zola-inky-fork/static/js/search.js

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function debounce(func, wait) {
var timeout;
return function () {
var context = this;
var args = arguments;
clearTimeout(timeout);
timeout = setTimeout(function () {
timeout = null;
func.apply(context, args);
}, wait);
};
}
// Taken from mdbook
// The strategy is as follows:
// First, assign a value to each word in the document:
// Words that correspond to search terms (stemmer aware): 40
// Normal words: 2
// First word in a sentence: 8
// Then use a sliding window with a constant number of words and count the
// sum of the values of the words within the window. Then use the window that got the
// maximum sum. If there are multiple maximas, then get the last one.
// Enclose the terms in <b>.
function makeTeaser(body, terms) {
var TERM_WEIGHT = 40;
var NORMAL_WORD_WEIGHT = 2;
var FIRST_WORD_WEIGHT = 8;
var TEASER_MAX_WORDS = 30;
var stemmedTerms = terms.map(function (w) {
return elasticlunr.stemmer(w.toLowerCase());
});
var termFound = false;
var index = 0;
var weighted = []; // contains elements of ["word", weight, index_in_document]
// split in sentences, then words
var sentences = body.toLowerCase().split(". ");
for (var i in sentences) {
var words = sentences[i].split(" ");
var value = FIRST_WORD_WEIGHT;
for (var j in words) {
var word = words[j];
if (word.length > 0) {
for (var k in stemmedTerms) {
if (elasticlunr.stemmer(word).startsWith(stemmedTerms[k])) {
value = TERM_WEIGHT;
termFound = true;
}
}
weighted.push([word, value, index]);
value = NORMAL_WORD_WEIGHT;
}
index += word.length;
index += 1; // ' ' or '.' if last word in sentence
}
index += 1; // because we split at a two-char boundary '. '
}
if (weighted.length === 0) {
return body;
}
var windowWeights = [];
var windowSize = Math.min(weighted.length, TEASER_MAX_WORDS);
// We add a window with all the weights first
var curSum = 0;
for (var i = 0; i < windowSize; i++) {
curSum += weighted[i][1];
}
windowWeights.push(curSum);
for (var i = 0; i < weighted.length - windowSize; i++) {
curSum -= weighted[i][1];
curSum += weighted[i + windowSize][1];
windowWeights.push(curSum);
}
// If we didn't find the term, just pick the first window
var maxSumIndex = 0;
if (termFound) {
var maxFound = 0;
// backwards
for (var i = windowWeights.length - 1; i >= 0; i--) {
if (windowWeights[i] > maxFound) {
maxFound = windowWeights[i];
maxSumIndex = i;
}
}
}
var teaser = [];
var startIndex = weighted[maxSumIndex][2];
for (var i = maxSumIndex; i < maxSumIndex + windowSize; i++) {
var word = weighted[i];
if (startIndex < word[2]) {
// missing text from index to start of `word`
teaser.push(body.substring(startIndex, word[2]));
startIndex = word[2];
}
// add <em/> around search terms
if (word[1] === TERM_WEIGHT) {
teaser.push("<b>");
}
startIndex = word[2] + word[0].length;
teaser.push(body.substring(word[2], startIndex));
if (word[1] === TERM_WEIGHT) {
teaser.push("</b>");
}
}
teaser.push("…");
return teaser.join("");
}
function formatSearchResultItem(item, terms) {
return '<div class="search-results__item">'
+ `<h3><a href="${item.ref}">${item.doc.title}</a></h3>`
+ `<p>${makeTeaser(item.doc.body, terms)}</p>`
+ '</div>';
}
function initSearch() {
var $searchInput = document.getElementById("search");
var $searchResults = document.querySelector(".search-results");
var $searchResultsItems = document.querySelector(".search-results__items");
var MAX_ITEMS = 20;
var options = {
bool: "AND",
fields: {
title: { boost: 2 },
body: { boost: 1 },
}
};
var currentTerm = "";
var index = elasticlunr.Index.load(window.searchIndex);
$searchInput.addEventListener("keyup", debounce(function () {
var term = $searchInput.value.trim();
if (term === currentTerm || !index) {
return;
}
$searchResults.style.display = term === "" ? "none" : "block";
$searchResultsItems.innerHTML = "";
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currentTerm = term;
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if (term === "") {
return;
}
var results = index.search(term, options);
if (results.length === 0) {
$searchResults.style.display = "none";
return;
}
for (var i = 0; i < Math.min(results.length, MAX_ITEMS); i++) {
var item = document.createElement("li");
item.innerHTML = formatSearchResultItem(results[i], term.split(" "));
$searchResultsItems.appendChild(item);
}
}, 150));
}
if (document.readyState === "complete" ||
(document.readyState !== "loading" && !document.documentElement.doScroll)
) {
initSearch();
} else {
document.addEventListener("DOMContentLoaded", initSearch);
}