WrangleWorks Makes its Data Analysis Platform Open-Source

"Wrangles Python" reduces the amount of knowledge and code required to enrich data.

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AUSTIN, Texas — WrangleWorks, a provider of tools to automate data work, has open-sourced its Wrangles Python package.

Wrangles dramatically reduces the Python knowledge and code required to clean and semantically enrich data.

“Wrangles provides configurable transformations and recipes for data enrichment and automation,” said WrangleWorks CTO Chris Ince. “Wrangles are defined and run using an intuitive, low-code configuration syntax that requires only the most basic knowledge of Python. With Wrangles, virtually anyone can automate data preparation and integration.”

With Wrangles, “citizen wranglers” can:

  • Extract meaningful information from unstructured text
  • Format and standardize data quickly
  • Classify data into categories and hierarchies using machine learning modelsMap and move data from one system to another
  • Translate text accurately between languages

Wrangles was built to provide the clean, enriched data required by modern analytical and e-commerce applications.  It replaces manual data cleaning methods, which cannot keep pace with such large, dynamic systems. Wrangles can be used freely by citizen wranglers to automate all facets of data work, including applying application-specific semantics.

The Wrangles Python package is available on github and pypi.org.

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