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BigData Republic Analytics (python)

Our analytics library to quickly get our data scientists up to speed, on the python platform

User documentation can be found at https://bigdatarepublic.github.io/bdr-analytics-py/

Installation

Installation is done through the pip command line utility.

pip install bdranalytics

Using the Spark notebooks

Some notebooks in the notebooks folder use spark. Check the spark documentation for running jupyter with a spark contet.

But in short, for windows

set PYSPARK_DRIVER_PYTHON_OPTS=notebook
set PYSPARK_DRIVER_PYTHON=jupyter
[spark_install_dir]\bin\pyspark

And for nix

export PYSPARK_DRIVER_PYTHON_OPTS=notebook
export PYSPARK_DRIVER_PYTHON=jupyter
[spark_install_dir]/bin/pyspark

Contributing

To contribute, please fork or branch from master and submit a pull-request. Guidelines for an acceptable pull-request:

  • PEP8 compliant code
  • At least one line of documentation per class, function and method.
  • Tests covering edge cases of your code.

Development environment

To create the development environment with conda, run:

conda env create -f environment-dev.yml

source activate bdranalytics-dev

Running the test

To run all tests:

source activate bdranalytics-dev python setup.py test

Creating a package dist

To create a dist from a local checkout (when developing on this module):

source activate bdranalytics-dev python setup.py sdist

Running the installation script

This uses the setup.py script directly, useful for testing how the dist will be installed without creating the dist.

To just install the package and main dependencies from a local checkout (when going to use this module):

python setup.py install

Creating the sphinx documentation

To update html files:

source activate bdranalytics-dev
cd doc
make clean && make source && make html

About

Common data science and data engineering utilities to help us perform analytics. Our toolbox for data scientists, licensed under Apache-2.0

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