A logical, standardized, but flexible project structure for sharing AI and data science work following FAIR principles.
- Python 3.7+
- Cookiecutter Python package >= 2.1.1: This can be installed with
pip
orconda
:
$ pip install cookiecutter
or
$ conda config --add channels conda-forge
$ conda install cookiecutter
$ cookiecutter https://github.com/FAIR4HEP/cookiecutter4fair
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
We welcome contributions!
pip install -r requirements.txt
pytest tests