weighted_trie

🦀 Rust crate that allows creating weighted prefix trees that can be used in autocomplete

Released API Docs

Quickstart

To use weigthed-trie, add the following to your Cargo.toml file:

[dependencies]
weighted_trie = "0.1.0"  # NOTE: Replace to latest minor version.

Usage overview

use weighted_trie::WeightedTrie;

fn main() {
   let mut trie = WeightedTrie::new();
    // build trie with words and assoicated weights
    trie.insert("pie".to_owned(), 5);
    trie.insert("pita".to_owned(), 2);
    trie.insert("pi".to_owned(), 1);
    trie.insert("pizza".to_owned(), 10);

    // get prefix based suggestions sorted by weight
    let suggestions = trie.search("pi");
    assert_eq!(suggestions, vec!["pizza", "pie", "pita", "pi"]);

    let suggestions = trie.search("piz");
    assert_eq!(suggestions, vec!["pizza"]);

    // out of vocabulary
    let suggestions = trie.search("apple");
    assert_eq!(suggestions.len(), 0);

}

Alternatively you can use .build method

use weighted_trie::{WeightedString, WeightedTrie};

fn main() {
    let weighted_strings = vec![
           WeightedString {
               word: "pie".to_owned(),
               weight: 5,
           },
           WeightedString {
               word: "pita".to_owned(),
               weight: 2,
           },
           WeightedString {
               word: "pi".to_owned(),
               weight: 1,
           },
           WeightedString {
               word: "pizza".to_owned(),
               weight: 10,
           },
       ];

    let trie = WeightedTrie::build(weighted_strings);

}

Benchmarks

Using 100k weighted strings

weighted_trie/insert    time:   [374.13 ms 377.97 ms 382.13 ms]
weighted_trie/lookup    time:   [709.69 µs 725.45 µs 751.34 µs]
weighted_trie/build     time:   [375.60 ms 380.36 ms 385.45 ms]

Guidelines

README.md is generated from cargo readme command. Do not manually update README.md instead edit src/lib.rs and then run cargo readme > README.md.

TODO:

1. Add tests
2. Benchmark lookup speed
3. Benchmark insert speed
4. Measure memory footprint
5. Try low hanging fruit optimizations like usage of hashbrown instead of standart HashMap

License

License: Apache-2.0