n\nNow just run your python script! The view should be accessible at *http://localhost:5000/view/example*.\n\nFor more information check the [examples](examples) and the [documentation](https://pynorama.readthedocs.io)!\n\n## Acknowledgements\n\nPynorama was developed at [Man AHL](http://www.ahl.com/).\n\nOriginal concept and implementation: [Alexander Wettig](https://github.com/CodeCreator)\n\nContributors from AHL Tech team:\n\n * [Slavi Marinov](https://github.com/slavi)\n * [Nikolai Matiushev](https://github.com/egao1980)\n\nContributions welcome!\n\n## License\n\nPynorama is licensed under the GNU LGPL v2.1.  A copy of which is included in [LICENSE](LICENSE)\n\nChangelog\n\n### 1.0.0\n\n  * Initial public release\n\n\n",
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        "keywords": "ahl,visualization,NLP,data discovery",
        "license": "LGPL-2.1",
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        "name": "pynorama",
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