rust-fuzzy-search-0.1.1/.cargo_vcs_info.json 0000644 00000000112 00000000000 0014451 0 ustar {
"git": {
"sha1": "aa760d75df956f0c12a429be92e4350329e25246"
}
}
rust-fuzzy-search-0.1.1/.gitignore 0000644 0000000 0000000 00000000050 00000000000 0015210 0 ustar 0000000 0000000 target/*
!target/doc/
Cargo.lock
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pages:
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stage: deploy
#only:
# - master
script:
- cargo doc
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artifacts:
paths:
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rust-fuzzy-search-0.1.1/.idea/.gitignore 0000644 0000000 0000000 00000000057 00000000000 0016177 0 ustar 0000000 0000000 # Default ignored files
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rust-fuzzy-search-0.1.1/.idea/codeStyles/Project.xml 0000644 0000000 0000000 00000000407 00000000000 0020454 0 ustar 0000000 0000000 rust-fuzzy-search-0.1.1/.idea/codeStyles/codeStyleConfig.xml 0000644 0000000 0000000 00000000225 00000000000 0022125 0 ustar 0000000 0000000 rust-fuzzy-search-0.1.1/.idea/misc.xml 0000644 0000000 0000000 00000000254 00000000000 0015663 0 ustar 0000000 0000000
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rust-fuzzy-search-0.1.1/Cargo.lock 0000644 00000000241 00000000000 0012427 0 ustar # This file is automatically @generated by Cargo.
# It is not intended for manual editing.
version = 3
[[package]]
name = "rust-fuzzy-search"
version = "0.1.1"
rust-fuzzy-search-0.1.1/Cargo.toml 0000644 00000002035 00000000000 0012455 0 ustar # THIS FILE IS AUTOMATICALLY GENERATED BY CARGO
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[package]
edition = "2018"
name = "rust-fuzzy-search"
version = "0.1.1"
authors = ["EnricoCh "]
publish = true
description = "Fuzzy Search with trigrams implemented in Rust"
homepage = "https://gitlab.com/EnricoCh/rust-fuzzy-search"
documentation = "https://enricoch.gitlab.io/rust-fuzzy-search/rust_fuzzy_search/index.html"
keywords = ["fuzzy-search", "compare-strings", "fuzzy", "compare"]
license = "MIT OR Apache-2.0"
repository = "https://gitlab.com/EnricoCh/rust-fuzzy-search"
[dependencies]
rust-fuzzy-search-0.1.1/Cargo.toml.orig 0000644 00000001162 00000000000 0013414 0 ustar [package]
name = "rust-fuzzy-search"
version = "0.1.1"
authors = ["EnricoCh "]
edition = "2018"
description = "Fuzzy Search with trigrams implemented in Rust"
documentation = "https://enricoch.gitlab.io/rust-fuzzy-search/rust_fuzzy_search/index.html"
repository = "https://gitlab.com/EnricoCh/rust-fuzzy-search"
homepage = "https://gitlab.com/EnricoCh/rust-fuzzy-search"
keywords = ["fuzzy-search", "compare-strings", "fuzzy", "compare"]
publish = true
license = "MIT OR Apache-2.0"
# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
[dependencies]
rust-fuzzy-search-0.1.1/Cargo.toml.orig 0000644 0000000 0000000 00000001162 00000000000 0016114 0 ustar 0000000 0000000 [package]
name = "rust-fuzzy-search"
version = "0.1.1"
authors = ["EnricoCh "]
edition = "2018"
description = "Fuzzy Search with trigrams implemented in Rust"
documentation = "https://enricoch.gitlab.io/rust-fuzzy-search/rust_fuzzy_search/index.html"
repository = "https://gitlab.com/EnricoCh/rust-fuzzy-search"
homepage = "https://gitlab.com/EnricoCh/rust-fuzzy-search"
keywords = ["fuzzy-search", "compare-strings", "fuzzy", "compare"]
publish = true
license = "MIT OR Apache-2.0"
# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
[dependencies]
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rust-fuzzy-search-0.1.1/README.md 0000644 0000000 0000000 00000012120 00000000000 0014500 0 ustar 0000000 0000000 # Rust Fuzzy Search | [Documentation](https://enricoch.gitlab.io/rust-fuzzy-search/rust_fuzzy_search/index.html)
[](https://gitlab.com/EnricoCh/rust-fuzzy-search)
[](https://enricoch.gitlab.io/rust-fuzzy-search/rust_fuzzy_search/index.html)
[](https://gitlab.com/EnricoCh/rust-fuzzy-search/badges/master/pipeline.svg)
[](https://www.rust-lang.org/)
[](https://gitlab.com/EnricoCh/rust-fuzzy-search)
## Fuzzy search with trigrams implemented in Rust
This crate implements Fuzzy Searching with trigrams
Fuzzy searching allows to compare strings by similarity rather than by equality:\
Similar strings will get a high score (close to `1.0f32`) while dissimilar strings will get a lower score (closer to `0.0f32`).
