Added fuzzy searching + Some minor code refactoring
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litetex
parent
7fc0a3841a
commit
52542e04e8
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@ -111,6 +111,15 @@ public class SettingsActivity extends AppCompatActivity
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return super.onCreateOptionsMenu(menu);
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}
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@Override
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public void onBackPressed() {
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if (isSearchActive()) {
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setSearchActive(false);
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return;
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}
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super.onBackPressed();
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}
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@Override
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public boolean onOptionsItemSelected(final MenuItem item) {
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final int id = item.getItemId();
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@ -0,0 +1,121 @@
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package org.schabi.newpipe.settings.preferencesearch;
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import android.text.TextUtils;
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import androidx.annotation.NonNull;
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import org.schabi.newpipe.settings.preferencesearch.similarity.FuzzyScore;
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import java.util.Comparator;
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import java.util.Locale;
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import java.util.Map;
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import java.util.function.Function;
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import java.util.stream.Stream;
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public class PreferenceFuzzySearchFunction
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implements PreferenceSearchConfiguration.PreferenceSearchFunction {
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private static final FuzzyScore FUZZY_SCORE = new FuzzyScore(Locale.ROOT);
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@Override
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public Stream<PreferenceSearchItem> search(
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final Stream<PreferenceSearchItem> allAvailable,
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final String keyword
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) {
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final float maxScore = (keyword.length() + 1) * 3 - 2; // First can't get +2 bonus score
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return allAvailable
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// General search
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// Check all fields if anyone contains something that kind of matches the keyword
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.map(item -> new FuzzySearchGeneralDTO(item, keyword))
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.filter(dto -> dto.getScore() / maxScore >= 0.3f)
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.map(FuzzySearchGeneralDTO::getItem)
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// Specific search - Used for determining order of search results
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// Calculate a score based on specific search fields
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.map(item -> new FuzzySearchSpecificDTO(item, keyword))
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.sorted(Comparator.comparing(FuzzySearchSpecificDTO::getScore).reversed())
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.map(FuzzySearchSpecificDTO::getItem)
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// Limit the amount of search results
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.limit(20);
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}
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private float computeFuzzyScore(
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@NonNull final PreferenceSearchItem item,
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@NonNull final Function<PreferenceSearchItem, String> resolver,
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@NonNull final String keyword
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) {
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return FUZZY_SCORE.fuzzyScore(resolver.apply(item), keyword);
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}
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static class FuzzySearchGeneralDTO {
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private final PreferenceSearchItem item;
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private final float score;
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FuzzySearchGeneralDTO(
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final PreferenceSearchItem item,
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final String keyword) {
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this.item = item;
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this.score = FUZZY_SCORE.fuzzyScore(
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TextUtils.join(";", item.getAllRelevantSearchFields()),
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keyword);
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}
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public PreferenceSearchItem getItem() {
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return item;
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}
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public float getScore() {
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return score;
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}
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}
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static class FuzzySearchSpecificDTO {
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private static final Map<Function<PreferenceSearchItem, String>, Float> WEIGHT_MAP = Map.of(
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// The user will most likely look for the title -> prioritize it
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PreferenceSearchItem::getTitle, 1.5f,
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// The summary is also important as it usually contains a larger desc
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// Example: Searching for '4k' → 'show higher resolution' is shown
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PreferenceSearchItem::getSummary, 1f,
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// Entries are also important as they provide all known/possible values
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// Example: Searching where the resolution can be changed to 720p
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PreferenceSearchItem::getEntries, 1f
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);
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private final PreferenceSearchItem item;
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private final float score;
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FuzzySearchSpecificDTO(
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final PreferenceSearchItem item,
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final String keyword) {
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this.item = item;
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float attributeScoreSum = 0;
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int countOfAttributesWithScore = 0;
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for (final Map.Entry<Function<PreferenceSearchItem, String>, Float> we
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: WEIGHT_MAP.entrySet()) {
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final String valueToProcess = we.getKey().apply(item);
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if (valueToProcess.isEmpty()) {
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continue;
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}
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attributeScoreSum +=
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FUZZY_SCORE.fuzzyScore(valueToProcess, keyword) * we.getValue();
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countOfAttributesWithScore++;
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}
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if (countOfAttributesWithScore != 0) {
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this.score = attributeScoreSum / countOfAttributesWithScore;
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} else {
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this.score = 0;
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}
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}
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public PreferenceSearchItem getItem() {
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return item;
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}
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public float getScore() {
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return score;
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}
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}
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}
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@ -21,16 +21,7 @@ public class PreferenceSearchConfiguration {
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private BinaryOperator<String> breadcrumbConcat =
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(s1, s2) -> TextUtils.isEmpty(s1) ? s2 : (s1 + " > " + s2);
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private PreferenceSearchFunction searcher =
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(itemStream, keyword) ->
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itemStream
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// Filter the items by the keyword
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.filter(item -> item.getAllRelevantSearchFields().stream()
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.filter(str -> !TextUtils.isEmpty(str))
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.anyMatch(str ->
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str.toLowerCase().contains(keyword.toLowerCase())))
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// Limit the search results
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.limit(100);
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private PreferenceSearchFunction searcher = new PreferenceFuzzySearchFunction();
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private final List<String> parserIgnoreElements = Arrays.asList(
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PreferenceCategory.class.getSimpleName());
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@ -81,7 +81,7 @@ public class PreferenceSearchFragment extends Fragment {
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adapter.setContent(new ArrayList<>(results));
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setEmptyViewShown(!TextUtils.isEmpty(keyword) && results.isEmpty());
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setEmptyViewShown(results.isEmpty());
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}
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private void setEmptyViewShown(final boolean shown) {
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@ -0,0 +1,148 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.schabi.newpipe.settings.preferencesearch.similarity;
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import java.util.Locale;
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/**
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* A matching algorithm that is similar to the searching algorithms implemented in editors such
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* as Sublime Text, TextMate, Atom and others.
