mirror of
https://github.com/crate-ci/typos.git
synced 2024-11-30 04:51:03 -05:00
285e5f633c
This dictionary was taken from OpenOfice
274 lines
8.2 KiB
Rust
274 lines
8.2 KiB
Rust
use indexmap::IndexSet;
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use std::collections::BTreeMap;
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use std::collections::HashMap;
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use std::collections::HashSet;
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use unicase::UniCase;
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type Dict = BTreeMap<UniCase<String>, IndexSet<String>>;
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#[test]
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fn verify() {
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let asset_path = "assets/words.csv";
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let typos_dict = parse_dict(asset_path);
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let new_dict = process(typos_dict);
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let mut content = vec![];
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let mut wtr = csv::WriterBuilder::new()
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.flexible(true)
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.from_writer(&mut content);
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for (typo, corrections) in new_dict {
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let mut row = vec![typo.as_str().to_owned()];
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row.extend(corrections);
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wtr.write_record(&row).unwrap();
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}
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wtr.flush().unwrap();
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drop(wtr);
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let content = String::from_utf8(content).unwrap();
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snapbox::assert_eq_path(asset_path, content);
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}
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fn parse_dict(path: &str) -> Vec<(String, Vec<String>)> {
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let data = std::fs::read(path).unwrap();
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let mut reader = csv::ReaderBuilder::new()
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.has_headers(false)
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.flexible(true)
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.from_reader(&*data);
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reader
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.records()
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.map(Result::unwrap)
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.map(|record| {
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let mut iter = record.into_iter();
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let typo = iter.next().expect("typo");
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(
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typo.to_owned(),
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iter.map(ToOwned::to_owned).collect::<Vec<_>>(),
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)
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})
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.collect()
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}
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fn dict_from_iter<S: Into<String>>(
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iter: impl IntoIterator<Item = (S, impl IntoIterator<Item = S>)>,
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) -> Dict {
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let mut dict = Dict::new();
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for (typo, corrections) in iter {
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let typo = UniCase::new(typo.into().to_ascii_lowercase());
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// duplicate entries are merged
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dict.entry(typo)
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.or_default()
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.extend(corrections.into_iter().map(|c| {
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let mut c = c.into();
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c.make_ascii_lowercase();
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c
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}));
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}
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dict
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}
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fn process<S: Into<String>>(
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iter: impl IntoIterator<Item = (S, impl IntoIterator<Item = S>)>,
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) -> Dict {
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let dict = dict_from_iter(iter);
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let rows: Dict = dict
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.into_iter()
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.filter(|(t, _)| is_word(t))
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.map(|(t, c)| {
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let new_c: IndexSet<_> = c.into_iter().filter(|c| is_word(c)).collect();
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(t, new_c)
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})
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.collect();
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let varcon_words = varcon_words();
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let allowed_words = allowed_words();
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let word_variants = proper_word_variants();
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let rows: Vec<_> = rows
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.into_iter()
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.filter(|(typo, _)| {
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let is_disallowed = varcon_words.contains(&unicase::UniCase::new(typo));
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if is_disallowed {
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eprintln!("{:?} is disallowed; in varcon", typo);
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}
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!is_disallowed
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})
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.filter(|(typo, _)| {
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if let Some(reason) = allowed_words.get(typo.as_ref()) {
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eprintln!("{:?} is disallowed; {}", typo, reason);
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false
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} else {
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true
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}
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})
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.map(|(typo, corrections)| {
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let mut new_corrections = IndexSet::new();
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for correction in corrections {
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let correction = word_variants
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.get(correction.as_str())
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.and_then(|words| find_best_match(&typo, correction.as_str(), words))
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.unwrap_or(&correction);
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new_corrections.insert(correction.to_owned());
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}
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(typo, new_corrections)
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})
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.collect();
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let mut dict = Dict::new();
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for (bad, good) in rows {
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let current = dict.entry(bad).or_default();
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current.extend(good);
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}
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let corrections: HashMap<_, _> = dict
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.iter()
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.flat_map(|(bad, good)| good.iter().map(|good| (good.to_owned(), bad.to_owned())))
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.collect();
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dict.into_iter()
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.filter(|(typo, _)| {
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if let Some(correction) = corrections.get(typo.as_str()) {
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eprintln!("{typo} <-> {correction} cycle detected");
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false
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} else {
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true
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}
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})
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.collect()
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}
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#[test]