Fuzzy searching tolerates changes in word order:\
ex. `"John Dep"` and `"Dep John"` will get a high score.
The Algorithm used is taken from :
Basic idea:
1. From both strings extracts all groups of 3 adjacent letters.\
(`"House"` becomes `[' H', ' Ho', 'Hou', 'ous', 'use', 'se ']`).\
Note the 2 spaces added to the head of the string and the one on the tail, used to make the algorithm work on zero length words.
1. Then counts the number of trigrams of the first words that are also present on the second word and divide by the number of trigrams of the first word.
Example: Comparing 2 strings
```rust
fn test () {
use rust_fuzzy_search::fuzzy_compare;
let score : f32 = fuzzy_compare("kolbasobulko", "kolbasobulko");
println!("score = {:?}", score);
}
```
Example: Comparing a string with a list of strings and retrieving only the best matches
```rust
fn test() {
use rust_fuzzy_search::fuzzy_search_best_n;
let s = "bulko";
let list : Vec<&str> = vec![
"kolbasobulko",
"sandviĉo",
"ŝatas",
"domo",
"emuo",
"fabo",
"fazano"
];
let n : usize = 3;
let res : Vec<(&str, f32)> = fuzzy_search_best_n(s,&list, n);
for (_word, score) in res {
println!("{:?}",score)
}
}
```
Example: if you have a `Vec` of `String`s you need to convert it to a list of `&str`
```rust
fn works_with_strings() {
use rust_fuzzy_search::fuzzy_search;
let s = String::from("varma");
let list: Vec = vec![String::from("varma vetero"), String::from("varma ĉokolado")];
fuzzy_search(&s, &list.iter().map(String::as_ref).collect::>());
}
```
The crate exposes 5 main functions:
- [fuzzy_compare](https://enricoch.gitlab.io/rust-fuzzy-search/rust_fuzzy_search/fn.fuzzy_compare.html) will take 2 strings and return a score representing how similar those strings are.
- [fuzzy_search](https://enricoch.gitlab.io/rust-fuzzy-search/rust_fuzzy_search/fn.fuzzy_search.html) applies [fuzzy_compare](https://enricoch.gitlab.io/rust-fuzzy-search/rust_fuzzy_search/fn.fuzzy_compare.html) to a list of strings and returns a list of tuples: (word, score).
- [fuzzy_search_sorted](https://enricoch.gitlab.io/rust-fuzzy-search/rust_fuzzy_search/fn.fuzzy_search_sorted.html) is similar to [fuzzy_search](https://enricoch.gitlab.io/rust-fuzzy-search/rust_fuzzy_search/fn.fuzzy_search.html) but orders the output in descending order.
- [fuzzy_search_threshold](https://enricoch.gitlab.io/rust-fuzzy-search/rust_fuzzy_search/fn.fuzzy_search_threshold.html) will take an additional `f32` as input and returns only tuples with score greater than the threshold.
- [fuzzy_search_best_n](https://enricoch.gitlab.io/rust-fuzzy-search/rust_fuzzy_search/fn.fuzzy_search_best_n.html) will take an additional `usize` arguments and returns the first `n` tuples.
