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 </pre><pre class="rust"><code><span class="kw">use </span>std::collections::HashMap;
 <span class="kw">use </span>std::ops::Range;

 <span class="kw">use </span>levenshtein_automata::{Distance, LevenshteinAutomatonBuilder, DFA};
 <span class="kw">use </span>once_cell::sync::Lazy;
 <span class="kw">use </span>tantivy_fst::Automaton;

 <span class="kw">use </span><span class="kw">crate</span>::query::{AutomatonWeight, EnableScoring, Query, Weight};
 <span class="kw">use </span><span class="kw">crate</span>::schema::Term;
 <span class="kw">use </span><span class="kw">crate</span>::TantivyError::InvalidArgument;

 <span class="kw">pub</span>(<span class="kw">crate</span>) <span class="kw">struct </span>DfaWrapper(<span class="kw">pub </span>DFA);

 <span class="kw">impl </span>Automaton <span class="kw">for </span>DfaWrapper {
     <span class="kw">type </span>State = u32;

     <span class="kw">fn </span>start(<span class="kw-2">&amp;</span><span class="self">self</span>) -&gt; <span class="self">Self</span>::State {
         <span class="self">self</span>.<span class="number">0</span>.initial_state()
     }

     <span class="kw">fn </span>is_match(<span class="kw-2">&amp;</span><span class="self">self</span>, state: <span class="kw-2">&amp;</span><span class="self">Self</span>::State) -&gt; bool {
         <span class="kw">match </span><span class="self">self</span>.<span class="number">0</span>.distance(<span class="kw-2">*</span>state) {
             Distance::Exact(<span class="kw">_</span>) =&gt; <span class="bool-val">true</span>,
             Distance::AtLeast(<span class="kw">_</span>) =&gt; <span class="bool-val">false</span>,
         }
     }

     <span class="kw">fn </span>can_match(<span class="kw-2">&amp;</span><span class="self">self</span>, state: <span class="kw-2">&amp;</span>u32) -&gt; bool {
         <span class="kw-2">*</span>state != levenshtein_automata::SINK_STATE
     }

     <span class="kw">fn </span>accept(<span class="kw-2">&amp;</span><span class="self">self</span>, state: <span class="kw-2">&amp;</span><span class="self">Self</span>::State, byte: u8) -&gt; <span class="self">Self</span>::State {
         <span class="self">self</span>.<span class="number">0</span>.transition(<span class="kw-2">*</span>state, byte)
     }
 }

 <span class="doccomment">/// A range of Levenshtein distances that we will build DFAs for our terms
 /// The computation is exponential, so best keep it to low single digits
 </span><span class="kw">const </span>VALID_LEVENSHTEIN_DISTANCE_RANGE: Range&lt;u8&gt; = <span class="number">0</span>..<span class="number">3</span>;

 <span class="kw">static </span>LEV_BUILDER: Lazy&lt;HashMap&lt;(u8, bool), LevenshteinAutomatonBuilder&gt;&gt; = Lazy::new(|| {
     <span class="kw">let </span><span class="kw-2">mut </span>lev_builder_cache = HashMap::new();
     <span class="comment">// TODO make population lazy on a `(distance, val)` basis
     </span><span class="kw">for </span>distance <span class="kw">in </span>VALID_LEVENSHTEIN_DISTANCE_RANGE {
         <span class="kw">for </span><span class="kw-2">&amp;</span>transposition <span class="kw">in </span><span class="kw-2">&amp;</span>[<span class="bool-val">false</span>, <span class="bool-val">true</span>] {
             <span class="kw">let </span>lev_automaton_builder = LevenshteinAutomatonBuilder::new(distance, transposition);
             lev_builder_cache.insert((distance, transposition), lev_automaton_builder);
         }
     }
     lev_builder_cache
 });

