victor-cb/cookiecutter-simple-datascience

Cookiecutter template

Cookiecutter Modern Data Science

Cookiecutter template for starting a Data Science project. To install it:

1. pip install cookiecutter
2. cookiecutter https://github.com/Victor-cb/cookiecutter-simple-datascience.git

Directory structure

This is how your new project will look like:

├── .gitignore                <- GitHub's excellent Python .gitignore customized for this project
├── LICENSE                   <- Your project's license.
├── Pipfile                   <- The Pipfile for reproducing the analysis environment
├── README.md                 <- The top-level README for developers using this project.
│
├── data
│   ├── 0_raw                 <- The original, immutable data dump.
│   ├── 1_external            <- Data from third party sources.
│   ├── 2_interim             <- Intermediate data that has been transformed.
│   └── 3_final               <- The final, canonical data sets for modeling.
│
├── docs                      <- GitHub pages website
│   ├── data_dictionaries     <- Data dictionaries
│   └── references            <- Papers, manuals, and all other explanatory materials.
│
├── notebooks                 <- Jupyter notebooks. Naming convention is a number (for ordering),
│                                the creator's initials, and a short `_` delimited description, e.g.
│                                `01_cp_exploratory_data_analysis.ipynb`.
│
├── output
│   ├── features              <- Fitted and serialized features
│   ├── models                <- Trained and serialized models, model predictions, or model summaries
|   |   └── mlruns            <- MLflow artifacts 
│   └── reports               <- Generated analyses as HTML, PDF, LaTeX, etc.
│       └── figures           <- Generated graphics and figures to be used in reporting
│
|
│
└── serve                     <- HTTP API for serving predictions
    ├── Dockerfile            <- Dockerfile for HTTP API
    ├── Pipfile               <- The Pipfile for reproducing the serving environment
    ├── app.py                <- The entry point of the HTTP API
    └── tests
        ├── fixtures          <- Where to put example inputs and outputs
        │   ├── input.json    <- Test input data
        │   └── output.json   <- Test output data
        └── test_app.py       <- Integration tests for the HTTP API