## Usage
To use this crate, first add this to your Cargo.toml:
```toml
[dependencies]
rust-fuzzy-search = { git = "https://gitlab.com/EnricoCh/rust-fuzzy-search"}
```
Next, add this to your crate:
```rust
extern crate rust_fuzzy_search;
use rust_fuzzy_search::*;
fn main() {
// ...
}
```
## Building
To build the library use `cargo build`
## Testing
To test the library use `cargo test`
## License
Licensed under either of
- Apache License, Version 2.0 ([LICENSE-APACHE](LICENSE-APACHE) or http://apache.org/licenses/LICENSE-2.0)
- MIT license ([LICENSE-MIT](LICENSE-MIT) or http://opensource.org/licenses/MIT)
# Contribution
Unless you explicitly state otherwise, any contribution intentionally submitted
for inclusion in the work by you, as defined in the Apache-2.0 license, shall be
dual licensed as above, without any additional terms or conditions. rust-fuzzy-search-0.1.1/public/.gitkeep 0000644 0000000 0000000 00000000000 00000000000 0016122 0 ustar 0000000 0000000 rust-fuzzy-search-0.1.1/rust-fuzzy-search.iml 0000644 0000000 0000000 00000000740 00000000000 0017356 0 ustar 0000000 0000000
rust-fuzzy-search-0.1.1/src/lib.rs 0000644 0000000 0000000 00000025240 00000000000 0015133 0 ustar 0000000 0000000 #![warn(missing_docs)]
//#![doc(html_playground_url = "https://playground.example.com/")] // TODO add playground if possible
//! This crate implements Fuzzy Searching with trigrams
//!
//!
//! Fuzzy searching allows to compare strings by similarity rather than by equality:\
//! Similar strings will get a high score (close to `1.0f32`) while dissimilar strings will get a lower score (closer to `0.0f32`).
//!
//! Fuzzy searching tolerates changes in word order:\
//! ex. `"John Dep"` and `"Dep John"` will get a high score.
//!
//!
//! The crate exposes 5 main functions:
//! - [fuzzy_compare] will take 2 strings and return a score representing how similar those strings are.
//! - [fuzzy_search] applies [fuzzy_compare] to a list of strings and returns a list of tuples: (word, score).
//! - [fuzzy_search_sorted] is similar to [fuzzy_search] but orders the output in descending order.
//! - [fuzzy_search_threshold] will take an additional `f32` as input and returns only tuples with score greater than the threshold.
//! - [fuzzy_search_best_n] will take an additional `usize` arguments and returns the first `n` tuples.
//!
//! The Algorithm used is taken from :
//!
//! Basic idea:
//!
//! 1. From both strings extracts all groups of 3 adjacent letters.\
//! (`"House"` becomes `[' H', ' Ho', 'Hou', 'ous', 'use', 'se ']`).\
//! Note the 2 spaces added to the head of the string and the one on the tail, used to make the algorithm work on zero length words.
//!
//! 1. Then counts the number of trigrams of the first words that are also present on the second word and divide by the number of trigrams of the first word.\
//!
//!
//! Example: Comparing 2 strings
//! ```rust
//! fn test () {
//! use rust_fuzzy_search::fuzzy_compare;
//! let score : f32 = fuzzy_compare("kolbasobulko", "kolbasobulko");
//! println!("score = {:?}", score);
//! }
//! ```
//!
