lib.rs - source
Description: Source of the Rust file `src/lib.rs`.
Keywords: rust, rustlang, rust-lang

      1
      2
      3
      4
      5
      6
      7
      8
      9
     10
     11
     12
     13
     14
     15
     16
     17
     18
     19
     20
     21
     22
     23
     24
     25
     26
     27
     28
     29
     30
     31
     32
     33
     34
     35
     36
     37
     38
     39
     40
     41
     42
     43
     44
     45
     46
     47
     48
     49
     50
     51
     52
     53
     54
     55
     56
     57
     58
     59
     60
     61
     62
     63
     64
     65
     66
     67
     68
     69
     70
     71
     72
     73
     74
     75
     76
     77
     78
     79
     80
     81
     82
     83
     84
     85
     86
     87
     88
     89
     90
     91
     92
     93
     94
     95
     96
     97
     98
     99
    100
    101
    102
    103
    104
    105
    106
    107
    108
    109
    110
    111
    112
    113
    114
    115
    116
    117
    118
    119
    120
    121
    122
    123
    124
    125
    126
    127
    128
    129
    130
    131
    132
    133
    134
    135
    136
    137
    138
    139
    140
    141
    142
    143
    144
    145
    146
    147
    148
    149
    150
    151
    152
    153
    154
    155
    156
    157
    158
    159
    160
    161
    162
    163
    164
    165
    166
    167
    168
    169
    170
    171
    172
    173
    174
    175
    176
    177
    178
    179
    180
    181
    182
    183
    184
    185
    186
    187
    188
    189
    190
    191
    192
    193
    194
    195
    196
    197
    198
    199
    200
    201
    202
    203
    204
    205
    206
    207
    208
    209
    210
    211
    212
    213
    214
    215
    216
    217
    218
    219
    220
    221
    222
    223
    224
    225
    226
    227
    228
    229
    230
    231
    232
    233
    234
    235
    236
    237
    238
    239
    240
    241
    242
    243
    244
    245
    246
    247
    248
    249
    250
    251
    252
    253
    254
    255
    256
    257
    258
    259
    260
    261
    262
    263
    264
    265
    266
    267
    268
    269
    270
    271
    272
    273
    274
    275
    276
    277
    278
    279
    280
    281
    282
    283
    284
    285
    286
    287
    288
    289
    290
    291
    292
    293
    294
    295
    296
    297
    298
    299
    300
    301
    302
    303
    304
    305
    306
    307
    308
    309
    310
    311
    312
    313
    314
    315
    316
    317
    318
    319
    320
    321
    322
    323
    324
    325
    326
    327
    328
    329
    330
    331
    332

    //#![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 then 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 4 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 : <https://dev.to/kaleman15/fuzzy-searching-with-postgresql-97o>
    //!
    //! 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
    //! ```
    //! 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)
    //!     }
    //! }
    //! ```
    //!
    //!

    use std::iter;

    #[inline]
    fn trigrams(s : &str) -> Vec<(char,char,char)> {

        let mut it_1 = iter::once(' ').chain(iter::once(' ')).chain(s.chars());
        let mut it_2 = iter::once(' ').chain(s.chars());
        let mut it_3 = s.chars().chain(iter::once(' '));
        let string_len = s.chars().count();
        let mut trigrams : Vec<(char,char,char)> = Vec::with_capacity(string_len);
        for _  in 0..string_len {
            let tup : (char, char, char) = (it_1.next().unwrap(), it_2.next().unwrap(), it_3.next().unwrap());
            trigrams.push(tup);
        }
        trigrams
    }

    /// 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 {
        /*
        //let chars_a: Vec<char> = ["1", "2", &a, "3"].join("").chars().collect();
        //let chars_b: Vec<char> = [" ", " ", &b, " "].join("").chars().collect();
        //let mut a1 = chars_a.iter();
        //let mut a2 = chars_a.iter();
        //a2.next();
        //let mut a3 = chars_a.iter();
        //a3.next();
        //a3.next();
        */

        let string_len = a.chars().count();

        let trigrams_a = trigrams(a);
        let trigrams_b = trigrams(b);

        let mut acc : f32 = 0.0f32;
        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);
        if (0.0f32..=1.0f32).contains(&res) {
            res
        }else{
            0.0f32
        }
    /*
        //for (a,b,c) in &res3 {
        //    print!("{}{}{} ",a,b,c);
        //};
        //println!("-----------------");

     */
    }

    /// 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_sorted, fuzzy_search_threshold, fuzzy_search_best_n};

        //use std::fs::File;
        #[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("", ""),0.0f32)
        }
        #[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);
        }

    }

    // (<a href="https://www.codecogs.com/eqnedit.php?latex=\frac{number&space;_&space;of&space;_&space;trigrams&space;_&space;of&space;_&space;the&space;f_&space;irst&space;_&space;words&space;_&space;that&space;_&space;are&space;_&space;also&space;_&space;present&space;_&space;on&space;_&space;the&space;_&space;second&space;_&space;word}{number&space;_&space;of&space;_&space;trigrams&space;_&space;of&space;_&space;the&space;_&space;first&space;_&space;word}" target="_blank"><img src="https://latex.codecogs.com/gif.latex?\frac{number&space;_&space;of&space;_&space;trigrams&space;_&space;of&space;_&space;the&space;f_&space;irst&space;_&space;words&space;_&space;that&space;_&space;are&space;_&space;also&space;_&space;present&space;_&space;on&space;_&space;the&space;_&space;second&space;_&space;word}{number&space;_&space;of&space;_&space;trigrams&space;_&space;of&space;_&space;the&space;_&space;first&space;_&space;word}" title="\frac{number _ of _ trigrams _ of _ the f_ irst _ words _ that _ are _ also _ present _ on _ the _ second _ word}{number _ of _ trigrams _ of _ the _ first _ word}" /></a>)