{ "info": { "author": "Gaetan Semet", "author_email": "gaetan@xeberon.net", "bugtrack_url": null, "classifiers": [ "Intended Audience :: Information Technology", "Intended Audience :: System Administrators", "License :: OSI Approved :: MIT License", "Operating System :: POSIX :: Linux", "Programming Language :: Python", "Programming Language :: Python :: 2", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5" ], "description": "======================\nJupyter Notebook Utils\n======================\n\n.. image:: https://travis-ci.org/Stibbons/jupyter_utils.svg?branch=master\n :target: https://travis-ci.org/Stibbons/jupyter_utils\n.. image:: https://badge.fury.io/py/jupyter_utils.svg\n :target: https://pypi.python.org/pypi/jupyter_utils/\n :alt: Pypi package\n\nA set of Python utility methods to ease usage of Jupyter notebook\n\n* Free software: MIT\n* Source: https://github.com/Stibbons/jupyter_utils\n\nInstallation\n============\n\nInstall `jupyter_utils` in Anaconda:\n\n.. code-block:: bash\n\n $ source activate my_conda_env\n $ pip install jupyter_utils\n\nNote: only dependencies described in `requirements.txt` will be installed when using `pip install`.\nThe development dependencies (pylint,...) and **not** installed on deployment.\n\nUsage\n=====\n\n>From now, on every Jupyter notebook that use this conda environment, you can install any missing\nanaconda package directly from the cell.\n\nInstall Anaconda package\n------------------------\n\nAn anaconda package can be installed directly from the notebook using `! conda install ...`, but\nyou need to specify the name of the kernel. To simply this, Jupyter Utils provides:\n\n.. code-block:: python\n\n from jupyter_utils import conda\n conda.install(\"numpy\")\n\nGrid Search CV on Apache Spark 1.6\n----------------------------------\n\nEasily distribute Scikit-learn Cross Validation on a Spark Cluster. Only for Spark 1.6.x. 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