skillfed

rake-nltk

RAKE short for Rapid Automatic Keyword Extraction algorithm, is a domain independent keyword extraction algorithm which tries to determine key phrases in a body of text by analyzing the frequency of word appearance and its co-occurance with other words in the text.

rake-nltk v1.0.6 316.2K downloads/30d#7,679 on PyPI1,083
Permissive license MIT Abandoned released

What it is and what it does

rake-nltk is a Python implementation of the RAKE (Rapid Automatic Keyword Extraction) algorithm, which identifies important phrases in text by analyzing word frequency and co-occurrence patterns. It wraps NLTK to provide configurable tokenization, language-specific stop words, and ranking metrics, making it suitable for extracting domain-independent keywords from documents without manual tuning.

The package offers a simple interface: initialize a Rake object, pass text or sentences to it, and retrieve ranked phrases either as a list or with their scores. It is designed to be modular and tunable, though it has not been actively maintained since late 2022 and is now abandoned.

Use it for:

  • Extract key topics from research papers or articles for quick summarization and indexing.
  • Identify important terms from customer feedback or survey responses for sentiment analysis.
  • Generate tag suggestions for blog posts or documents based on automatic phrase detection.
  • Build a keyword index for search engines or information retrieval systems.
  • Analyze text corpora to discover domain terminology without pre-labeled training data.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Extracts keywords and key phrases from text using the RAKE algorithm, which ranks words by their frequency and co-occurrence patterns to identify domain-independent topic terms.

Yes, if you need a lightweight, simple keyword extraction tool and can tolerate an abandoned package. The MIT license is permissive, install friction is low, and there are no known vulnerabilities. However, be aware that no updates or maintenance will occur; test thoroughly with your Python version and nltk version before relying on it in production. For active projects requiring ongoing support, consider maintained alternatives.

Install

rake-nltk on PyPI

pip

pip install rake-nltk

uv

uv add rake-nltk

poetry

poetry add rake-nltk

Installing rake-nltk

Before you install

Low friction install with a single runtime dependency (nltk). However, the package is abandoned—last release was 2021-09-15 and last commit 2022-12-09—so expect no maintenance, bug fixes, or updates to support newer Python versions beyond what's already declared.

License in practice

MIT license is permissive; you can use, modify, and distribute this package freely in commercial or private projects with minimal restrictions.

Quickstart

pip install rake-nltk

from rake_nltk import Rake

r = Rake()
r.extract_keywords_from_text("your text here")
print(r.get_ranked_phrases_with_scores())

Requires NLTK's stopwords corpus; download it first with: python -c "import nltk; nltk.download('stopwords')"

Verify before relying

  • Whether the package works reliably with Python versions beyond 3.9 despite being abandoned.
  • Performance characteristics on large documents or high-volume keyword extraction tasks.
  • Compatibility with recent versions of nltk and whether dependency version pinning is needed.

Package facts

License MIT (permissive)
Python support supports the current Python release (>=3.6,<4.0)
Install friction low — pure-Python wheel
Runtime dependencies 1 — nltk
Maintenance abandoned — 1,794 days since the last release
Last repo commit
First released
Downloads 316,250/month — #7,679 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: rake_nltk-1.0.6-py3-none-any.whl

Keywords: nlp, text-mining, algorithms, development

Development Status :: 3 - AlphaIntended Audience :: DevelopersIntended Audience :: EducationLicense :: OSI Approved :: MIT LicenseOperating System :: POSIXProgramming Language :: Python :: 3Programming Language :: Python :: 3.6Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Software Development :: Build ToolsTopic :: Software Development :: Libraries :: Python Modules

Tags

keyword extractionautomatic phrase detectiontext mining nlprake algorithmkey phrase rankingdocument summarizationnlp keyword analysis
keyword-extractionnlptext-analysis

More Python Modules packages