Metadata-Version: 2.1
Name: pyscaffoldext-dsproject
Version: 0.1
Summary: PyScaffold extension for Data Science projects
Home-page: https://github.com/pyscaffold/pyscaffoldext-dsproject
Author: Florian Wilhelm
Author-email: florian.wilhelm@gmail.com
License: mit
Project-URL: Documentation, https://pyscaffold.org/
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
Description-Content-Type: text/markdown
Requires-Dist: pyscaffold (<4.0a0,>=3.2a0)
Requires-Dist: pyscaffoldext-markdown
Provides-Extra: testing
Requires-Dist: flake8 ; extra == 'testing'
Requires-Dist: pytest ; extra == 'testing'
Requires-Dist: pytest-cov ; extra == 'testing'
Requires-Dist: pytest-virtualenv ; extra == 'testing'
Requires-Dist: pytest-xdist ; extra == 'testing'

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# pyscaffoldext-dsproject

PyScaffold extension tailored for *Data Science* projects. This extension is inspired by
[cookiecutter-data-science] and enhanced in many ways.

Besides the typical [PyScaffold] layout, the extensions provides:

* `data` folder to keep your data,
* `experiments` folder for the actual scripts, e.g. `train_model.py`,
* `notebooks` for data exploration with [Jupyter] notebooks,
* `notebooks/template.ipynb` for starting with the most important imports and plugins,
* `models` for trained and serialized models, model predictions, or model summaries,
* `references` for data dictionaries, manuals, and all other explanatory materials.
* `reports` for generated analysis as HTML, PDF, LaTeX, etc. and a `figures` subdirectory
  for generated graphics and figures to be used in reporting,
* `environment.yaml` to create an [conda][Miniconda] environment with the most
  needed data science libraries and tools,

Check out the initial project structure under [dsproject-demo].

## Usage

Just install this package with `pip install pyscaffoldext-dsproject`
and note that `putup -h` shows a new option `--dsproject`.

## Note

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

[PyScaffold]: https://pyscaffold.org/
[cookiecutter-data-science]: https://github.com/drivendata/cookiecutter-data-science
[Miniconda]: https://docs.conda.io/en/latest/miniconda.html
[Jupyter]: https://jupyter.org/
[dsproject-demo]: https://github.com/pyscaffold/dsproject-demo


