english-words
Generate sets of english words by combining different word lists
Decision gist · record as of 2026-08-14
Yes, if you need an offline English word corpus and can tolerate the ~20MB footprint and aging maintenance. The package is stable (MIT licensed, no vulnerabilities, low install friction) and suitable for spell-checking, word games, or linguistic tasks. However, if you need active development, Unicode normalization, or additional word lists, consider whether a maintained alternative or a custom word source would better fit your needs.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Low friction to install as a pure Python wheel with no runtime dependencies.
- Maintenance is aging—last release was a year ago and the repository shows minimal recent activity, though it remains archived and functional.
License · maintenance · safety
MIT (permissive) — MIT license permits free use, modification, and distribution with minimal restrictions, making it suitable for both open-source and commercial projects.
last release 2025-08-14 (365 days) · last repo commit 2025-08-14 · 34 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 136,790 downloads/mo, #11,388 on PyPI
Alternatives
Verify before relying
pip install english-words
from english_words import get_english_words_set
web2_lower = get_english_words_set(['web2'], lower=True)
if 'hello' in web2_lower:
print('Valid word')- Whether the ~20MB package size remains acceptable for typical use cases or if lazy-loading of word lists is planned.
- Current state of Unicode character handling in GCIDE entries (the description notes unprocessed Unicode like `<ae/` instead of `æ`).
What it is and what it does
english-words is a Python package that bundles pre-processed English word lists (GCIDE and web2) and exposes them as in-memory sets. You call `get_english_words_set()` with a list of source identifiers and optional flags to retrieve a set of words filtered by case (lowercase conversion) and character type (alphanumeric-only). The word lists are pre-processed at package build time, so filtering operations run at constant speed regardless of which flags you use.
The package is designed for tasks like word validation, spell-checking, or linguistic analysis where you need a reliable, offline English word corpus. It trades disk space (~20MB) for simplicity: all data is bundled and ready to use without external API calls or downloads. The main constraint is that it includes only two word lists (GCIDE and web2), each with different capitalization conventions, so combining them requires care.
Use it for
- Validate user input against a known English word list in spell-checkers or word games.
- Generate word lists for linguistic analysis, NLP training, or text-processing pipelines.
- Filter or deduplicate words in data processing by checking membership against a curated set.
- Build offline word-lookup tools that don't require network access or external services.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need an offline English word corpus and can tolerate the ~20MB footprint and aging maintenance.
The package is stable (MIT licensed, no vulnerabilities, low install friction) and suitable for spell-checking, word games, or linguistic tasks. However, if you need active development, Unicode normalization, or additional word lists, consider whether a maintained alternative or a custom word source would better fit your needs.
Install
english-words on PyPI
Before you install
Low friction to install as a pure Python wheel with no runtime dependencies. Maintenance is aging—last release was a year ago and the repository shows minimal recent activity, though it remains archived and functional.
License in practice
MIT license permits free use, modification, and distribution with minimal restrictions, making it suitable for both open-source and commercial projects.
Quickstart
pip install english-words
from english_words import get_english_words_set
web2_lower = get_english_words_set(['web2'], lower=True)
if 'hello' in web2_lower:
print('Valid word')Verify before relying
- Whether the ~20MB package size remains acceptable for typical use cases or if lazy-loading of word lists is planned.
- Current state of Unicode character handling in GCIDE entries (the description notes unprocessed Unicode like `<ae/` instead of `æ`).
Package facts
| License | MIT permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Aging 365 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 136,790 / month, #11,388 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/StableLicense :: OSI Approved :: MIT LicenseNatural Language :: EnglishProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.9 |
Evidence: english_words-2.0.2-py3-none-any.whl
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