# xiaoxu193/PyTeaser

Summarizes news articles

Repository: https://github.com/xiaoxu193/PyTeaser
Canonical: https://ross.abutalabs.com/products/pyteaser
Homepage: http://xiaoxu193.github.io/PyTeaser/
Language: Python
License: MIT
License Family: permissive
Topics: pyteaser, news-articles
Last push: 2021-08-28T22:29:17+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4665, "days_push": 1831, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1171, forks 173 (observed 2026-08-28T04:03:51.591389+00:00)

## What it is
PyTeaser is a Python library that summarizes news articles by ranking sentences for relevance to the title, keywords, position, and length, returning the top sentences as a summary. It is a Python port of the Scala TextTeaser project and can extract article text from a URL or work with provided text.

## Use cases
- summarize news articles from a url in python
- extract key sentences from an article
- generate brief summaries of long text
- automatic text summarization library
- get article summary from webpage

## When to choose
- you need simple extractive summarization of news articles in Python 2.7
- you want a lightweight, dependency-free-of-ML summarizer based on sentence ranking heuristics

## When to avoid
- you are on Python 3 - the library requires Python 2.7 and is unmaintained
- you need abstractive or neural summarization
- you need an actively maintained project

## Facets
- artifact type: library
- maturity: abandoned
- function: nlp, parser, web-scraping
- domain: media, developer-tools
- platform: python, cli
- tags: text-summarization, extractive-summarization, news-articles, python2, sentence-ranking, natural-language-processing

## Member repositories
- xiaoxu193/PyTeaser (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:51.591389+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:28:33.886889+00:00, confidence not recorded.
  - readme: https://github.com/xiaoxu193/PyTeaser (fetched 2026-08-28T04:03:51.591389+00:00, sha 01a9c35b2d9b)
  - homepage: http://xiaoxu193.github.io/PyTeaser/ (fetched 2026-08-29T12:34:21.510537+00:00, sha 2915b3e4bcb7)
  - registry_pypi: https://pypi.org/pypi/pyteaser/json (fetched 2026-08-29T12:34:21.519563+00:00, sha 5f3f53dfa3c4)
- Data as of 2026-08-30T08:39:29.467469+00:00.