csurfer/rake-nltk

Health v2 · maintenance only

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Adoption not part of the score

1083 stars · 151 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

rake-nltk is a Python library implementing the Rapid Automatic Keyword Extraction (RAKE) algorithm on top of NLTK. It determines key phrases in a body of text by analyzing word frequency and co-occurrence, with configurable tokenizers, language stopwords, and ranking metrics.

Use cases

• extract keywords from text in python
• get key phrases from a document
• rake keyword extraction python implementation
• automatically tag articles with keyphrases
• find top ranked keywords with scores
• keyword extraction without training a machine learning model
• pull key phrases from sentences for search indexing

When to choose

• you need a simple, domain-independent keyword extractor that works out of the box with no training data
• you want a lightweight pip-installable library rather than heavy ML or transformer dependencies
• you need configurable tokenization, language-based stopwords, or a custom ranking metric
• you are working with individual documents or short texts where statistical co-occurrence scoring is sufficient

When to avoid

• you need semantically aware or state-of-the-art keyphrase extraction (consider embedding- or transformer-based tools like KeyBERT)
• you need to process very large corpora or streams at scale rather than individual documents
• you require languages or tokenization rules not covered by NLTK's stopwords and tokenizers
• you need actively developed software with frequent updates

Facets

library · maturity stable

nlp python cross-platform keyword-extraction text-mining rake keyphrases nltk stopwords natural-language-processing

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