=============================== PyRefine

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OpenRefine_ is a great tool for exploring and cleaning datasets prior to analysing them. It also records an undo history of all actions that you can export as a sort of script in JSON_ format. However, in order to execute that script on a new dataset, you need to manually import it through the graphical interface or set up a BatchRefine_ server, neither of which is quick.

PyRefine allows you to execute OpenRefine JSON scripts against datasets without firing up a full Java/OpenRefine server. It has a commandline tool for quick use, or you can use it as a library to integrate it into your pandas_-based data analysis pipeline.

More details in this blog post_.

Please note: PyRefine is still very much alpha-quality. It probably doesn't work exactly how you're expecting right now. That said, please try it out, and consider :doc:contributing!

.. _OpenRefine: http://openrefine.org .. _JSON: http://en.wikipedia.org/wiki/JSON .. _BatchRefine: https://github.com/fusepoolP3/p3-batchrefine .. _pandas: http://pandas.pydata.org/ .. _this blog post: https://erambler.co.uk/blog/introducing-pyrefine-openrefine-python/

• Free software: MIT license
• Documentation: https://pyrefine.readthedocs.io.

Features

• Execute OpenRefine JSON against a dataset from the command line
• Execute OpenRefine JSON from a Python script

Credits

This package was created with Cookiecutter_ and the audreyr/cookiecutter-pypackage_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter .. _audreyr/cookiecutter-pypackage: https://github.com/audreyr/cookiecutter-pypackage