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Description:

jupyter utils 1.2.6

A set of Python utility methods to ease usage of Jupyter notebook

Free software: MIT
Source: https://github.com/Stibbons/jupyter_utils

Installation
Install jupyter_utils in Anaconda:
$ source activate my_conda_env
$ pip install jupyter_utils
Note: only dependencies described in requirements.txt will be installed when using pip install.
The development dependencies (pylint,…) and not installed on deployment.

Usage
>From now, on every Jupyter notebook that use this conda environment, you can install any missing
anaconda package directly from the cell.

Install Anaconda package
An anaconda package can be installed directly from the notebook using ! conda install …, but
you need to specify the name of the kernel. To simply this, Jupyter Utils provides:
from jupyter_utils import conda
conda.install("numpy")

Grid Search CV on Apache Spark 1.6
Easily distribute Scikit-learn Cross Validation on a Spark Cluster. Only for Spark 1.6.x. For Spark
2, use Sparkit-Learn or
Spark-SKLearn.
from jupyter_utils.spark import SparkGridSearchCV
SparkGridSearchCV(sc, model, params)

Contributing
Create a virtualenv:
$ virtualenv venv
$ source venv/bin/activate
$ pip install --upgrade pip # Force upgrade to latest version of pip
Setup for production:
$ pip install -r requirements.txt .
Setup for development and unit tests:
$ pip install --upgrade -r requirements.txt -r requirements-dev.txt -e .
$ python setup.py develop
Execute unit tests:
$ python setup.py test
Code Style:
$ python setup.py flake8
$ yapf -r -i jupyter_utils
Build:
$ # Source package
$ python setup.py sdist
$ # Binary package:
$ python setup.py bdist bdist_wheel