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*
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* <p>
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* One point is given for every matched character. Subsequent matches yield two bonus points.
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* A higher score indicates a higher similarity.
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* </p>
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*
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* <p>
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* This code has been adapted from Apache Commons Lang 3.3.
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* </p>
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*
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* @since 1.0
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*
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* Note: This class was forked from
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* <a href="https://git.io/JyYJg">
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* apache/commons-text (8cfdafc) FuzzyScore.java
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* </a>
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*/
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public class FuzzyScore {
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/**
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* Locale used to change the case of text.
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*/
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private final Locale locale;
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/**
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* This returns a {@link Locale}-specific {@link FuzzyScore}.
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*
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* @param locale The string matching logic is case insensitive.
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A {@link Locale} is necessary to normalize both Strings to lower case.
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* @throws IllegalArgumentException
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* This is thrown if the {@link Locale} parameter is {@code null}.
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*/
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public FuzzyScore(final Locale locale) {
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if (locale == null) {
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throw new IllegalArgumentException("Locale must not be null");
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}
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this.locale = locale;
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}
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/**
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* Find the Fuzzy Score which indicates the similarity score between two
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* Strings.
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*
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* <pre>
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* score.fuzzyScore(null, null) = IllegalArgumentException
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* score.fuzzyScore("not null", null) = IllegalArgumentException
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* score.fuzzyScore(null, "not null") = IllegalArgumentException
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* score.fuzzyScore("", "") = 0
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* score.fuzzyScore("Workshop", "b") = 0
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* score.fuzzyScore("Room", "o") = 1
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* score.fuzzyScore("Workshop", "w") = 1
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* score.fuzzyScore("Workshop", "ws") = 2
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* score.fuzzyScore("Workshop", "wo") = 4
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* score.fuzzyScore("Apache Software Foundation", "asf") = 3
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* </pre>
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*
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* @param term a full term that should be matched against, must not be null
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* @param query the query that will be matched against a term, must not be
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* null
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* @return result score
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* @throws IllegalArgumentException if the term or query is {@code null}
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*/
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public Integer fuzzyScore(final CharSequence term, final CharSequence query) {
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if (term == null || query == null) {
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throw new IllegalArgumentException("CharSequences must not be null");
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}
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// fuzzy logic is case insensitive. We normalize the Strings to lower
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// case right from the start. Turning characters to lower case
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// via Character.toLowerCase(char) is unfortunately insufficient
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// as it does not accept a locale.
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final String termLowerCase = term.toString().toLowerCase(locale);
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final String queryLowerCase = query.toString().toLowerCase(locale);
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// the resulting score
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int score = 0;
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// the position in the term which will be scanned next for potential
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// query character matches
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int termIndex = 0;
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// index of the previously matched character in the term
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int previousMatchingCharacterIndex = Integer.MIN_VALUE;
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for (int queryIndex = 0; queryIndex < queryLowerCase.length(); queryIndex++) {
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final char queryChar = queryLowerCase.charAt(queryIndex);
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boolean termCharacterMatchFound = false;
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for (; termIndex < termLowerCase.length()
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&& !termCharacterMatchFound; termIndex++) {
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final char termChar = termLowerCase.charAt(termIndex);
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if (queryChar == termChar) {
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// simple character matches result in one point
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score++;
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// subsequent character matches further improve
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// the score.
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if (previousMatchingCharacterIndex + 1 == termIndex) {
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score += 2;
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}
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previousMatchingCharacterIndex = termIndex;
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// we can leave the nested loop. Every character in the
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// query can match at most one character in the term.
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termCharacterMatchFound = true;
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}
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}
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}
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return score;
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}
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/**
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* Gets the locale.
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*
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* @return The locale
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*/
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public Locale getLocale() {
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return locale;
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}
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}
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