PyScaffold extension tailored for my own simple structured projects. This extension is powered by pyscaffoldext-dsproject
The final directory structure looks like:
Project_Dir
├── AUTHORS.rst <- List of developers and maintainers.
├── CHANGELOG.rst <- Changelog to keep track of new features and fixes.
├── LICENSE.txt <- License as chosen on the command-line.
├── README.md <- The top-level README for developers.
├── data
├── docs <- Directory for Sphinx documentation in rst or md.
├── 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 description,
│ e.g. `1.0-fw-initial-data-exploration`.
├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│ └── figures <- Generated plots and figures for reports.
├── src
│ └── Project_Name <- Actual Python project which can be deploy to production
│ └── environment.yaml <- Actual Python project need conda environment yaml file
│ └── run_python_project_main.py <- Actual Python project some one part main execute script
│ └── supervisor_project_main.ini <- Actual Python project some one part main script supervisor ini template file
│ └── project_name <- Actual Python project some one package template
│ └── __init__.py <- Use for sphinx auto documents
├── tests <- Unit tests which can be run with `py.test`.
Just install this package with pip install pyscaffoldext-beeproject
and note that putup -h shows a new option --beeproject.
Creating a data science project is then as easy as:
putup --beeproject Simple_Project
This project has been set up using PyScaffold 3.2. For details and usage information on PyScaffold see https://pyscaffold.org/.