textstat 0.1.0

Readability metrics for English text: Flesch Reading Ease, Flesch-Kincaid, Gunning Fog, SMOG, ARI, Coleman-Liau, plus word/sentence/syllable counts. Zero-dependency, no_std.
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    15 out of 15 items documented1 out of 8 items with examples
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  • Documentation size: 203.86 kB This is the summed size of all files generated by rustdoc for all configured targets
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  • all releases: 2s Average build duration of successful builds in releases after 2024-10-23.
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textstat

Crates.io Documentation CI License no_std

Readability metrics for English text. Flesch Reading Ease, Flesch-Kincaid Grade, Gunning Fog, SMOG, Automated Readability Index, Coleman-Liau — plus the word / sentence / syllable counts they're built on. Inspired by Python's textstat. Zero dependencies, #![no_std].

let text = "The cat sat on the mat. The dog ran fast.";

assert_eq!(textstat::lexicon_count(text), 10);   // words
assert_eq!(textstat::sentence_count(text), 2);
assert_eq!(textstat::syllable_count(text), 10);

let ease = textstat::flesch_reading_ease(text);  // ~117 (very easy)
let grade = textstat::flesch_kincaid_grade(text); // ~ -1.8 (well below grade 1)

Why textstat?

Rust's readability crates are article extractors (arc90/Mozilla Readability) — they pull the main content out of a web page. None of them compute readability scores. textstat fills that gap: drop-in functions for the standard formulas, useful for content tooling, SEO, writing assistants, education, and accessibility (WCAG) checks.

Install

[dependencies]
textstat = "0.1"

Metrics

Function Returns
flesch_reading_ease 0–100+ score (higher = easier)
flesch_kincaid_grade U.S. school grade level
gunning_fog U.S. school grade level
smog_index U.S. school grade level
automated_readability_index U.S. school grade level
coleman_liau_index U.S. school grade level
reading_time(text, wpm) estimated seconds to read

Counts

lexicon_count (words), sentence_count, syllable_count, syllables(word), polysyllabic_count, char_count (non-whitespace), letter_count.

Accuracy

Syllables are estimated with a fast English heuristic (vowel groups + a silent-e rule, including accented Latin vowels), not a pronunciation dictionary, so scores are close to — not bit-identical with — dictionary-based tools. The metric formulas are the standard published ones.

  • sentence_count skips decimal points (3.14) and initialism dots (U.S.A.); trailing abbreviation dots (Dr.) may still add one.
  • Best results are on English text. Non-Latin scripts (no Latin vowels) fall back to one syllable per word, so scores stay bounded rather than correct.
  • Empty input yields 0 everywhere — no panics, no division by zero.

no_std

textstat is #![no_std] (needs only alloc) with a dependency-free Newton's -method sqrt, so it builds for bare-metal targets such as thumbv7em-none-eabi.

License

Licensed under either of Apache-2.0 or MIT at your option.