60 lines
1.6 KiB
Rust
60 lines
1.6 KiB
Rust
use std::collections::HashMap;
|
|
use std::fmt::Write;
|
|
|
|
fn levenshtein_distance(s1: &str, s2: &str) -> usize {
|
|
let mut column: Vec<_> = (0..=s1.len()).collect();
|
|
for (x, rx) in s2.bytes().enumerate() {
|
|
column[0] = x + 1;
|
|
let mut lastdiag = x;
|
|
for (y, ry) in s1.bytes().enumerate() {
|
|
let olddiag = column[y + 1];
|
|
if rx != ry {
|
|
lastdiag += 1;
|
|
}
|
|
column[y + 1] = (column[y + 1] + 1).min((column[y] + 1).min(lastdiag));
|
|
lastdiag = olddiag;
|
|
}
|
|
}
|
|
column[s1.len()]
|
|
}
|
|
|
|
pub fn make_suggestion<I, A>(prefix: &str, options: I, input: &str) -> Option<String>
|
|
where
|
|
I: IntoIterator<Item = A>,
|
|
A: AsRef<str>,
|
|
{
|
|
let mut selected = Vec::new();
|
|
let mut distances = HashMap::new();
|
|
|
|
for opt in options {
|
|
let opt = opt.as_ref().to_string();
|
|
let distance = levenshtein_distance(input, &opt);
|
|
let threshold = (input.len() / 2).max((opt.len() / 2).max(1));
|
|
if distance < threshold {
|
|
selected.push(opt.clone());
|
|
distances.insert(opt, distance);
|
|
}
|
|
}
|
|
|
|
if selected.is_empty() {
|
|
return None;
|
|
}
|
|
selected.sort_by(|a, b| distances[a].cmp(&distances[b]));
|
|
|
|
let mut suggestion =
|
|
String::with_capacity(prefix.len() + selected.iter().map(|s| s.len() + 5).sum::<usize>());
|
|
suggestion.push_str(prefix);
|
|
suggestion.push(' ');
|
|
|
|
for (i, s) in selected.iter().enumerate() {
|
|
if i != 0 {
|
|
suggestion.push_str(", ");
|
|
}
|
|
write!(suggestion, "\"{}\"", s).unwrap();
|
|
}
|
|
|
|
suggestion.push('?');
|
|
|
|
Some(suggestion)
|
|
}
|