//! Example: Comparing a string with a list of strings and retrieving only the best matches
//! ```rust
//! fn test() {
//! use rust_fuzzy_search::fuzzy_search_best_n;
//! let s = "bulko";
//! let list : Vec<&str> = vec![
//! "kolbasobulko",
//! "sandviĉo",
//! "ŝatas",
//! "domo",
//! "emuo",
//! "fabo",
//! "fazano"
//! ];
//! let n : usize = 3;
//! let res : Vec<(&str, f32)> = fuzzy_search_best_n(s,&list, n);
//! for (_word, score) in res {
//! println!("{:?}",score)
//! }
//! }
//! ```
//! Example: if you have a `Vec` of `String`s you need to convert it to a list of `&str`
//! ```rust
//! fn works_with_strings() {
//! use rust_fuzzy_search::fuzzy_search;
//! let s = String::from("varma");
//! let list: Vec = vec![String::from("varma vetero"), String::from("varma ĉokolado")];
//! fuzzy_search(&s, &list.iter().map(String::as_ref).collect::>());
//! }
//! ```
//!
use std::iter;
fn trigrams(s: &str) -> Vec<(char, char, char)> {
let it_1 = iter::once(' ').chain(iter::once(' ')).chain(s.chars());
let it_2 = iter::once(' ').chain(s.chars());
let it_3 = s.chars().chain(iter::once(' '));
let res: Vec<(char, char, char)> = it_1
.zip(it_2)
.zip(it_3)
.map(|((a, b), c): ((char, char), char)| (a, b, c))
.collect();
res
}
/// Use this function to compare 2 strings.
///
/// The output is a score (between `0.0f32 and 1.0f32`) representing how similar the 2 strings are.
///
/// Arguments:
/// * `a` : the first string to compare.
/// * `b` : the second string to compare.
///
///
/// example:
/// ```rust
/// fn test () {
/// use rust_fuzzy_search::fuzzy_compare;
/// let score : f32 = fuzzy_compare("kolbasobulko", "kolbasobulko");
/// println!("score = {:?}", score);
/// }
/// ```
pub fn fuzzy_compare(a: &str, b: &str) -> f32 {
// gets length of first input string plus 1 (because of the 3 added spaces (' '))
let string_len = a.chars().count() + 1;
// gets the trigrams for both strings
let trigrams_a = trigrams(a);
let trigrams_b = trigrams(b);
// accumulator
let mut acc: f32 = 0.0f32;
// counts the number of trigrams of the first string that are also present in the second one
for t_a in &trigrams_a {
for t_b in &trigrams_b {
if t_a == t_b {
acc += 1.0f32;
break;
}
}
}
let res = acc / (string_len as f32);
// crops between zero and one
if (0.0f32..=1.0f32).contains(&res) {
res
} else {
0.0f32
}
}
/// Use this function to compare a string (`&str`) with all elements of a list.
///
///
/// The result is a list whose elements are tuples of the form `(string, score)`, the first element being the word of the list and the second element the score.
///
/// Arguments:
/// * `s` : the string to compare.
/// * `list` : the list of strings to compare with `s`.
///
/// example:
/// ```rust
/// fn test() {
/// use rust_fuzzy_search::fuzzy_search;
/// let s = "bulko";
/// let list : Vec<&str> = vec!["kolbasobulko", "sandviĉo"];
/// let res : Vec<(&str, f32)> = fuzzy_search(s,&list);
/// for (_word, score) in res {
/// println!("{:?}",score)
/// }
/// }
/// ```
///
///
pub fn fuzzy_search<'a>(s: &'a str, list: &'a [&str]) -> Vec<(&'a str, f32)> {
list.iter()
.map(|&value| {
let res = fuzzy_compare(s, value);
(value, res)
})
.collect()
}
/// This function is similar to [fuzzy_search] but sorts the result in descending order (the best matches are placed at the beginning).
///
/// Arguments:
/// * `s` : the string to compare.
/// * `list` : the list of strings to compare with `s`.
///
/// example:
/// ```rust
/// fn test() {
/// use rust_fuzzy_search::fuzzy_search_sorted;
/// let s = "bulko";
/// let list : Vec<&str> = vec!["kolbasobulko", "sandviĉo"];
/// let res : Vec<(&str, f32)> = fuzzy_search_sorted(s,&list);
/// for (_word, score) in res {
/// println!("{:?}",score)
/// }
/// }
/// ```
///
pub fn fuzzy_search_sorted<'a>(s: &'a str, list: &'a [&str]) -> Vec<(&'a str, f32)> {
let mut res = fuzzy_search(s, list);
res.sort_by(|(_, d1), (_, d2)| d2.partial_cmp(d1).unwrap()); // TODO to fix the unwrap call
res
}
/// This function is similar to [fuzzy_search] but filters out element with a score lower than the specified one.
