Make public API, docs algorithm-agnostic
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16 changed files with 81 additions and 73 deletions
229
compiler/rustc_span/src/edit_distance.rs
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229
compiler/rustc_span/src/edit_distance.rs
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//! Edit distances.
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//!
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//! The [edit distance] is a metric for measuring the difference between two strings.
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//!
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//! [edit distance]: https://en.wikipedia.org/wiki/Edit_distance
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// The current implementation is the restricted Damerau-Levenshtein algorithm. It is restricted
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// because it does not permit modifying characters that have already been transposed. The specific
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// algorithm should not matter to the caller of the methods, which is why it is not noted in the
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// documentation.
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use crate::symbol::Symbol;
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use std::{cmp, mem};
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#[cfg(test)]
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mod tests;
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/// Finds the [edit distance] between two strings.
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///
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/// Returns `None` if the distance exceeds the limit.
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///
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/// [edit distance]: https://en.wikipedia.org/wiki/Edit_distance
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pub fn edit_distance(a: &str, b: &str, limit: usize) -> Option<usize> {
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let mut a = &a.chars().collect::<Vec<_>>()[..];
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let mut b = &b.chars().collect::<Vec<_>>()[..];
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// Ensure that `b` is the shorter string, minimizing memory use.
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if a.len() < b.len() {
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mem::swap(&mut a, &mut b);
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}
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let min_dist = a.len() - b.len();
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// If we know the limit will be exceeded, we can return early.
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if min_dist > limit {
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return None;
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}
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// Strip common prefix.
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while let Some(((b_char, b_rest), (a_char, a_rest))) = b.split_first().zip(a.split_first())
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&& a_char == b_char
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{
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a = a_rest;
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b = b_rest;
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}
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// Strip common suffix.
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while let Some(((b_char, b_rest), (a_char, a_rest))) = b.split_last().zip(a.split_last())
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&& a_char == b_char
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{
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a = a_rest;
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b = b_rest;
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}
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// If either string is empty, the distance is the length of the other.
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// We know that `b` is the shorter string, so we don't need to check `a`.
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if b.len() == 0 {
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return Some(min_dist);
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}
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let mut prev_prev = vec![usize::MAX; b.len() + 1];
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let mut prev = (0..=b.len()).collect::<Vec<_>>();
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let mut current = vec![0; b.len() + 1];
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// row by row
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for i in 1..=a.len() {
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current[0] = i;
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let a_idx = i - 1;
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// column by column
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for j in 1..=b.len() {
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let b_idx = j - 1;
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// There is no cost to substitute a character with itself.
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let substitution_cost = if a[a_idx] == b[b_idx] { 0 } else { 1 };
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current[j] = cmp::min(
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// deletion
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prev[j] + 1,
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cmp::min(
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// insertion
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current[j - 1] + 1,
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// substitution
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prev[j - 1] + substitution_cost,
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),
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);
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if (i > 1) && (j > 1) && (a[a_idx] == b[b_idx - 1]) && (a[a_idx - 1] == b[b_idx]) {
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// transposition
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current[j] = cmp::min(current[j], prev_prev[j - 2] + 1);
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}
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}
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// Rotate the buffers, reusing the memory.
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[prev_prev, prev, current] = [prev, current, prev_prev];
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}
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// `prev` because we already rotated the buffers.
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let distance = prev[b.len()];
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(distance <= limit).then_some(distance)
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}
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/// Provides a word similarity score between two words that accounts for substrings being more
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/// meaningful than a typical edit distance. The lower the score, the closer the match. 0 is an
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/// identical match.
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///
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/// Uses the edit distance between the two strings and removes the cost of the length difference.
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/// If this is 0 then it is either a substring match or a full word match, in the substring match
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/// case we detect this and return `1`. To prevent finding meaningless substrings, eg. "in" in
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/// "shrink", we only perform this subtraction of length difference if one of the words is not
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/// greater than twice the length of the other. For cases where the words are close in size but not
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/// an exact substring then the cost of the length difference is discounted by half.
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///
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/// Returns `None` if the distance exceeds the limit.
