cookiecutter data science

CookieCutter數據科學

用於進行和共享數據科學工作的邏輯，合理標準化但靈活的項目結構。

CookieCutter數據科學（CCD）是設置包含最佳實踐的數據科學項目模板的工具。要了解有關CCD的理念的更多信息，請訪問項目主頁。

CookieCutter Data Science V2已從V1變化。現在，它需要安裝新的CookieCutter-Data-Science Python軟件包，該軟件包擴展了CookieCutter模板實用程序的功能。使用提供的ccds命令行程序而不是cookiecutter 。

安裝

CookieCutter數據科學V2需要Python 3.8+。由於這是一個交叉項目的實用程序應用程序，因此我們建議將其與PIPX安裝。安裝命令選項：

 # With pipx from PyPI (recommended)
pipx install cookiecutter-data-science

# With pip from PyPI
pip install cookiecutter-data-science

# With conda from conda-forge (coming soon)
# conda install cookiecutter-data-science -c conda-forge 

開始一個新項目

要啟動一個新項目，請運行：

ccds

結果目錄結構

新項目的目錄結構將看起來像這樣（取決於您選擇的設置）：

 ├── LICENSE            <- Open-source license if one is chosen
├── Makefile           <- Makefile with convenience commands like `make data` or `make train`
├── 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.
│
├── docs               <- A default mkdocs project; see www.mkdocs.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`.
│
├── pyproject.toml     <- Project configuration file with package metadata for 
│                         {{ cookiecutter.module_name }} and configuration for tools like black
│
├── 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          <- Configuration file for flake8
│
└── {{ cookiecutter.module_name }}   <- Source code for use in this project.
    │
    ├── __init__.py             <- Makes {{ cookiecutter.module_name }} a Python module
    │
    ├── config.py               <- Store useful variables and configuration
    │
    ├── dataset.py              <- Scripts to download or generate data
    │
    ├── features.py             <- Code to create features for modeling
    │
    ├── modeling                
    │   ├── __init__.py 
    │   ├── predict.py          <- Code to run model inference with trained models          
    │   └── train.py            <- Code to train models
    │
    └── plots.py                <- Code to create visualizations   

使用V1

如果要使用舊的V1項目模板，則需要安裝CookieCutter-Data-Science軟件包或CookieCutter軟件包。然後，將任一個命令行程序與-c v1選項：

ccds https://github.com/drivendataorg/cookiecutter-data-science -c v1
# or equivalently
cookiecutter https://github.com/drivendataorg/cookiecutter-data-science -c v1

貢獻

我們歡迎捐款！有關指南，請參見文檔。

安裝開發要求

pip install -r dev-requirements.txt

運行測試

pytest tests