Licenses & attributions
Third-party software and resources used in this project
Python libraries
Flask-Limiter
Applies request limits to selected endpoints.
License: MIT
flask-limiter.readthedocs.ioNumPy
Handles the solver's array and matrix calculations.
License: BSD-3-Clause, with separately licensed bundled components listed by NumPy
numpy.orgFonts
Manrope
Used for body text.
Designer: Mikhail Sharanda
License: SIL Open Font License 1.1
View on Google FontsSpace Grotesk
Used for headings and display text.
Designer: Florian Karsten
License: SIL Open Font License 1.1
View on Google FontsIcons
Inspiration & references
- 3Blue1Brown — Solving Wordle using information theory, a visual explanation of the approach
- Claude Shannon — A Mathematical Theory of Communication, the source of the entropy measure used here
Word lists
The Wordle guess list comes from an archived public copy of the game's list. The possible-answer list begins with the original public answer array and adds answers observed through the New York Times daily-answer API. Practice and retained lookup pages also draw on SCOWL and other public word-list sources. Exact links, hashes and scope are documented on the data page.
Data sources
- Word etymologies — sourced from Wiktionary, available under the Creative Commons Attribution-ShareAlike (CC BY-SA) license. Every displayed etymology links back to its Wiktionary source.
- Definitions and lexical details — selected and lightly formatted from an offline English Wiktionary extract produced by Kaikki. Wiktionary text is available under CC BY-SA 4.0. The import selects up to four senses, collapses whitespace and may shorten long entries; every displayed entry links to its source and identifies the adaptation. Unsourced glosses are omitted, and definitions are never treated as evidence that a word is accepted or can be an answer.
- Opt-in dictionary API lookups — the separate definition API may request a missing word server-side from dictionaryapi.dev. Word-page HTML never waits on that service.
- Exact optimal-play evaluations — derived from Alex Selby's Wordle solver results (MIT License).
- Pronunciations — derived from the CMU Pronouncing Dictionary (BSD-2-Clause). Words absent from CMUdict carry machine-generated estimates from the g2p_en model (Apache-2.0) and are labeled as estimates wherever shown.
- Synonyms, antonyms and categories — derived from Open English WordNet, 2025 edition, under CC BY 4.0.
- Example sentences — from the Tatoeba Project, licensed CC BY 2.0 FR; each displayed sentence is credited to its contributor's Tatoeba username and linked to its sentence page.
- How Sure? comparison facts — quantities, labels and as-of dates from Wikidata, released under CC0 1.0; each round names its source and the date its figures were true.
- Learner-difficulty levels — derived from the CEFR-J Vocabulary Profile ver 1.5, redistributed by Open Language Profiles; free for research and commercial use with citation; copyright Tono Laboratory at TUFS. Cited as: "The CEFR-J Wordlist Version 1.5. Compiled by Yukio Tono, Tokyo University of Foreign Studies. Retrieved from http://www.cefr-j.org/download.html on 1/20/2020."
- Psycholinguistic norms — imageability, familiarity and age-of-acquisition values from the Glasgow Norms (Scott et al., 2019), and perceptual-modality values from the Lancaster Sensorimotor Norms (Lynott et al., 2020), both under CC BY 4.0; values are rescaled and adapted as described on the pages that show them.
- Word-frequency scores — derived from wordfreq by Robyn Speer (code MIT; word-frequency data CC BY-SA 4.0), used for the site's rarity flags and frequency bands.
Full license texts
Follow the project links above for license texts and notices. Python packages may also install transitive dependencies; their metadata and license files are included with the installed packages.