pyscaffoldext-beeproject

PyScaffold extension tailored for my own simple structured projects. This extension is powered by pyscaffoldext-dsproject

The final directory structure looks like:

├── 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
│   ├── 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                    <- Directory for Sphinx documentation in rst or md.
├── environment.yaml        <- The conda environment file for reproducibility.
├── 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`.
├── references              <- Data dictionaries, manuals, and all other materials.
├── reports                 <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures             <- Generated plots and figures for reports.
├── setup.cfg               <- Declarative configuration of your project.
├── setup.py                <- Use `python setup.py develop` to install for development or
|                              or create a distribution with `python setup.py bdist_wheel`.
├── src
│   └── PYTHON_PKG          <- Actual Python package where the main functionality goes.
├── tests                   <- Unit tests which can be run with `py.test`.

Usage

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 my_simple_project

Note

This project has been set up using PyScaffold 3.2. For details and usage information on PyScaffold see https://pyscaffold.org/.