///
/// Arguments:
/// * `s` : the string to compare.
/// * `list` : the list of strings to compare with `s`.
/// * `threshold` : the minimum allowed score for the elements in the result: elements with lower score will be removed.
///
/// ```rust
/// fn test() {
/// use rust_fuzzy_search::fuzzy_search_threshold;
/// let s = "bulko";
/// let list : Vec<&str> = vec!["kolbasobulko", "sandviĉo"];
/// let threshold : f32 = 0.4f32;
/// let res : Vec<(&str, f32)> = fuzzy_search_threshold(s,&list, threshold);
/// for (_word, score) in res {
/// println!("{:?}",score)
/// }
/// }
/// ```
pub fn fuzzy_search_threshold<'a>(
s: &'a str,
list: &'a [&str],
threshold: f32,
) -> Vec<(&'a str, f32)> {
fuzzy_search(s, list)
.into_iter()
.filter(|&(_, score)| score >= threshold)
.collect()
}
/// This function is similar to [fuzzy_search_sorted] but keeps only the `n` best items, those with a better match.
///
/// Arguments :
/// * `s` : the string to compare.
/// * `list` : the list of strings to compare with `s`.
/// * `n` : the number of element to retrieve.
///
/// example:
/// ```
/// fn test() {
/// use rust_fuzzy_search::fuzzy_search_best_n;
/// let s = "bulko";
/// let list : Vec<&str> = vec!["kolbasobulko", "sandviĉo"];
/// let n : usize = 1;
/// let res : Vec<(&str, f32)> = fuzzy_search_best_n(s,&list, n);
/// for (_word, score) in res {
/// println!("{:?}",score)
/// }
/// }
/// ```
///
pub fn fuzzy_search_best_n<'a>(s: &'a str, list: &'a [&str], n: usize) -> Vec<(&'a str, f32)> {
fuzzy_search_sorted(s, list).into_iter().take(n).collect()
}
#[cfg(test)]
mod tests {
use crate::{
fuzzy_compare, fuzzy_search, fuzzy_search_best_n, fuzzy_search_sorted,
fuzzy_search_threshold,
};
#[test]
fn perfect_match_1() {
assert_eq!(fuzzy_compare("kolbasobulko", "kolbasobulko"), 1.0f32)
}
#[test]
fn perfect_match_2() {
assert_eq!(fuzzy_compare("sandviĉo", "sandviĉo"), 1.0f32)
}
#[test]
fn perfect_match_3() {
assert_eq!(fuzzy_compare("domo", "domo"), 1.0f32)
}
#[test]
fn perfect_match_4() {
assert_eq!(fuzzy_compare("ŝatas", "ŝatas"), 1.0f32)
}
#[test]
fn perfect_match_5() {
assert_eq!(fuzzy_compare("mirinda estonto", "mirinda estonto"), 1.0f32)
}
#[test]
fn no_match() {
assert_eq!(fuzzy_compare("abc", "def"), 0.0f32)
}
#[test]
fn empty_word() {
assert_eq!(fuzzy_compare("", ""), 1.0f32)
}
#[test]
fn one_letter() {
assert_eq!(fuzzy_compare("a", "a"), 1.0f32)
}
#[test]
fn utf8_one_letter_1() {
assert_eq!(fuzzy_compare("ĉ", "ĉ"), 1.0f32)
}
#[test]
fn utf8_one_letter_2() {
assert_eq!(fuzzy_compare("ł", "ł"), 1.0f32)
}
#[test]
fn utf8_no_match() {
assert_eq!(fuzzy_compare("cgs", "ĉĝŝ"), 0.0f32)
}
#[test]
fn test_fuzzy_search_1() {
let s: &str = "bulko";
let list: Vec<&str> = vec!["kolbasobulko", "sandviĉo", "kolbasobulkejo"];
let res: Vec<(&str, f32)> = fuzzy_search(s, &list);
assert_eq!(res.into_iter().count(), 3);
}
#[test]
fn test_fuzzy_search_sorted() {
let s: &str = "bulko";
let list: Vec<&str> = vec!["kolbasobulko", "sandviĉo", "kolbasobulkejo"];
