A simplified project structure for biology experiments based off the cookiecutter data science template
- Python 2.7 or 3.5+
- Cookiecutter Python package >= 1.4.0: This can be installed with pip by or conda depending on how you manage your Python packages:
$ pip install cookiecutter
or
$ conda config --add channels conda-forge
$ conda install cookiecutter
cookiecutter -c v1 https://github.com/SpikyClip/cookiecutter-biology-experiment
The directory structure of your new project looks like this:
├── LICENSE
├── README.md <- The top-level README for developers using this project.
├── data
│ ├── external <- Data from third party sources.
│ ├── interim <- Intermediate data that has been transformed.
│ ├── processed <- The final, canonical data sets for modeling.
│ └── raw <- The original, immutable data dump.
│
├── dist <- Folder for repo python package distribution archives
│
├── 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.cfg <- Makes project pip installable (pip install -e .) so src can be imported
├── pyproject.toml <- Tells build tools what is required to build project
│
├── src <- Source code for use in this project.
│ ├── __init__.py <- Makes src a Python module
│ │
│ ├── data <- Scripts to download, generate or clean data
│ │
│ ├── models <- Scripts to train models and then use trained models to make
│ │ predictions
│ │
│ └── visualization <- Scripts to create exploratory and results oriented visualizations
│
└── tests <- folder for unit testing