1e0ng/simhash
A Python Implementation of Simhash Algorithm observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 4736
- days_rel: n/a
- days_push: 1623
- n_releases_24m: 0
Adoption not part of the score
1039 stars · 221 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A Python implementation of the Simhash algorithm for near-duplicate detection and similarity estimation of text. It provides a small, focused library for computing Simhash fingerprints and comparing their Hamming distance.
Use cases
- detect near-duplicate documents in a corpus
- deduplicate web pages or news articles
- compute similarity between text strings
- find duplicate content at scale with hashing
- cluster similar text documents
- identify plagiarism or copied content
When to choose
- you need fast, lightweight near-duplicate detection in Python
- you want a minimal, dependency-free Simhash implementation
- you are processing large text collections where exact matching is insufficient
When to avoid
- you need full semantic similarity rather than lexical near-duplicates
- you need actively maintained features or support
- you need embeddings-based similarity for short texts
Facets
library · maturity maintenance
nlp search-engine parser python simhash locality-sensitive-hashing near-duplicate-detection text-similarity hashing natural-language-processing algorithms search
2 sources
- readme: https://github.com/1e0ng/simhash · fetched 2026-08-28 · 2807b9827f1b
- registry_pypi: https://pypi.org/pypi/simhash/json · fetched 2026-08-29 · 6b59c3292c9b
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| 1e0ng/simhash | main | 32 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem