{
    "info": {
        "author": "Paco Nathan",
        "author_email": "ceteri@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Framework :: Jupyter",
            "Intended Audience :: Developers",
            "Intended Audience :: Information Technology",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: Apache Software License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3",
            "Topic :: Scientific/Engineering :: Artificial Intelligence",
            "Topic :: Scientific/Engineering :: Human Machine Interfaces",
            "Topic :: Scientific/Engineering :: Information Analysis"
        ],
        "description": "Active Learning with Jupyter Notebooks\n======================================\n\nThis is a Python 3 library to read/write cells programmatically in\n`Jupyter notebooks <https://jupyter.org/>`_ which anticipates upcoming\n`collaborative <https://groups.google.com/forum/#!topic/jupyter/r7QSObF5YSg>`_\nfeatures in Jupyter.\n\nWe use this at `O'Reilly Media <https://www.oreilly.com/>`_ for\nnotebooks used to manage machine learning pipelines.\nThat is to say, *machines and people collaborate on documents*, \nimplementing a \"human-in-the-loop\" design pattern:\n\n-  people adjust hyperparameters for the ML pipelines\n-  machines write structured \"logs\" during ML modeling/evaluation\n-  people run ``jupyter notebook`` via SSH tunnel for remote access\n\nFor more info about use cases for this library and *active learning* \nin general, see the `JupyterCon 2017 <https://jupytercon.com/>`_ talk\n`Humans in the loop <https://conferences.oreilly.com/jupyter/jup-ny/public/schedule/detail/60058>`_\n\n\nExample Usage\n-------------\n\nThe following script generates a Jupyter notebook in the ``test.ipynb``\nfile, then runs it:\n\n::\n\n    python test.py\n    jupyter notebook\n\nThen launch the ``test.ipynb`` notebook and from the ``Cells`` menu\nselect ``Run All`` to view results.\n\nNB: whenever you use the ``put_df()`` function to store data as a \n`Pandas dataframe <https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html>`_\nbe sure to include ``import pandas as pd`` at some earlier point in\nthe notebook.\n\n\nDependencies and Installation\n-----------------------------\n\nThis code has dependencies on:\n\n-  `nbformat <https://github.com/jupyter/nbformat>`_\n-  `pandas <https://pandas.pydata.org/>`_\n\nTo install from `PyPi <https://pypi.python.org/pypi/nbtransom>`_:\n\n::\n\n    pip install nbtransom\n\n\nTo install from this Git repo:\n\n::\n\n    git clone https://github.com/ceteri/nbtransom.git\n    cd nbtransom\n    pip install -r requirements.txt\n\n\nKudos\n-----\n\n`@htmartin <https://github.com/htmartin>`_\n`@esztiorm <https://github.com/esztiorm>`_\n`@fperez <https://github.com/fperez>`_\n`@odewahn <https://github.com/odewahn>`_\n\n\n",
        "description_content_type": null,
        "docs_url": null,
        "download_url": "",
        "downloads": {
            "last_day": -1,
            "last_month": -1,
            "last_week": -1
        },
        "home_page": "http://github.com/ceteri/nbtransom",
        "keywords": "human-in-the-loop,active learning,collaborative documents,jupyter notebook,pipelines,machine learning",
        "license": "Apache License 2.0",
        "maintainer": "",
        "maintainer_email": "",
        "name": "nbtransom",
        "package_url": "https://pypi.org/project/nbtransom/",
        "platform": "",
        "project_url": "https://pypi.org/project/nbtransom/",
        "project_urls": {
            "Homepage": "http://github.com/ceteri/nbtransom"
        },
        "release_url": "https://pypi.org/project/nbtransom/1.0.1/",
        "requires_dist": [
            "nbformat",
            "pandas"
        ],
        "requires_python": "",
        "summary": "Machines and people collaborating together through Jupyter notebooks.",
        "version": "1.0.1"
    },
    "last_serial": 2977809,
    "releases": {
        "1.0.1": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "317d0dc4e8ae35322f3d26c7baf84ebe",
                    "sha256": "6db18297e18064fc8c4e79c42d8433dd409a81a84323e21d15a346519c739964"
                },
                "downloads": -1,
                "filename": "nbtransom-1.0.1-py3-none-any.whl",
                "has_sig": false,
                "md5_digest": "317d0dc4e8ae35322f3d26c7baf84ebe",
                "packagetype": "bdist_wheel",
                "python_version": "py3",
                "requires_python": null,
                "size": 6193,
                "upload_time": "2017-06-25T18:03:22",
                "url": "https://files.pythonhosted.org/packages/b2/18/79bae38ff8aa2c5ac8cf96bdccad0eb372678870e279237df6d3bb6b2daa/nbtransom-1.0.1-py3-none-any.whl"
            },
            {
                "comment_text": "",
                "digests": {
                    "md5": "decc2b74c01f517fb558bca975b4268a",
                    "sha256": "271e4a1f071d43ebc16d3d4d4ed242ef27506bc7d620b119ce9cefba9570c51b"
                },
                "downloads": -1,
                "filename": "nbtransom-1.0.1.tar.gz",
                "has_sig": false,
                "md5_digest": "decc2b74c01f517fb558bca975b4268a",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 4197,
                "upload_time": "2017-06-25T18:03:23",
                "url": "https://files.pythonhosted.org/packages/73/af/a1bd16162caf5d0c384ae39b9b65bd64a3a8da3e9efbab7bb983a938d38e/nbtransom-1.0.1.tar.gz"
            }
        ]
    },
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "md5": "317d0dc4e8ae35322f3d26c7baf84ebe",
                "sha256": "6db18297e18064fc8c4e79c42d8433dd409a81a84323e21d15a346519c739964"
            },
            "downloads": -1,
            "filename": "nbtransom-1.0.1-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "317d0dc4e8ae35322f3d26c7baf84ebe",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": null,
            "size": 6193,
            "upload_time": "2017-06-25T18:03:22",
            "url": "https://files.pythonhosted.org/packages/b2/18/79bae38ff8aa2c5ac8cf96bdccad0eb372678870e279237df6d3bb6b2daa/nbtransom-1.0.1-py3-none-any.whl"
        },
        {
            "comment_text": "",
            "digests": {
                "md5": "decc2b74c01f517fb558bca975b4268a",
                "sha256": "271e4a1f071d43ebc16d3d4d4ed242ef27506bc7d620b119ce9cefba9570c51b"
            },
            "downloads": -1,
            "filename": "nbtransom-1.0.1.tar.gz",
            "has_sig": false,
            "md5_digest": "decc2b74c01f517fb558bca975b4268a",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 4197,
            "upload_time": "2017-06-25T18:03:23",
            "url": "https://files.pythonhosted.org/packages/73/af/a1bd16162caf5d0c384ae39b9b65bd64a3a8da3e9efbab7bb983a938d38e/nbtransom-1.0.1.tar.gz"
        }
    ]
}