51 lines
1.3 KiB
Rust
51 lines
1.3 KiB
Rust
|
use itertools::Itertools;
|
||
|
|
use std::collections::HashMap;
|
||
|
|
|
||
|
|
fn levenshtein_distance(s1: &str, s2: &str) -> usize {
|
||
|
|
let mut column = (0..=s1.len()).collect_vec();
|
||
|
|
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<'a, I>(prefix: &str, options: I, input: &str) -> Option<String>
|
||
|
|
where
|
||
|
|
I: Iterator<Item = &'a str>,
|
||
|
|
{
|
||
|
|
let mut selected = Vec::new();
|
||
|
|
let mut distances = HashMap::new();
|
||
|
|
|
||
|
|
for opt in options {
|
||
|
|
let distance = levenshtein_distance(input, opt);
|
||
|
|
let threshold = (input.len() / 2).max((opt.len() / 2).max(1));
|
||
|
|
if distance < threshold {
|
||
|
|
selected.push(opt);
|
||
|
|
distances.insert(opt, distance);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
if selected.is_empty() {
|
||
|
|
return None;
|
||
|
|
}
|
||
|
|
selected.sort_by(|a, b| distances[a].cmp(&distances[b]));
|
||
|
|
|
||
|
|
Some(format!(
|
||
|
|
"{} {}?",
|
||
|
|
prefix,
|
||
|
|
selected
|
||
|
|
.into_iter()
|
||
|
|
.map(|s| format!("\"{}\"", s))
|
||
|
|
.join(", ")
|
||
|
|
))
|
||
|
|
}
|