nltk
Natural Language Toolkit
Decision gist · record as of 2026-08-14
Yes. NLTK is a stable, permissively licensed, actively maintained library with low install friction and no security issues. It's the standard choice for NLP education and research, and a solid foundation for prototyping. Install it if you need foundational NLP tools, linguistic datasets, or are learning the field; consider specialized libraries (spaCy, transformers) if you need production-scale performance or modern deep-learning approaches.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Some corpora and datasets must be downloaded separately via nltk.download().
- Low install friction with a pure-Python wheel distribution.
License · maintenance · safety
Apache License, Version 2.0 (permissive) — Apache License 2.0 (permissive) allows commercial use and modification. Documentation is under Creative Commons Attribution-Noncommercial-No Derivative Works 3.0, and corpora are redistributable for non-commercial use.
last release 2026-08-12 (2 days) · last repo commit 2026-08-13 · 14,694 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 74,083,238 downloads/mo, #454 on PyPI
Alternatives
Verify before relying
pip install nltk
import nltk
from nltk.tokenize import word_tokenize
tokens = word_tokenize('Hello, world!')- Whether all corpora and datasets are included by default or require separate downloads
- Performance characteristics for large-scale text processing workloads
- Compatibility with async/concurrent processing patterns
What it is and what it does
NLTK is a mature, widely-used Python library for natural language processing research and development. It provides modules for core NLP tasks—tokenization, part-of-speech tagging, parsing, semantic analysis—along with curated linguistic datasets and educational tutorials. The library is built on five runtime dependencies (defusedxml, click, joblib, regex, tqdm) that handle XML parsing, command-line interfaces, parallel processing, regex operations, and progress reporting.
Developers use NLTK for academic research, educational projects, and production NLP pipelines. It's positioned as a foundational toolkit rather than a high-performance engine; it trades raw speed for breadth of algorithms, accessibility, and pedagogical clarity. The package is actively maintained, supports current Python versions (3.10–3.14), and carries no known security vulnerabilities.
Use it for
- Tokenize and tag parts of speech in text for linguistic analysis or preprocessing
- Parse sentence structure and extract syntactic relationships for grammar research
- Build educational NLP projects and teach computational linguistics concepts
- Analyze sentiment, extract named entities, or perform text classification with built-in corpora
- Prototype NLP pipelines before moving to specialized production libraries
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
NLTK is a stable, permissively licensed, actively maintained library with low install friction and no security issues. It's the standard choice for NLP education and research, and a solid foundation for prototyping. Install it if you need foundational NLP tools, linguistic datasets, or are learning the field; consider specialized libraries (spaCy, transformers) if you need production-scale performance or modern deep-learning approaches.
Install
nltk on PyPI
Before you install
Low install friction with a pure-Python wheel distribution. Active maintenance with a recent release (2 days old) and steady repository activity. Supports Python 3.10 through 3.14.
Requires Python 3.10 or later. Some corpora and datasets must be downloaded separately via nltk.download().
License in practice
Apache License 2.0 (permissive) allows commercial use and modification. Documentation is under Creative Commons Attribution-Noncommercial-No Derivative Works 3.0, and corpora are redistributable for non-commercial use.
Quickstart
pip install nltk
import nltk
from nltk.tokenize import word_tokenize
tokens = word_tokenize('Hello, world!')Verify before relying
- Whether all corpora and datasets are included by default or require separate downloads
- Performance characteristics for large-scale text processing workloads
- Compatibility with async/concurrent processing patterns
Package facts
| License | Apache License, Version 2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 5 packagesdefusedxmlclickjoblibregextqdm |
| Maintenance | Actively maintained 2 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 74,083,238 / month, #454 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: Information TechnologyIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Scientific/EngineeringTopic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Scientific/Engineering :: Human Machine InterfacesTopic :: Scientific/Engineering :: Information AnalysisTopic :: Text ProcessingTopic :: Text Processing :: FiltersTopic :: Text Processing :: GeneralTopic :: Text Processing :: IndexingTopic :: Text Processing :: Linguistic |
Evidence: nltk-3.10.3-py3-none-any.whl
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