Cookiecutter Data Science

A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.

Project homepage

Requirements to use the cookiecutter template:

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• 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

To start a new project, run:

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cookiecutter https://github.com/heisguyy/cookiecutter-data-science

New version of Cookiecutter Data Science

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Cookiecutter data science is moving to v2 soon, which will entail using the command ccds ... rather than cookiecutter .... The cookiecutter command will continue to work, and this version of the template will still be available. To use the legacy template, you will need to explicitly use -c v1 to select it. Please update any scripts/automation you have to append the -c v1 option (as above), which is available now.

The resulting directory structure

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The directory structure of your new project looks like this:

 ├── .github/workflows       <- CI/CD and automation files.
 │   ├── deploy.yml          <- Github action for continuous deployment (CD). 
 │   └── integration.yml     <- Github action for continuous integration tests (CI). 
 │── .vscode/settings.json   <- Visual studio code IDE config files.
 ├── artifacts               <- Trained and serialized models, vectorizers, encoders, tokenizers, etc.
 ├── data                    <- Data used for the project
 ├── experiments             <- 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`.
 ├── infrastructure          <- IaC files.
 │   ├── modules/            <- Modules of various components of the deployment infrastructure.
 │   ├── vars/               <- Defined variables for stages of the development lifecycle.
 │   ├── main.tf             <- Terraform declaration of backend and infrastructure. 
 │   └── variables.tf        <- Terraform initialization of variables for the infrastructure.
 ├── src                     <- Source code for use in this project.
 │   ├── __init__.py         <- Makes src a Python module
 │   ├── main.py             <- Scripts for API.
 │   └── Dockerfile          <- Blueprint for building docker container.
 ├── tests                   <- Tests codes to ensure quality of codes. 
 │   ├── integration/        <- Codes to ensure changes haven't broken any essential feature.
 │   └── unit/               <- Codes to ensure that each function/unit is performing as expected.
 ├── .env                    <- Contains environmental variables like app secrets. This file should not
 │                              be committed or pushed.
 ├── .gitignore              <- List of files to avoid committing/pushing to the local and remote git repo.
 ├── .pre-commit-config.yaml <- Configurations of checks to run before a commit is accepted.
 ├── LICENSE                 <- Permissions for the public on the use/distribution of the repo/project.
 ├── Makefile                <- Makefile with commands like `make requirements`.
 ├── README.md               <- The top-level README for developers using this project.
 ├── pyproject.toml          <- Makefile with commands like `make data` or `make train`
 └── requirements.txt        <- List of libraries/packages and their versions required for the project.

Contributing

We welcome contributions! See the docs for guidelines.

Installing development requirements

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pip install -r requirements.txt

Running the tests

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py.test tests