A UMD build of fast-levenshtein
This script should not be not be installed directly. It is a library for other scripts to include with the meta directive // @require https://update.greasyfork.org/scripts/525938/1532043/fast-levenshtein-umd.js
(function (global, factory) { typeof exports === 'object' && typeof module !== 'undefined' ? module.exports = factory() : typeof define === 'function' && define.amd ? define(factory) : (global = typeof globalThis !== 'undefined' ? globalThis : global || self, global.Levenshtein = factory()); })(this, (function () { 'use strict'; const peq = new Uint32Array(0x10000); const myers_32 = (a, b) => { const n = a.length; const m = b.length; const lst = 1 << (n - 1); let pv = -1; let mv = 0; let sc = n; let i = n; while (i--) { peq[a.charCodeAt(i)] |= 1 << i; } for (i = 0; i < m; i++) { let eq = peq[b.charCodeAt(i)]; const xv = eq | mv; eq |= ((eq & pv) + pv) ^ pv; mv |= ~(eq | pv); pv &= eq; if (mv & lst) sc++; if (pv & lst) sc--; mv = (mv << 1) | 1; pv = (pv << 1) | ~(xv | mv); mv &= xv; } i = n; while (i--) { peq[a.charCodeAt(i)] = 0; } return sc; }; const myers_x = (b, a) => { const n = a.length; const m = b.length; const mhc = []; const phc = []; const hsize = Math.ceil(n / 32); const vsize = Math.ceil(m / 32); for (let i = 0; i < hsize; i++) { phc[i] = -1; mhc[i] = 0; } let j = 0; for (; j < vsize - 1; j++) { let mv = 0; let pv = -1; const start = j * 32; const vlen = Math.min(32, m) + start; for (let k = start; k < vlen; k++) { peq[b.charCodeAt(k)] |= 1 << k; } for (let i = 0; i < n; i++) { const eq = peq[a.charCodeAt(i)]; const pb = (phc[(i / 32) | 0] >>> i) & 1; const mb = (mhc[(i / 32) | 0] >>> i) & 1; const xv = eq | mv; const xh = ((((eq | mb) & pv) + pv) ^ pv) | eq | mb; let ph = mv | ~(xh | pv); let mh = pv & xh; if ((ph >>> 31) ^ pb) { phc[(i / 32) | 0] ^= 1 << i; } if ((mh >>> 31) ^ mb) { mhc[(i / 32) | 0] ^= 1 << i; } ph = (ph << 1) | pb; mh = (mh << 1) | mb; pv = mh | ~(xv | ph); mv = ph & xv; } for (let k = start; k < vlen; k++) { peq[b.charCodeAt(k)] = 0; } } let mv = 0; let pv = -1; const start = j * 32; const vlen = Math.min(32, m - start) + start; for (let k = start; k < vlen; k++) { peq[b.charCodeAt(k)] |= 1 << k; } let score = m; for (let i = 0; i < n; i++) { const eq = peq[a.charCodeAt(i)]; const pb = (phc[(i / 32) | 0] >>> i) & 1; const mb = (mhc[(i / 32) | 0] >>> i) & 1; const xv = eq | mv; const xh = ((((eq | mb) & pv) + pv) ^ pv) | eq | mb; let ph = mv | ~(xh | pv); let mh = pv & xh; score += (ph >>> (m - 1)) & 1; score -= (mh >>> (m - 1)) & 1; if ((ph >>> 31) ^ pb) { phc[(i / 32) | 0] ^= 1 << i; } if ((mh >>> 31) ^ mb) { mhc[(i / 32) | 0] ^= 1 << i; } ph = (ph << 1) | pb; mh = (mh << 1) | mb; pv = mh | ~(xv | ph); mv = ph & xv; } for (let k = start; k < vlen; k++) { peq[b.charCodeAt(k)] = 0; } return score; }; const distance = (a, b) => { if (a.length < b.length) { const tmp = b; b = a; a = tmp; } if (b.length === 0) return a.length; if (a.length <= 32) return myers_32(a, b); return myers_x(a, b); }; const collator = Intl.Collator("generic", { sensitivity: "base" }); const prevRow = []; const str2Char = []; const Levenshtein = { get(str1, str2, options={useCollator:false}) { const useCollator = (options && collator && options.useCollator); if (useCollator) { const str1Len = str1.length; const str2Len = str2.length; if (str1Len === 0) return str2Len; if (str2Len === 0) return str1Len; for (i=0; i<str2Len; ++i) { prevRow[i] = i; str2Char[i] = str2.charCodeAt(i); } prevRow[str2Len] = str2Len; var strCmp; for (let i = 0; i < str1Len; ++i) { let nextCol = i + 1; for (let j = 0; j < str2Len; ++j) { let curCol = nextCol; strCmp = 0 === collator.compare(str1.charAt(i), String.fromCharCode(str2Char[j])); nextCol = prevRow[j] + (strCmp ? 0 : 1); let tmp = curCol + 1; if (nextCol > tmp) { nextCol = tmp; } tmp = prevRow[j + 1] + 1; if (nextCol > tmp) { nextCol = tmp; } prevRow[j] = curCol; } prevRow[j] = nextCol; } return nextCol; } return distance(str1, str2); } }; return Levenshtein; }));