let res: Vec<(&str, f32)> = fuzzy_search_sorted(s, &list);
assert_eq!(res.into_iter().count(), 3);
}
#[test]
fn no_lowers() {
let threshold = 0.5f32;
let s: &str = "bulko";
let list: Vec<&str> = vec!["kolbasobulko", "sandviĉo", "kolbasobulkejo"];
for (_word, score) in fuzzy_search_threshold(s, &list, threshold) {
assert!(score > threshold)
}
}
#[test]
fn test_fuzzy_search_best_n() {
let s: &str = "bulko";
let list: Vec<&str> = vec!["kolbasobulko", "sandviĉo", "kolbasobulkejo"];
let res: Vec<(&str, f32)> = fuzzy_search_best_n(s, &list, 2);
assert_eq!(res.into_iter().count(), 2);
}
#[test]
fn works_with_strings() {
let s = String::from("varma");
let list: Vec = vec![String::from("varma vetero"), String::from("varma ĉokolado")];
fuzzy_search(&s, &list.iter().map(String::as_ref).collect::>());
}
} rust-fuzzy-search-0.1.1/src/main.rs 0000644 0000000 0000000 00000004471 00000000000 0015314 0 ustar 0000000 0000000 use rust_fuzzy_search::*;
fn main() {
fuzzy_compare("kolbaso", "kolbasobulko");
}
#[allow(dead_code)]
fn simple_search() {
let s = "bulko";
let list: Vec<&str> = vec!["kolbasobulko", "sandviĉo"];
let res = fuzzy_search(&s, &list);
for x in res {
println!("{:?}", x)
}
}
#[allow(dead_code)]
fn search_through_file() {
use std::fs::File;
use std::io::Read;
// string to search in the file
let input = "colos";
// filename
let filename = "src/example_file.txt";
// creates a buffer and reads the file
let mut buffer = String::new();
File::open(filename)
.unwrap()
.read_to_string(&mut buffer)
.unwrap();
// split the string in the buffer in words
let dict: Vec<&str> = buffer.split(' ').collect();
// gets the n (10usize) best matches
let ress = fuzzy_search_best_n(&input, &dict, 10usize);
// prints all the matches
for (x, d) in ress {
println!("word : {:?} \t\t\t\t score : {:?}", x, d);
}
}
#[allow(dead_code)]
fn repl_compare() {
use std::io;
loop {
println!("write 2 lines:");
// creates 2 buffers to read from stdin
let mut buffer1 = String::new();
let mut buffer2 = String::new();
// reads 2 lines from stdin
io::stdin().read_line(&mut buffer1).unwrap();
io::stdin().read_line(&mut buffer2).unwrap();
// test quit instruction (user typed something similar to "quit")
if fuzzy_compare(&buffer1, &"quit") > 0.9 {
println!("quit : quitting");
break;
}
// compares strings and prints the score
let distance = fuzzy_compare(&buffer1, &buffer2);
println!("distance is {:?}", distance);
}
}
#[allow(dead_code)]
fn simple_searches() {
println!(
"bulubulu - bulubulu : {:?}",
fuzzy_compare(&"bulubulu".to_string(), &"bulubulu".to_string())
);
println!(
"sandviĉo - sandviĉo : {:?}",
fuzzy_compare(&"sandviĉo".to_string(), &"sandviĉo".to_string())
);
println!(
"sandviĉo - kolbasobulko : {:?}",
fuzzy_compare(&"sandviĉo".to_string(), &"kolbasobulko".to_string())
);
println!(
"varma vetero - vetero : {:?}",
fuzzy_compare(&"varma vetero".to_string(), &"vetero".to_string())
);
}
](https://gitlab.com/EnricoCh/rust-fuzzy-search)
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