https://github.com/guiferviz/recipipe

Improved pipelines for data science projects.
https://github.com/guiferviz/recipipe

data-science machine-learning machine-learning-pipelines pipeline preprocessing sklearn

Last synced: 4 months ago
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Improved pipelines for data science projects.

• Host: GitHub
• URL: https://github.com/guiferviz/recipipe
• Owner: guiferviz
• License: mit
• Created: 2019-03-11T20:32:39.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2020-06-11T22:52:01.000Z (about 6 years ago)
• Last Synced: 2025-01-29T08:11:16.640Z (over 1 year ago)
• Topics: data-science, machine-learning, machine-learning-pipelines, pipeline, preprocessing, sklearn
• Language: Python
• Homepage:
• Size: 6.89 MB
• Stars: 4
• Watchers: 3
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Authors: AUTHORS.md

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README

          



  



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Improved pipelines for data science projects.

# Getting started

## Why Recipipe?

It has cool features, like selecting columns using Unix patterns:



or getting beautiful output column names instead of numeric indexed outputs:



or fitting a different transformer per group:



Read the tutorials and other examples to learn more.

## Install from PyPI

    pip install recipipe

All the dependencies will be installed automatically.

## Install from source

Clone the repository and run:

	pip install .

Install the package in a dev environment with:

    pip install -e .

All the dependencies will be installed automatically.

## Tutorials and examples

* Explore a notebook with a

[list of things you can do with Recipipe](examples/features.ipynb).

* Learn how to [transform Titanic data](examples/titanic.ipynb).

* Learn how to use Recipipe analyzing data from weird creatures from another

planet: [Recipipe getting started tutorial](examples/paranoids.ipynb).

## Running the tests

Run all the test using:

    pytest

Run an specific test file with:

    pytest tests/

Run tests with coverage using:

    coverage run --source=recipipe -m pytest

# What's the meaning of Recipipe?

It comes from a beautiful R library called [recipes][recipesR] and the concept

of [pipelines][pipelinesWikipedia].

    recipes + pipelines = recipipe

That explains the logo of a muffing (recipes) holding some pipes (pipelines).



  



# License

This project is licensed under the **MIT License**, see the

[LICENSE][license] file for details.

# Author

*guiferviz*, contributions are more than welcome.

[![Twitter @guiferviz](https://img.shields.io/twitter/follow/guiferviz?style=social)](https://twitter.com/guiferviz)

[license]: https://github.com/guiferviz/recipipe/blob/master/LICENSE

[recipesR]: https://github.com/tidymodels/recipes

[pipelinesWikipedia]: https://en.wikipedia.org/wiki/Pipeline_(computing)