 <span class="doccomment">/// A Fuzzy Query matches all of the documents
 /// containing a specific term that is within
 /// Levenshtein distance
 /// ```rust
 /// use tantivy::collector::{Count, TopDocs};
 /// use tantivy::query::FuzzyTermQuery;
 /// use tantivy::schema::{Schema, TEXT};
 /// use tantivy::{doc, Index, Term};
 ///
 /// fn example() -&gt; tantivy::Result&lt;()&gt; {
 ///     let mut schema_builder = Schema::builder();
 ///     let title = schema_builder.add_text_field(&quot;title&quot;, TEXT);
 ///     let schema = schema_builder.build();
 ///     let index = Index::create_in_ram(schema);
 ///     {
 ///         let mut index_writer = index.writer(3_000_000)?;
 ///         index_writer.add_document(doc!(
 ///             title =&gt; &quot;The Name of the Wind&quot;,
 ///         ))?;
 ///         index_writer.add_document(doc!(
 ///             title =&gt; &quot;The Diary of Muadib&quot;,
 ///         ))?;
 ///         index_writer.add_document(doc!(
 ///             title =&gt; &quot;A Dairy Cow&quot;,
 ///         ))?;
 ///         index_writer.add_document(doc!(
 ///             title =&gt; &quot;The Diary of a Young Girl&quot;,
 ///         ))?;
 ///         index_writer.commit()?;
 ///     }
 ///     let reader = index.reader()?;
 ///     let searcher = reader.searcher();
 ///
 ///     {
 ///         let term = Term::from_field_text(title, &quot;Diary&quot;);
 ///         let query = FuzzyTermQuery::new(term, 1, true);
 ///         let (top_docs, count) = searcher.search(&amp;query, &amp;(TopDocs::with_limit(2), Count)).unwrap();
 ///         assert_eq!(count, 2);
 ///         assert_eq!(top_docs.len(), 2);
 ///     }
 ///
 ///     Ok(())
 /// }
 /// # assert!(example().is_ok());
 /// ```
 </span><span class="attribute">#[derive(Debug, Clone)]
 </span><span class="kw">pub struct </span>FuzzyTermQuery {
     <span class="doccomment">/// What term are we searching
     </span>term: Term,
     <span class="doccomment">/// How many changes are we going to allow
     </span>distance: u8,
     <span class="doccomment">/// Should a transposition cost 1 or 2?
     </span>transposition_cost_one: bool,
     <span class="doccomment">///
     </span>prefix: bool,
 }

 <span class="kw">impl </span>FuzzyTermQuery {
     <span class="doccomment">/// Creates a new Fuzzy Query
     </span><span class="kw">pub fn </span>new(term: Term, distance: u8, transposition_cost_one: bool) -&gt; FuzzyTermQuery {
         FuzzyTermQuery {
             term,
             distance,
             transposition_cost_one,
             prefix: <span class="bool-val">false</span>,
         }
     }

     <span class="doccomment">/// Creates a new Fuzzy Query of the Term prefix
     </span><span class="kw">pub fn </span>new_prefix(term: Term, distance: u8, transposition_cost_one: bool) -&gt; FuzzyTermQuery {
         FuzzyTermQuery {
             term,
             distance,
             transposition_cost_one,
             prefix: <span class="bool-val">true</span>,
         }
     }

     <span class="kw">fn </span>specialized_weight(<span class="kw-2">&amp;</span><span class="self">self</span>) -&gt; <span class="kw">crate</span>::Result&lt;AutomatonWeight&lt;DfaWrapper&gt;&gt; {
         <span class="comment">// LEV_BUILDER is a HashMap, whose `get` method returns an Option
         </span><span class="kw">match </span>LEV_BUILDER.get(<span class="kw-2">&amp;</span>(<span class="self">self</span>.distance, <span class="self">self</span>.transposition_cost_one)) {
             <span class="comment">// Unwrap the option and build the Ok(AutomatonWeight)
             </span><span class="prelude-val">Some</span>(automaton_builder) =&gt; {
                 <span class="kw">let </span>term_text = <span class="self">self</span>.term.as_str().ok_or_else(|| {
                     <span class="kw">crate</span>::TantivyError::InvalidArgument(
                         <span class="string">&quot;The fuzzy term query requires a string term.&quot;</span>.to_string(),
                     )
                 })<span class="question-mark">?</span>;
                 <span class="kw">let </span>automaton = <span class="kw">if </span><span class="self">self</span>.prefix {
                     automaton_builder.build_prefix_dfa(term_text)
                 } <span class="kw">else </span>{
                     automaton_builder.build_dfa(term_text)
                 };
                 <span class="prelude-val">Ok</span>(AutomatonWeight::new(
                     <span class="self">self</span>.term.field(),
                     DfaWrapper(automaton),
                 ))
             }
             <span class="prelude-val">None </span>=&gt; <span class="prelude-val">Err</span>(InvalidArgument(<span class="macro">format!</span>(
                 <span class="string">&quot;Levenshtein distance of {} is not allowed. Choose a value in the {:?} range&quot;</span>,
                 <span class="self">self</span>.distance, VALID_LEVENSHTEIN_DISTANCE_RANGE
             ))),
         }
     }
 }

