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life4/textdistance

📐 Compute distance between sequences. 30+ algorithms, pure python implementation, common interface, optional external libs usage. observed · 2026-08-28

github.com/life4/textdistance · Python · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

30/100

  • Activity 17
  • Release rhythm 8
  • Longevity 100
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 3407
  • days_rel: n/a
  • days_push: 502
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

3540 stars · 261 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A Python library for computing distances and similarities between two or more sequences using 30+ algorithms such as Levenshtein, Hamming, and Jaccard. It offers a pure Python implementation with a common interface and optional external libraries or NumPy for speed.

Use cases

  • compare similarity between two strings
  • compute levenshtein distance in python
  • fuzzy match text records
  • deduplicate similar names in a dataset
  • measure sequence distance for record linkage
  • find closest matching string to a query

When to choose

  • you need many string distance algorithms behind one consistent API
  • you want a pure Python fallback with optional accelerated backends
  • you need to compare more than two sequences at once

When to avoid

  • you need maximum raw performance for a single algorithm - a dedicated C implementation like python-Levenshtein is faster
  • you need non-text sequence distances outside its supported algorithm set

Facets

library · maturity active

nlp parser math developer-tools python cross-platform string-similarity levenshtein sequence-comparison fuzzy-matching text-analysis natural-language-processing algorithms

1 source

Member repositories

RepositoryRoleHealth v2
life4/textdistancemain30

For agents

markdown · JSON · MCP: product_card(name="life4/textdistance")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem