lev
lev is an extremely fast Python library for the Levenshtein distance and similarity ratio, written in Rust. 🦀
Installation
uv add lev-rs
or if you prefer slow:
pip install lev-rs
Usage
import lev
lev.distance("kitten", "sitting") # 3
lev.distance("résumé", "resume") # 2
lev.distance("日本語", "日本") # 1
lev.ratio("kitten", "sitting") # 0.769...
lev.ratio("", "") # 1.0
For more details on the API see the API Reference.
Benchmarks
lev is benchmarked against the fastest Python Levenshtein libraries:
rapidfuzz,
editdistance, and
edlib. We excluded slower implementations like
pylev and python-Levenshtein.
Benchmarks were run on an Apple Mac Mini M2 Pro (macOS 27.0) using Python 3.13. The ASCII, Latin-1, CJK, and Emoji pairs are exactly 100 characters long; the realistic-text pair is natural-length prose. Results represent the total wall time for 1,000 repetitions using Python's
timeit. To reproduce, runuv run scripts/benchmark.py.
ASCII
lev is significantly faster than the other libraries on 100-character ASCII strings.
Other Encodings
lev maintains its lead across all four CPython string-encoding kinds.
Latin-1
CJK
Emoji
Realistic Text
This pair is a short customer support message with a handful of natural typos.
Contact
To get in contact, please open an issue or contact me via github@markusbilz.com.
1 maintainer
Metadata
1 maintainer
Release files for lev-rs 0.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| lev_rs-0.3.0.tar.gz | 149.0 kB | Details |
Built distributions (wheels)
Total release size: 6.3 MB
Release files / lev_rs-0.3.0.tar.gz
| Download URL | lev_rs-0.3.0.tar.gz |
|---|---|
| Size | 149.0 kB |
| Tags | Source |
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|---|---|
| Size | 396.5 kB |
| Tags | CPython 3.15 CPython 3.15 free-threading macOS 10.12+ universal2 (ARM64, x86-64) macOS 10.12+ x86-64 macOS 11.0+ ARM64 |
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| Tags | CPython 3.15 Windows x86-64 |
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