fuzzyset2

What it is and what it does

fuzzyset2 is a data structure for fuzzy string matching that finds approximate matches in a set of strings. It breaks strings into n-grams (substrings of configurable length), builds a reverse index, and uses cosine similarity and optional Levenshtein distance scoring to rank matches by similarity. You add strings to the set once, then query it with potentially misspelled or slightly different text to get back a list of (score, matched_string) tuples where the score ranges from 0 to 1.

The package is a maintained fork of the original fuzzyset, designed for use cases like autocomplete, typo correction, and record deduplication. It depends on rapidfuzz for distance calculations and supports Python 3.6 and later across Windows, macOS, and Linux. The library is stable and production-ready but receives infrequent updates.

Use it for:

• Autocomplete and search suggestions that tolerate user typos and spelling variations
• Deduplicating records in databases where names or identifiers may be slightly different
• Spell-checking and typo correction in text processing pipelines
• Matching user input against a predefined set of valid options with fuzzy tolerance
• Entity resolution and record linkage in data integration workflows

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Performs fuzzy string matching and approximate searching against a set of strings, returning scored matches for misspellings and similar text.

Yes, if you need fuzzy string matching in a stable, low-dependency library. The permissive BSD license and broad platform support make it accessible. However, the dormant maintenance status (no releases in 662 days) means you should verify that version 0.2.5 meets your Python and rapidfuzz compatibility needs before committing to it for a long-lived project.

Install

fuzzyset2 on PyPI

pip install fuzzyset2

uv add fuzzyset2

poetry add fuzzyset2

Installing fuzzyset2

Before you install

Medium install friction due to compiled wheels for multiple Python versions and platforms. Dormant maintenance status (last commit 2024-11-25, no releases in 662 days) means bug fixes and compatibility updates are unlikely, though the package is marked Production/Stable.

License in practice

BSD permissive license allows commercial and private use with minimal restrictions, making it suitable for most projects.

Quickstart

pip install fuzzyset2

from fuzzyset2 import FuzzySet

fs = FuzzySet()
fs.add("michael axiak")
results = fs.get("micael asiak")
print(results)

Requires Python 3.6 or later; rapidfuzz must be installed as a runtime dependency.

Verify before relying

• Whether a Cython-accelerated variant is available or built by default in version 0.2.5
• Performance characteristics and typical latency for large datasets or high-frequency queries
• Compatibility with rapidfuzz versions and whether it is a hard runtime requirement or optional

Package facts

Evidence: fuzzyset2-0.2.5-cp310-cp310-macosx_10_9_x86_64.whl; fuzzyset2-0.2.5-cp310-cp310-macosx_11_0_arm64.whl; fuzzyset2-0.2.5-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl; fuzzyset2-0.2.5-cp310-cp310-win32.whl; fuzzyset2-0.2.5-cp310-cp310-win_amd64.whl; fuzzyset2-0.2.5-cp311-cp311-macosx_10_9_x86_64.whl; fuzzyset2-0.2.5-cp311-cp311-macosx_11_0_arm64.whl; fuzzyset2-0.2.5-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl; fuzzyset2-0.2.5-cp311-cp311-win32.whl; fuzzyset2-0.2.5-cp311-cp311-win_amd64.whl; fuzzyset2-0.2.5-cp312-cp312-macosx_10_13_x86_64.whl; fuzzyset2-0.2.5-cp312-cp312-macosx_11_0_arm64.whl; fuzzyset2-0.2.5-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl; fuzzyset2-0.2.5-cp312-cp312-win32.whl; fuzzyset2-0.2.5-cp312-cp312-win_amd64.whl; fuzzyset2-0.2.5-cp313-cp313-macosx_10_13_x86_64.whl; fuzzyset2-0.2.5-cp313-cp313-macosx_11_0_arm64.whl; fuzzyset2-0.2.5-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl; fuzzyset2-0.2.5-cp313-cp313-win32.whl; fuzzyset2-0.2.5-cp313-cp313-win_amd64.whl

Keywords: fuzzyset, fuzzy, data, structure

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