 <span class="kw">impl </span>Query <span class="kw">for </span>FuzzyTermQuery {
     <span class="kw">fn </span>weight(<span class="kw-2">&amp;</span><span class="self">self</span>, _enable_scoring: EnableScoring&lt;<span class="lifetime">&#39;_</span>&gt;) -&gt; <span class="kw">crate</span>::Result&lt;Box&lt;<span class="kw">dyn </span>Weight&gt;&gt; {
         <span class="prelude-val">Ok</span>(Box::new(<span class="self">self</span>.specialized_weight()<span class="question-mark">?</span>))
     }
 }

 <span class="attribute">#[cfg(test)]
 </span><span class="kw">mod </span>test {
     <span class="kw">use </span><span class="kw">super</span>::FuzzyTermQuery;
     <span class="kw">use </span><span class="kw">crate</span>::collector::{Count, TopDocs};
     <span class="kw">use </span><span class="kw">crate</span>::schema::{Schema, TEXT};
     <span class="kw">use crate</span>::{assert_nearly_equals, Index, Term};

     <span class="attribute">#[test]
     </span><span class="kw">pub fn </span>test_fuzzy_term() -&gt; <span class="kw">crate</span>::Result&lt;()&gt; {
         <span class="kw">let </span><span class="kw-2">mut </span>schema_builder = Schema::builder();
         <span class="kw">let </span>country_field = schema_builder.add_text_field(<span class="string">&quot;country&quot;</span>, TEXT);
         <span class="kw">let </span>schema = schema_builder.build();
         <span class="kw">let </span>index = Index::create_in_ram(schema);
         {
             <span class="kw">let </span><span class="kw-2">mut </span>index_writer = index.writer_for_tests()<span class="question-mark">?</span>;
             index_writer.add_document(<span class="macro">doc!</span>(
                 country_field =&gt; <span class="string">&quot;japan&quot;</span>,
             ))<span class="question-mark">?</span>;
             index_writer.add_document(<span class="macro">doc!</span>(
                 country_field =&gt; <span class="string">&quot;korea&quot;</span>,
             ))<span class="question-mark">?</span>;
             index_writer.commit()<span class="question-mark">?</span>;
         }
         <span class="kw">let </span>reader = index.reader()<span class="question-mark">?</span>;
         <span class="kw">let </span>searcher = reader.searcher();

         <span class="comment">// passes because Levenshtein distance is 1 (substitute &#39;o&#39; with &#39;a&#39;)
         </span>{
             <span class="kw">let </span>term = Term::from_field_text(country_field, <span class="string">&quot;japon&quot;</span>);
             <span class="kw">let </span>fuzzy_query = FuzzyTermQuery::new(term, <span class="number">1</span>, <span class="bool-val">true</span>);
             <span class="kw">let </span>top_docs = searcher.search(<span class="kw-2">&amp;</span>fuzzy_query, <span class="kw-2">&amp;</span>TopDocs::with_limit(<span class="number">2</span>))<span class="question-mark">?</span>;
             <span class="macro">assert_eq!</span>(top_docs.len(), <span class="number">1</span>, <span class="string">&quot;Expected only 1 document&quot;</span>);
             <span class="kw">let </span>(score, <span class="kw">_</span>) = top_docs[<span class="number">0</span>];
             <span class="macro">assert_nearly_equals!</span>(<span class="number">1.0</span>, score);
         }

