J535D165/recordlinkage

Health v2 · maintenance only

Adoption not part of the score

1060 stars · 152 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A modular Python toolkit for record linkage and duplicate detection across datasets, built on pandas and numpy. It provides indexing (blocking) methods, record comparison/similarity functions, and classifiers for linking records within or between data sources.

Use cases

• deduplicate customer records in a database
• match records between two datasets with fuzzy string comparison
• entity resolution for messy data
• find duplicate entries in a pandas dataframe
• link patient records across datasets
• probabilistic record linkage with Fellegi-Sunter

When to choose

• you need to link or deduplicate small to medium-sized tabular datasets in Python
• you want pandas-integrated record linkage with extensible comparison and classification steps
• you need classic record linkage algorithms like blocking, Jaro-Winkler, and supervised classifiers

When to avoid

• you need to deduplicate very large datasets that exceed pandas memory limits
• you need real-time or streaming entity resolution
• you want a turnkey GUI or service rather than a Python library

Facets

library · maturity maintenance

machine-learning data-science etl search-engine data-science privacy python record-linkage entity-resolution deduplication data-matching string-similarity pandas blocking fuzzy-matching data-engineering algorithms

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