# WikiExtractor/wikiextractor

A tool for extracting plain text from Wikipedia dumps

Repository: https://github.com/WikiExtractor/wikiextractor
Canonical: https://ross.abutalabs.com/products/wikiextractor
Homepage: http://wikiextractor.github.io/wikiextractor/
Language: Python
License: AGPL-3.0
License Family: copyleft
Last push: 2026-08-10T19:52:00+00:00

## Health v2 (maintenance only)
Score: 98/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 97, release rhythm 97, longevity 100
- inputs: {"age_days": 4182, "days_push": 23, "days_rel": 23, "gap_med": 18, "n_releases_24m": 2}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4001, forks 1003 (observed 2026-08-28T04:08:32.061351+00:00)

## What it is
WikiExtractor is a Python command-line tool that extracts and cleans plain text from Wikipedia database backup dumps (XML). It supports template expansion, multiprocessing, and JSON or custom document output formats.

## Use cases
- extract plain text from a Wikipedia dump
- build a text corpus for NLP training from Wikipedia
- convert Wikipedia XML dumps to JSON documents
- preprocess Wikipedia articles for language model training
- extract a single page from a Wikipedia dump
- strip MediaWiki markup and templates from articles

## When to choose
- you need clean plain text from full Wikipedia dumps
- you want a dependency-free Python tool
- you need parallel extraction of large dumps
- you want template expansion or JSON output

## When to avoid
- you need live Wikipedia API access rather than offline dumps
- you're on Windows, where StringIO issues cause problems
- you need other MediaWiki-based wikis with complex custom templates
- you need structured data like wikidata triples

## Facets
- artifact type: cli-tool
- maturity: stable
- function: parser, nlp, etl, cli
- domain: developer-tools
- platform: python, cli, cross-platform
- tags: wikipedia, text-extraction, wiki-dump, mediawiki, corpus-preparation, natural-language-processing, data-engineering, linux, macos

## Member repositories
- WikiExtractor/wikiextractor (main) score 98

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:32.061351+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 2026-08-29T18:24:07.682370+00:00, confidence not recorded.
  - readme: https://github.com/WikiExtractor/wikiextractor (fetched 2026-08-28T04:08:32.061351+00:00, sha 52562b6d4232)
  - homepage: http://wikiextractor.github.io/wikiextractor/ (fetched 2026-08-29T09:17:14.018590+00:00, sha b8d76997114d)
- Data as of 2026-08-30T08:39:29.467469+00:00.