{
    "info": {
        "author": "Andrea Zonca",
        "author_email": "code@andreazonca.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 2 - Pre-Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Natural Language :: English",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5"
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        "description": "=====\nnbenv\n=====\n\n\n.. image:: https://img.shields.io/pypi/v/nbenv.svg\n        :target: https://pypi.python.org/pypi/nbenv\n\n.. image:: https://img.shields.io/travis/zonca/nbenv.svg\n        :target: https://travis-ci.org/zonca/nbenv\n\nStore conda environment package list inside Notebook documents\n\nThis package provides a hook for the Jupyter Notebook that saves metadata about the\nconda environment (equivalent of `conda env export`) inside the Notebook `.ipynb` file\neverytime that the Notebook is saved.\nIt also supports packages installed inside the conda environment with `pip`.\n\nOnce such Jupyter Notebook is shared, another user can inspect the environment where\nit ran:\n\n.. code-block:: bash\n\n    $ nbenv --extract my_notebook.ipynb\n\n    name: test_input_env\n    channels:\n    - defaults\n    - conda-forge\n    dependencies:\n    - ca-certificates=2017.08.26=h1d4fec5_0\n    - certifi=2017.7.27.1=py35h19f42a1_0\n    - decorator=4.1.2=py35h3a268aa_0\n    - ipykernel=4.6.1=py35h29d130c_0\n    - ipython=6.1.0=py35h1b71439_1\n    - ipython_genutils=0.2.0=py35hc9e07d0_0\n    - jupyter_client=5.1.0=py35h2bff583_0\n    - pip:\n      - ipython-genutils==0.2.0\n      - jupyter-client==5.1.0\n\nAnd re-create the same environment (includes install of IPython Kernel):\n\n.. code-block:: bash\n\n    $ nbenv my_notebook.ipynb --name reconstructed_env\n    $ source activate reconstructed_env\n    $ jupyter notebook\n\nThe environment metadata will be preserved if the Notebook file is modified by a Jupyter Notebook session\nwith no ``nbenv`` installed.\n\nInstall\n--------\n\nInstall the package with `pip install nbenv`\n\nInstall the Jupyter Notebook hook in your `.jupyter/jupyter_notebook_config.py`:\n\n.. code-block:: python\n\n    try:\n        from nbenv import save_conda_environment\n        c.FileContentsManager.pre_save_hook = save_conda_environment\n    except ImportError:\n        print(\"nbenv package not found: automatic saving of conda environment disabled\")\n\nImplementation details\n----------------------\n\nThe `pre_save_hook` is automatically triggered by the Jupyter Notebook before saving the Notebook\nto disk.\nIt identifies the conda environment being run checking the KernelSpec and then calls ``conda env export``\nand saves the output in ``[\"content\"][\"metadata\"][\"conda_environment\"]`` in the ``.ipynb`` JSON.\n\nThe ``nbenv`` command line tool can then extract that and use ``conda create`` to a new environment.\n\nCredits\n---------\n\nDesign of this package was conceived during discussion at the `Container Analysis Environments Workshop`_\nheld at NCSA in August 2017.\n\n.. _`Container Analysis Environments Workshop`: https://nationaldataservice.atlassian.net/wiki/spaces/NDSC/pages/37284774/Container+Analysis+Environments+Workshop\n\nThis package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.\n\n.. _Cookiecutter: https://github.com/audreyr/cookiecutter\n.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage\n\n\n\n",
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        "keywords": "nbenv",
        "license": "MIT license",
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        "name": "nbenv",
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        "summary": "Store conda environment package list inside Notebook documents",
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