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pub fn edit_distance_with_substrings(a: &str, b: &str, limit: usize) -> Option<usize> {
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let n = a.chars().count();
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let m = b.chars().count();
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// Check one isn't less than half the length of the other. If this is true then there is a
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// big difference in length.
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let big_len_diff = (n * 2) < m || (m * 2) < n;
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let len_diff = if n < m { m - n } else { n - m };
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let distance = edit_distance(a, b, limit + len_diff)?;
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// This is the crux, subtracting length difference means exact substring matches will now be 0
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let score = distance - len_diff;
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// If the score is 0 but the words have different lengths then it's a substring match not a full
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// word match
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let score = if score == 0 && len_diff > 0 && !big_len_diff {
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1 // Exact substring match, but not a total word match so return non-zero
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} else if !big_len_diff {
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// Not a big difference in length, discount cost of length difference
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score + (len_diff + 1) / 2
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} else {
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// A big difference in length, add back the difference in length to the score
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score + len_diff
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};
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(score <= limit).then_some(score)
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}
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/// Finds the best match for given word in the given iterator where substrings are meaningful.
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///
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/// A version of [`find_best_match_for_name`] that uses [`edit_distance_with_substrings`] as the
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/// score for word similarity. This takes an optional distance limit which defaults to one-third of
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/// the given word.
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///
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/// We use case insensitive comparison to improve accuracy on an edge case with a lower(upper)case
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/// letters mismatch.
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pub fn find_best_match_for_name_with_substrings(
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candidates: &[Symbol],
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lookup: Symbol,
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dist: Option<usize>,
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) -> Option<Symbol> {
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find_best_match_for_name_impl(true, candidates, lookup, dist)
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}
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/// Finds the best match for a given word in the given iterator.
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///
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/// As a loose rule to avoid the obviously incorrect suggestions, it takes
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/// an optional limit for the maximum allowable edit distance, which defaults
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/// to one-third of the given word.
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///
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/// We use case insensitive comparison to improve accuracy on an edge case with a lower(upper)case
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/// letters mismatch.
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pub fn find_best_match_for_name(
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candidates: &[Symbol],
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lookup: Symbol,
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dist: Option<usize>,
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) -> Option<Symbol> {
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find_best_match_for_name_impl(false, candidates, lookup, dist)
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}
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#[cold]
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fn find_best_match_for_name_impl(
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use_substring_score: bool,
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candidates: &[Symbol],
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lookup: Symbol,
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dist: Option<usize>,
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) -> Option<Symbol> {
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let lookup = lookup.as_str();
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let lookup_uppercase = lookup.to_uppercase();
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// Priority of matches:
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// 1. Exact case insensitive match
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// 2. Edit distance match
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// 3. Sorted word match
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if let Some(c) = candidates.iter().find(|c| c.as_str().to_uppercase() == lookup_uppercase) {
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return Some(*c);
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}
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let mut dist = dist.unwrap_or_else(|| cmp::max(lookup.len(), 3) / 3);
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let mut best = None;
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for c in candidates {
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match if use_substring_score {
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edit_distance_with_substrings(lookup, c.as_str(), dist)
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} else {
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edit_distance(lookup, c.as_str(), dist)
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} {
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Some(0) => return Some(*c),
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Some(d) => {
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dist = d - 1;
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best = Some(*c);
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}
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None => {}
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}
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}
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if best.is_some() {
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return best;
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}
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find_match_by_sorted_words(candidates, lookup)
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}
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fn find_match_by_sorted_words(iter_names: &[Symbol], lookup: &str) -> Option<Symbol> {
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iter_names.iter().fold(None, |result, candidate| {
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if sort_by_words(candidate.as_str()) == sort_by_words(lookup) {
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Some(*candidate)
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} else {
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result
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}
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})
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}
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fn sort_by_words(name: &str) -> String {
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let mut split_words: Vec<&str> = name.split('_').collect();
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// We are sorting primitive &strs and can use unstable sort here.
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split_words.sort_unstable();
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split_words.join("_")
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}
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