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fn test_preserve_correction_order() {
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let dict = process([("foo", ["xyz", "abc"])]);
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let mut corrections = dict.get(&UniCase::new("foo".into())).unwrap().iter();
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assert_eq!(corrections.next().unwrap(), "xyz");
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assert_eq!(corrections.next().unwrap(), "abc");
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}
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#[test]
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fn test_merge_duplicates() {
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assert_eq!(
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process([("foo", ["bar"]), ("foo", ["baz"])]),
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dict_from_iter([("foo", ["bar", "baz"])])
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);
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}
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#[test]
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fn test_duplicate_correction_removal() {
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let dict = process([("foo", ["bar", "bar"])]);
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assert_eq!(dict, dict_from_iter([("foo", ["bar"])]));
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}
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#[test]
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fn test_cycle_removal() {
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assert!(process([("foo", ["foobar"]), ("foobar", ["foo"])]).is_empty());
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}
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#[test]
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fn test_varcon_removal() {
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assert!(process([("colour", ["color"])]).is_empty());
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}
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#[test]
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fn test_varcon_best_match() {
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assert_eq!(
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process([(
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"neighourhood", // note the missing 'b'
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["neighborhood"],
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)]),
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dict_from_iter([(
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"neighourhood",
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["neighbourhood"] // note that 'bor' has become 'bour' to match the typo
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)])
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);
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}
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fn is_word(word: &str) -> bool {
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word.chars().all(|c| c.is_alphabetic())
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}
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fn varcon_words() -> HashSet<unicase::UniCase<&'static str>> {
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// Even include improper ones because we should be letting varcon handle that rather than our
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// dictionary
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varcon::VARCON
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.iter()
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.flat_map(|c| c.entries.iter())
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.flat_map(|e| e.variants.iter())
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.map(|v| unicase::UniCase::new(v.word))
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.collect()
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}
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fn proper_word_variants() -> HashMap<&'static str, HashSet<&'static str>> {
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let mut words: HashMap<&'static str, HashSet<&'static str>> = HashMap::new();
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for entry in varcon::VARCON.iter().flat_map(|c| c.entries.iter()) {
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let variants: HashSet<_> = entry
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.variants
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.iter()
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.filter(|v| v.types.iter().any(|t| t.tag != Some(varcon::Tag::Improper)))
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.map(|v| v.word)
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.collect();
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for variant in variants.iter() {
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let set = words.entry(variant).or_insert_with(HashSet::new);
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set.extend(variants.iter().filter(|v| *v != variant));
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}
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}
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words
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}
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fn find_best_match<'c>(
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typo: &'c str,
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correction: &'c str,
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word_variants: &HashSet<&'static str>,
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) -> Option<&'c str> {
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assert!(!word_variants.contains(correction));
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#[allow(clippy::single_match)]
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match (typo, correction) {
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// Picking the worst option due to a letter swap being an edit distance of two
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("alinging", "aligning") => {
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return None;
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}
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_ => {}
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}
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let current = edit_distance::edit_distance(typo, correction);
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let mut matches: Vec<_> = word_variants
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.iter()
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.map(|r| (edit_distance::edit_distance(typo, r), *r))
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.filter(|(d, _)| *d < current)
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.collect();
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matches.sort_unstable();
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matches.into_iter().next().map(|(_, r)| r)
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}
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fn allowed_words() -> std::collections::HashMap<String, String> {
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let allowed_path = "assets/english.csv";
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let english_data = std::fs::read(allowed_path).unwrap();
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let mut allowed_english = csv::ReaderBuilder::new()
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.has_headers(false)
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.flexible(true)
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.from_reader(english_data.as_slice());
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let allowed_english = allowed_english.records().map(Result::unwrap).map(|r| {
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let mut i = r.iter();
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let mut typo = i.next().expect("typo").to_owned();
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typo.make_ascii_lowercase();
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(typo, String::from("english word"))
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});
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let allowed_path = "assets/allowed.csv";
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let local_data = std::fs::read(allowed_path).unwrap();
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let mut allowed_local = csv::ReaderBuilder::new()
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.has_headers(false)
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.flexible(true)
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.from_reader(local_data.as_slice());
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let allowed_local = allowed_local.records().map(Result::unwrap).map(|r| {
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let mut i = r.iter();
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let mut typo = i.next().expect("typo").to_owned();
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typo.make_ascii_lowercase();
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let reason = i.next().expect("reason").to_owned();
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(typo, reason)
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});
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allowed_english.chain(allowed_local).collect()
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}
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