Dedupe 2.0.17

dedupe is a library that uses machine learning to perform de-duplication and entity resolution quickly on structured data.

If you’re looking for the documentation for the Web API, you can find that here:

dedupe will help you:

  • remove duplicate entries from a spreadsheet of names and addresses

  • link a list with customer information to another with order history, even without unique customer id’s

  • take a database of campaign contributions and figure out which ones were made by the same person, even if the names were entered slightly differently for each record

dedupe takes in human training data and comes up with the best rules for your dataset to quickly and automatically find similar records, even with very large databases.

Tools built with dedupe A full service web service powered by dedupe for de-duplicating and find matches in your messy data. It provides an easy-to-use interface and provides cluster review and automation, as well as advanced record linkage, continuous matching and API integrations. See the product page and the launch blog post.

csvdedupe Command line tool for de-duplicating and linking CSV files. Read about it on Source Knight-Mozilla OpenNews.



  • machine learning - reads in human labeled data to automatically create optimum weights and blocking rules

  • runs on a laptop - makes intelligent comparisons so you don’t need a powerful server to run it

  • built as a library - so it can be integrated in to your applications or import scripts

  • extensible - supports adding custom data types, string comparators and blocking rules

  • open source - anyone can use, modify or add to it


pip install dedupe

Errors / Bugs

If something is not behaving intuitively, it is a bug, and should be reported. Report it here

Contributing to dedupe

Check out dedupe repo for how to contribute to the library.

Check out dedupe-examples for how to contribute a useful example of using dedupe.

Citing dedupe

If you use Dedupe in an academic work, please give this citation:

Gregg, Forest and Derek Eder. 2015. Dedupe.

Indices and tables