FAIR4HEP / cookiecutter4fair

A logical, standardized, but flexible project structure for sharing AI and data science work following FAIR principles.

Cookiecutter4FAIR

A logical, standardized, but flexible project structure for sharing AI and data science work following FAIR principles.

Project homepage

Requirements to use the cookiecutter template:

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• Python 3.7+
• Cookiecutter Python package >= 2.1.1: This can be installed with pip or conda:

$ pip install cookiecutter

or

$ conda config --add channels conda-forge
$ conda install cookiecutter

To start a new project, run:

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$ cookiecutter https://github.com/FAIR4HEP/cookiecutter4fair

Demo:

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The resulting directory structure

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The directory structure of your new project looks like this:

├── LICENSE            <- License for reusing code
├── Makefile           <- Makefile with commands like `make data` or `make train`
├── CITATION.cff       <- Standardized citation metadata
├── README.md          <- The top-level README for developers using this project
├── data
│   ├── processed      <- The final, canonical data sets for modeling
│   └── raw            <- The original, FAIR, and immutable data dump
│
├── Dockerfile         <- For building a containerized environment
|
├── docs               <- A default Sphinx project for documentation; see sphinx-doc.org for details
│
├── models             <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
│                         the creator's initials, and a short `-` delimited description, e.g.
│                         `1.0-jqp-initial-data-exploration`.
│
├── references         <- Data dictionaries, manuals, and all other explanatory materials
│
├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures        <- Generated graphics and figures to be used in reporting
│
├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
│                         generated with `pip freeze > requirements.txt`
│
├── setup.py           <- Makes project pip installable (`pip install -e .`) so src can be imported
├── src                <- Source code for use in this project
│   ├── __init__.py    <- Makes `src` a Python module
│   │
│   ├── data           <- Scripts to download or generate data
│   │   └── make_dataset.py
│   │
│   ├── features       <- Scripts to turn raw data into features for modeling
│   │   └── build_features.py
│   │
│   ├── models         <- Scripts to train models and then use trained models to make
│   │   │                 predictions
│   │   ├── predict_model.py
│   │   └── train_model.py
│   │
│   └── visualization  <- Scripts to create exploratory and results oriented visualizations
│       └── visualize.py
│
└── tox.ini            <- Tox file with settings for running `tox`; see tox.readthedocs.io

Contributing

We welcome contributions!

Installing development requirements

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pip install -r requirements.txt

Running the tests

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pytest tests