Data Science Python Project Setup

A minimal setup to let you crunch numbers like a pro.

Read the full article on Medium.

If you like to use the repository as a blueprint for your own projects just follow the steps below.

Replace data-science-project with you project/environment name in:

.travis.yml
environment.yml
README.md
setup.py

Replace the package information in the setup.py with your own.

Setup

Miniconda

Skip this step if you have Anaconda or Miniconda installed already!

Linux

wget -O ~/miniconda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash ~/miniconda.sh -b -p ~/miniconda
rm ~/miniconda.sh
export PATH="$HOME/miniconda/bin:$PATH"
conda init

Mac OS X

curl -fSL -o ~/miniconda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
bash ~/miniconda.sh -b -p ~/miniconda
rm ~/miniconda.sh
export PATH="$HOME/miniconda/bin:$PATH"
conda init

Project

git clone https://github.com/datasciencejob-de/data-science-python-setup.git

conda env create -f environment.yml
conda activate data-science-project

Usage

conda env update -f environment.yml
conda activate data-science-project
jupyter notebook

Data

See the Data README for more infos.

Tests

flake8 # Run code style checks
pytest # Run the tests