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#![allow(clippy::inline_always)]
use crate::simple::internal::fuzzers::rapidfuzz::{
DamerauLevenshtein,
Hamming,
Indel,
Jaro,
JaroWinkler,
LcsSeq,
Levenshtein,
Osa,
Postfix,
Prefix,
};
use crate::simple::RapidfuzzMetric;
// -----------------------------------------------------------------------------
impl<K: std::hash::Hash + Ord> crate::simple::search_index::SearchIndex<K> {
/// Scans the entire search index for the closest matching keyword using
/// the the specified string similarity metric from the
/// [rapidfuzz](https://crates.io/crates/rapidfuzz) crate.
///
/// When the user's search string contains a keyword that returns no
/// matches, this method can be used to find the best match to be used as a
/// substitution.
///
/// All keywords in the search index will potentially be examined.
///
/// # Input
///
/// * `user_keyword` · This keyword is used to search the search index.
///
/// For example, if the user provided the misspelled word `nthing`, this
/// could potentially return `nothing` as an alternative keyword if it
/// was present in the index.
///
/// Note that this method expects the input to be normalized already, i.e.
/// if the search is meant to be case-insensitive then the input should be
/// in lowercase.
///
/// # Output
///
/// This method returns the single best matching alternative keyword.
///
/// If no reasonable alternative keywords were found, a `None` will be
/// returned.
///
/// # Notes
///
/// * This method differs from `rapidfuzz_substitute_comparator` in that
/// this method will perform some common setup, and dynamically dispatch
/// to the generic method indicated by the chosen string similarity metric
/// (`DamerauLevenshtein`, `Jaro`, `Osa`, etc.)
///
/// # Basic Usage
///
/// ```ignore
/// # use indicium::simple::{AutocompleteType, Indexable, SearchIndex, SearchType};
/// # use pretty_assertions::assert_eq;
/// #
/// # struct MyStruct {
/// # title: String,
/// # year: u16,
/// # body: String,
/// # }
/// #
/// # impl Indexable for MyStruct {
/// # fn strings(&self) -> Vec<String> {
/// # vec![
/// # self.title.clone(),
/// # self.year.to_string(),
/// # self.body.clone(),
/// # ]
/// # }
/// # }
/// #
/// # let my_vec = vec![
/// # MyStruct {
/// # title: "Harold Godwinson".to_string(),
/// # year: 1066,
/// # body: "Last crowned Anglo-Saxon king of England.".to_string(),
/// # },
/// # MyStruct {
/// # title: "Edgar Ætheling".to_string(),
/// # year: 1066,
/// # body: "Last male member of the royal house of Cerdic of Wessex.".to_string(),
/// # },
/// # MyStruct {
/// # title: "William the Conqueror".to_string(),
/// # year: 1066,
/// # body: "First Norman monarch of England.".to_string(),
/// # },
/// # MyStruct {
/// # title: "William Rufus".to_string(),
/// # year: 1087,
/// # body: "Third son of William the Conqueror.".to_string(),
/// # },
/// # MyStruct {
/// # title: "Henry Beauclerc".to_string(),
/// # year: 1100,
/// # body: "Fourth son of William the Conqueror.".to_string(),
/// # },
/// # ];
/// #
/// # let mut search_index: SearchIndex<usize> = SearchIndex::default();
/// #
/// # my_vec
/// # .iter()
/// # .enumerate()
/// # .for_each(|(index, element)|
/// # search_index.insert(&index, element)
/// # );
/// #
/// #
/// let keyword_substitution = search_index.rapidfuzz_substitute("Harry");
///
/// assert_eq!(
/// keyword_substitution,
/// Some("harold")
/// );
/// ```
#[must_use]
#[inline(always)]
#[allow(clippy::option_if_let_else)]
pub(crate) fn rapidfuzz_substitute(
&self,
user_keyword: &str
) -> Option<&str> {
// If the search index is set to be case insensitive, normalize the
// keyword to lower-case:
let user_keyword = self.normalize(user_keyword);
// This call to `index_range` builds a keyword index range to fuzzy
// match against.
//
// This is used to restrict fuzzy-matching to only strings that match
// the first _n_ characters in the user's keyword. This helps reduce
// required compute.
//
// For example, if the `index_range` is "super" and the user's keyword
// is "supersonic", only index keywords beginning with "super" will be
// fuzzy compared against the user's keyword: "supersonic" against
// "superalloy", "supersonic" against "supergiant" and so on...
let best_match: Option<&str> = match self.index_range(&user_keyword) {
// Attempt to find the closest match to the user's keyword. We'll
// use the selected string similarity metric defined in the search
// index:
Some(index_range) => match self.rapidfuzz_metric.as_ref() {
Some(RapidfuzzMetric::DamerauLevenshtein) =>
self.rapidfuzz_substitute_comparator::<DamerauLevenshtein>(
&user_keyword,
&index_range,
),
Some(RapidfuzzMetric::Hamming) =>
self.rapidfuzz_substitute_comparator::<Hamming>(
&user_keyword,
&index_range,
),
Some(RapidfuzzMetric::Indel) =>
self.rapidfuzz_substitute_comparator::<Indel>(
&user_keyword,
&index_range,
),
Some(RapidfuzzMetric::Jaro) =>
self.rapidfuzz_substitute_comparator::<Jaro>(
&user_keyword,
&index_range,
),
Some(RapidfuzzMetric::JaroWinkler) =>
self.rapidfuzz_substitute_comparator::<JaroWinkler>(
&user_keyword,
&index_range,
),
Some(RapidfuzzMetric::LcsSeq) =>
self.rapidfuzz_substitute_comparator::<LcsSeq>(
&user_keyword,
&index_range,
),
Some(RapidfuzzMetric::Levenshtein) =>
self.rapidfuzz_substitute_comparator::<Levenshtein>(
&user_keyword,
&index_range,
),
Some(RapidfuzzMetric::Osa) =>
self.rapidfuzz_substitute_comparator::<Osa>(
&user_keyword,
&index_range,
),
Some(RapidfuzzMetric::Postfix) =>
self.rapidfuzz_substitute_comparator::<Postfix>(
&user_keyword,
&index_range,
),
Some(RapidfuzzMetric::Prefix) =>
self.rapidfuzz_substitute_comparator::<Prefix>(
&user_keyword,
&index_range,
),
// If no string similarity metric was defined in the search
// index, fuzzy string matching is effectively turned off.
None => None,
}, // Some(index_range)
// If a `None` is returned by `index_range` then no fuzzy-matching
// should be performed.
None => None,
}; // match
// Return the closest matching keyword to the caller:
best_match
} // fn
} // impl