         <span class="comment">// fails because non-prefix Levenshtein distance is more than 1 (add &#39;a&#39; and &#39;n&#39;)
         </span>{
             <span class="kw">let </span>term = Term::from_field_text(country_field, <span class="string">&quot;jap&quot;</span>);

             <span class="kw">let </span>fuzzy_query = FuzzyTermQuery::new(term, <span class="number">1</span>, <span class="bool-val">true</span>);
             <span class="kw">let </span>top_docs = searcher.search(<span class="kw-2">&amp;</span>fuzzy_query, <span class="kw-2">&amp;</span>TopDocs::with_limit(<span class="number">2</span>))<span class="question-mark">?</span>;
             <span class="macro">assert_eq!</span>(top_docs.len(), <span class="number">0</span>, <span class="string">&quot;Expected no document&quot;</span>);
         }

         <span class="comment">// passes because prefix Levenshtein distance is 0
         </span>{
             <span class="kw">let </span>term = Term::from_field_text(country_field, <span class="string">&quot;jap&quot;</span>);
             <span class="kw">let </span>fuzzy_query = FuzzyTermQuery::new_prefix(term, <span class="number">1</span>, <span class="bool-val">true</span>);
             <span class="kw">let </span>top_docs = searcher.search(<span class="kw-2">&amp;</span>fuzzy_query, <span class="kw-2">&amp;</span>TopDocs::with_limit(<span class="number">2</span>))<span class="question-mark">?</span>;
             <span class="macro">assert_eq!</span>(top_docs.len(), <span class="number">1</span>, <span class="string">&quot;Expected only 1 document&quot;</span>);
             <span class="kw">let </span>(score, <span class="kw">_</span>) = top_docs[<span class="number">0</span>];
             <span class="macro">assert_nearly_equals!</span>(<span class="number">1.0</span>, score);
         }
         <span class="prelude-val">Ok</span>(())
     }

     <span class="attribute">#[test]
     </span><span class="kw">pub fn </span>test_fuzzy_term_transposition_cost_one() -&gt; <span class="kw">crate</span>::Result&lt;()&gt; {
         <span class="kw">let </span><span class="kw-2">mut </span>schema_builder = Schema::builder();
         <span class="kw">let </span>country_field = schema_builder.add_text_field(<span class="string">&quot;country&quot;</span>, TEXT);
         <span class="kw">let </span>schema = schema_builder.build();
         <span class="kw">let </span>index = Index::create_in_ram(schema);
         <span class="kw">let </span><span class="kw-2">mut </span>index_writer = index.writer_for_tests()<span class="question-mark">?</span>;
         index_writer.add_document(<span class="macro">doc!</span>(country_field =&gt; <span class="string">&quot;japan&quot;</span>))<span class="question-mark">?</span>;
         index_writer.commit()<span class="question-mark">?</span>;
         <span class="kw">let </span>reader = index.reader()<span class="question-mark">?</span>;
         <span class="kw">let </span>searcher = reader.searcher();
         <span class="kw">let </span>term_jaapn = Term::from_field_text(country_field, <span class="string">&quot;jaapn&quot;</span>);
         {
             <span class="kw">let </span>fuzzy_query_transposition = FuzzyTermQuery::new(term_jaapn.clone(), <span class="number">1</span>, <span class="bool-val">true</span>);
             <span class="kw">let </span>count = searcher.search(<span class="kw-2">&amp;</span>fuzzy_query_transposition, <span class="kw-2">&amp;</span>Count)<span class="question-mark">?</span>;
             <span class="macro">assert_eq!</span>(count, <span class="number">1</span>);
         }
         {
             <span class="kw">let </span>fuzzy_query_transposition = FuzzyTermQuery::new(term_jaapn, <span class="number">1</span>, <span class="bool-val">false</span>);
             <span class="kw">let </span>count = searcher.search(<span class="kw-2">&amp;</span>fuzzy_query_transposition, <span class="kw-2">&amp;</span>Count)<span class="question-mark">?</span>;
             <span class="macro">assert_eq!</span>(count, <span class="number">0</span>);
         }
         <span class="prelude-val">Ok</span>(())
     }
 }
 </code></pre></div>
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