Simplified version of Cookiecutter Data Science that includes Docker Jupyter Image.
- Python 3.7
- Docker
- 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
cookiecutter https://github.com/kikejimenez/cookiecutter-docker-data-science
The directory structure of your new project looks like this:
├── MIT LICENSE
├── README.md <- The top-level README for developers using this project.
├── data
│ ├── interim <- Intermediate data that has been transformed.
│ ├── processed <- The final, canonical data sets for modeling.
│ └── raw <- The original, immutable data dump.
│
│
├── 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.
├── presentation <- Presentation slides
│
├── requirements.txt <- The requirements file for reproducing the analysis environment,
│
└── src <- Source code for use in this project.
├── __init__.py <- Makes src a Python module
- Enter command 'docker-compose up'