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Artefact's Boilerplate for DataScience Python projects

This repository is a boilerplate repository designed to be used when starting a new project to help kickstart things easily.

To create a new repository based on this one please use the "create from a template" feature (see Github's documentation).

There will be more than you need for your project so feel free to drop what you don't need after you initialized your repo with this one.

Organisation of the repo

Folders

The folder name should be self sufficient, however some extra details:
- bin: This is the folder where you store your executable, that could be main python scripts, or bash ones.
- lib: this is where you store the main libraries used within your project. 
- data: Separated in 3 folder to start: Raw data, intermediate, and processed.
- doc: Sphinx template to generate code documentation
- references: all the written documentation (functional, features) that is not sphinx generated 

Requirements

You should always have requirements to your project to ensure reproductibility.

Requirements are often a pain, between the one that you really use, and all the dependencies. This repo advise you to use Pip-tools.

To do so, put your requirements in the requirements.in, then run

  pip-compile requirements.in

This will generate automatically the requirements.txt with all the required dependencies.

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