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dedupe

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What dedupe is

dedupe is an open-source Python library for fuzzy matching, deduplication, and entity resolution on structured data. It learns to identify similar records from examples labeled by people, including when working with very large databases. The project describes uses such as removing repeated spreadsheet entries, connecting customer and order records that lack unique IDs, and identifying people across campaign contribution records. Developers can run the library on a local machine or server and integrate it into applications or import scripts to build self-hosted entity-resolution pipelines. Its documented features include learning from labeled data, laptop execution, and extensible data types and comparators. Installation is documented with `pip install dedupe`; a separate csvdedupe command-line tool supports CSV deduplication. The open-source library is free. Dedupe.io, a related web service, shut down on January 31, 2023, and its team now focuses on consulting through DataMade. The project directs bug reports to GitHub Issues and lists a mailing list for the library.

Who it suits

It suits Python developers who need to match, deduplicate, or resolve identities in structured data and can provide human-labeled examples. It can run locally or on servers as part of an application or self-hosted pipeline.

What it does well

  • Free, open-source Python library.
  • Learns matching rules from human-labeled examples.
  • Can run locally or on servers.
  • Integrates into applications and import scripts.
  • Includes extensible data types and comparators.

What to know first

  • Dedupe.io shut down on January 31, 2023.
  • The web service’s former upload-and-review workflow is discontinued.
  • Use requires working with a Python library.

Getting started

  1. Open the dedupe project on GitHub.
  2. Install the library with `pip install dedupe`.
  3. Use human-labeled record examples to train matching rules.
  4. Integrate the library into an application or import script, or run it on a local machine or server.
  5. Use the separate csvdedupe command-line tool for CSV deduplication.

Verdict

dedupe offers an open-source library for developers building structured-data matching and deduplication workflows. Do not confuse it with Dedupe.io, which shut down in 2023.

Questions

Is dedupe free?

Yes. The library is listed as free and open source.

What does dedupe do?

It uses machine learning for fuzzy matching, deduplication and entity resolution on structured data.

Which platforms does it support?

The listed platforms are API, Linux, macOS, self-hosted and Windows.

Is Dedupe.io still available?

No. Dedupe.io shut down on January 31, 2023. Its team now focuses on consulting through DataMade.

How do I install the library?

The documented installation command is `pip install dedupe`.

What support options does the project list?

The project directs bug reports to GitHub Issues and lists a mailing list for the open-source library.

Facts from dedupe's own pages

API
The former Dedupe.io web API supported matching and training against projects through REST calls, including incremental checks, matches and additions after deduplication. · dedupe.io, 4 Oct 2026
Compliance
The former service's FAQ states that Dedupe.io was certified FERPA compliant as of July 2019. · dedupe.io, 10 Oct 2026
Data formats
The former service’s FAQ says uploads accepted Excel spreadsheets and CSV files, with one record per row and column names in the first row. · dedupe.io, 4 Oct 2026
Data privacy
The former service's FAQ says it would not rent or sell submitted data and would not allow third-party access without signed consent. · dedupe.io, 10 Oct 2026
Features
Documented features include learned weights and blocking rules, laptop execution, library integration, and support for custom data types, comparators, and blocking rules. · docs.dedupe.io, 10 Oct 2026
Headquarters
Chicago, Illinois, United States · github.com, 28 Sept 2026
How it learns
It uses human-labeled training data to learn rules for finding similar records, including in large databases. · docs.dedupe.io, 10 Oct 2026
Input formats
The former Dedupe.io service accepted spreadsheet files (.xls, .xslx) and comma-separated text (.csv). · dedupe.io, 10 Oct 2026
Installation
The documentation gives `pip install dedupe` as the installation command. · docs.dedupe.io, 10 Oct 2026
Integrations
The project describes dedupe as a library that can be integrated into applications or import scripts; it also documents CSV deduplication through the separate csvdedupe command-line tool. · docs.dedupe.io, 4 Oct 2026
Intended users
The maintainers describe the library as suitable for integration into applications or import scripts, while the former Dedupe.io service was designed as an online tool for non-developers. · docs.dedupe.io, 10 Oct 2026
License
The GitHub repository identifies the project as MIT licensed. · github.com, 10 Oct 2026
Open source library
dedupe is a Python library that uses machine learning for fuzzy matching, deduplication and entity resolution on structured data. · github.com, 4 Oct 2026
Privacy
The former service’s FAQ says its privacy policy prohibited renting or selling user data and third-party access without signed consent, and limited company access to debugging and service improvement. · dedupe.io, 4 Oct 2026
Product status
Dedupe.io, the hosted service, shut down on January 31, 2023. · dedupe.io, 10 Oct 2026
Self-hosting
The developer page says Python developers can run the library on local machines or servers and build self-hosted entity-resolution pipelines. · dedupe.io, 4 Oct 2026
Support
The library documentation directs bug reports to GitHub Issues and lists a mailing list for users. · docs.dedupe.io, 10 Oct 2026
Training
The library uses human-labeled examples to learn rules for finding similar records, including in very large databases. · docs.dedupe.io, 4 Oct 2026
Training limit
The former service required at least 10 positive and 10 negative record-pair examples during training. · dedupe.io, 4 Oct 2026
Training requirement
The former Dedupe.io service required at least 10 positive and 10 negative record-pair examples during model training. · dedupe.io, 10 Oct 2026
Use cases
The library can remove duplicate spreadsheet entries and link customer, order history, or campaign contribution records without relying on unique IDs. · docs.dedupe.io, 10 Oct 2026
Web service workflow
The former Dedupe.io service described a workflow to upload data, train a model, review automatically found matches, and download results. · dedupe.io, 4 Oct 2026
What it does
The dedupe Python library uses machine learning for fuzzy matching, deduplication, and entity resolution on structured data. · github.com, 10 Oct 2026

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