Files
rlevtree/examples/benchmark.rs
2023-12-18 11:40:03 +08:00

60 lines
1.4 KiB
Rust

extern crate levtree;
use levtree::CaseSensitiveKeyChecker;
use levtree::CaseSensitiveLevTrie;
use levtree::DamerauLevenshteinDistanceCalculator;
use levtree::LevTrie;
use levtree::Trie;
use std::io::BufRead;
use std::io::BufReader;
trait IntoCharSlice {
fn into_char_slice(&self) -> Vec<char>;
}
impl IntoCharSlice for str {
fn into_char_slice(&self) -> Vec<char> {
self.chars().into_iter().collect::<Vec<_>>()
}
}
fn main() {
let bytes = include_bytes!("cracklib-small");
let reader = BufReader::new(&bytes[..]);
let mut trie: CaseSensitiveLevTrie = LevTrie::new();
reader
.lines()
.map(|line| line.unwrap())
.for_each(|word: String| {
trie.add(word.chars());
});
let keys = [
"camel",
"coriolis",
"mattel",
"cruzer",
"cpoper",
"roublesoot",
];
for _ in 0..50 {
for key in keys {
let word = &key.into_char_slice()[..];
trie.fuzzy_search::<DamerauLevenshteinDistanceCalculator>(word, 6);
}
}
for key in keys {
let word = &key.into_char_slice()[..];
let results = trie.fuzzy_search::<DamerauLevenshteinDistanceCalculator>(word, 6);
for result in results {
let word: String = trie.lineal_descendant(result.word).into_iter().collect();
println!("distance: {}, wordkey: {}", result.distance, word);
}
println!("")
}
}