feat: added option to search closest ekey
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commit
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@ -2,6 +2,7 @@ import {
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Box,
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Button,
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ButtonGroup,
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Checkbox,
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Flex,
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HStack,
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Heading,
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@ -14,23 +15,29 @@ import {
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MenuItem,
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MenuList,
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Text,
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Tooltip,
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} from '@chakra-ui/react';
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import { useDispatch, useSelector } from 'react-redux';
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import { qmc2AddKey, qmc2ClearKeys } from '../settingsSlice';
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import { qmc2AddKey, qmc2AllowFuzzyNameSearch, qmc2ClearKeys } from '../settingsSlice';
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import { selectStagingQMCv2Settings } from '../settingsSelector';
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import { useState } from 'react';
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import React, { useState } from 'react';
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import { MdAdd, MdDeleteForever, MdExpandMore, MdFileUpload } from 'react-icons/md';
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import { ImportFileModal } from './QMCv2/ImportFileModal';
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import { KeyInput } from './QMCv2/KeyInput';
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import { InfoOutlineIcon } from '@chakra-ui/icons';
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export function PanelQMCv2Key() {
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const dispatch = useDispatch();
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const qmc2Keys = useSelector(selectStagingQMCv2Settings).keys;
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const { keys: qmc2Keys, allowFuzzyNameSearch } = useSelector(selectStagingQMCv2Settings);
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const [showImportModal, setShowImportModal] = useState(false);
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const addKey = () => dispatch(qmc2AddKey());
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const clearAll = () => dispatch(qmc2ClearKeys());
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const handleAllowFuzzyNameSearchCheckbox = (e: React.ChangeEvent<HTMLInputElement>) => {
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dispatch(qmc2AllowFuzzyNameSearch({ enable: e.target.checked }));
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};
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return (
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<Flex minH={0} flexDir="column" flex={1}>
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<Heading as="h2" size="lg">
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@ -60,6 +67,34 @@ export function PanelQMCv2Key() {
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</MenuList>
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</Menu>
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</ButtonGroup>
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<HStack>
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<Checkbox isChecked={allowFuzzyNameSearch} onChange={handleAllowFuzzyNameSearchCheckbox}>
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<Text>匹配相似文件名</Text>
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</Checkbox>
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<Tooltip
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hasArrow
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closeOnClick={false}
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label={
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<Box>
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<Text>若文件名匹配失败,则使用相似文件名的密钥。</Text>
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<Text>
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使用「
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<ruby>
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莱文斯坦距离
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<rp> (</rp>
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<rt>Levenshtein distance</rt>
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<rp>)</rp>
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</ruby>
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」算法计算相似程度。
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</Text>
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<Text>若密钥数量过多,匹配时可能会造成浏览器卡顿或无响应一段时间。</Text>
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</Box>
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}
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>
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<InfoOutlineIcon />
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</Tooltip>
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</HStack>
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</HStack>
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<Box flex={1} minH={0} overflow="auto" pr="4">
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@ -54,6 +54,8 @@ export function InstructionsIOS() {
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<Heading as="h3" size="md" mt="3">
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解密离线文件
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</Heading>
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<Text>勾选设定界面的「使用近似文件名匹配」可跳过该节内容。</Text>
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<Text>⚠ 注意:若密钥过多,匹配过程可能会造成浏览器卡顿或无响应。</Text>
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<OrderedList>
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<ListItem>
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<Text>
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@ -10,9 +10,16 @@ const DEFAULT_STORAGE_KEY = 'um-react-settings';
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function mergeSettings(settings: ProductionSettings): ProductionSettings {
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return produce(settingsSlice.getInitialState().production, (draft) => {
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for (const [k, v] of enumObject(settings.qmc2?.keys)) {
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if (typeof v === 'string') {
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draft.qmc2.keys[k] = v;
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if (settings?.qmc2) {
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const { allowFuzzyNameSearch, keys } = settings.qmc2;
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for (const [k, v] of enumObject(keys)) {
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if (typeof v === 'string') {
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draft.qmc2.keys[k] = v;
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}
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}
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if (typeof allowFuzzyNameSearch === 'boolean') {
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draft.qmc2.allowFuzzyNameSearch = allowFuzzyNameSearch;
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}
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}
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});
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@ -1,5 +1,6 @@
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import type { DecryptCommandOptions } from '~/decrypt-worker/types';
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import type { RootState } from '~/store';
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import { closestByLevenshtein } from '~/util/levenshtein';
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import { hasOwn } from '~/util/objects';
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export const selectStagingQMCv2Settings = (state: RootState) => state.settings.staging.qmc2;
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@ -7,9 +8,21 @@ export const selectFinalQMCv2Settings = (state: RootState) => state.settings.pro
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export const selectDecryptOptionByFile = (state: RootState, name: string): DecryptCommandOptions => {
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const normalizedName = name.normalize();
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const qmc2Keys = selectFinalQMCv2Settings(state).keys;
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let qmc2Key: string | undefined;
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const { keys: qmc2Keys, allowFuzzyNameSearch } = selectFinalQMCv2Settings(state);
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if (hasOwn(qmc2Keys, normalizedName)) {
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qmc2Key = qmc2Keys[normalizedName];
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} else if (allowFuzzyNameSearch) {
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const qmc2KeyStoreNames = Object.keys(qmc2Keys);
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if (qmc2KeyStoreNames.length > 0) {
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const closestName = closestByLevenshtein(normalizedName, qmc2KeyStoreNames);
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console.debug('qmc2: key db could not find %o, using closest %o instead.', normalizedName, closestName);
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qmc2Key = qmc2Keys[closestName];
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}
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}
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return {
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qmc2Key: hasOwn(qmc2Keys, normalizedName) ? qmc2Keys[normalizedName] : undefined,
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qmc2Key,
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};
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};
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@ -6,12 +6,14 @@ import { objectify } from 'radash';
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export interface StagingSettings {
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qmc2: {
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keys: { id: string; name: string; key: string }[];
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allowFuzzyNameSearch: boolean;
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};
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}
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export interface ProductionSettings {
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qmc2: {
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keys: Record<string, string>; // { [fileName]: ekey }
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allowFuzzyNameSearch: boolean;
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};
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}
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@ -22,11 +24,13 @@ export interface SettingsState {
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const initialState: SettingsState = {
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staging: {
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qmc2: {
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allowFuzzyNameSearch: false,
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keys: [],
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},
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},
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production: {
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qmc2: {
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allowFuzzyNameSearch: false,
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keys: {},
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},
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},
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@ -39,12 +43,14 @@ const stagingToProduction = (staging: StagingSettings): ProductionSettings => ({
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(item) => item.name.normalize(),
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(item) => item.key.trim()
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),
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allowFuzzyNameSearch: staging.qmc2.allowFuzzyNameSearch,
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},
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});
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const productionToStaging = (production: ProductionSettings): StagingSettings => ({
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qmc2: {
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keys: Object.entries(production.qmc2.keys).map(([name, key]) => ({ id: nanoid(), name, key })),
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allowFuzzyNameSearch: production.qmc2.allowFuzzyNameSearch,
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},
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});
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@ -81,6 +87,9 @@ export const settingsSlice = createSlice({
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qmc2ClearKeys(state) {
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state.staging.qmc2.keys = [];
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},
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qmc2AllowFuzzyNameSearch(state, { payload: { enable } }: PayloadAction<{ enable: boolean }>) {
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state.staging.qmc2.allowFuzzyNameSearch = enable;
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},
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discardStagingChanges: (state) => {
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state.staging = productionToStaging(state.production);
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},
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@ -107,6 +116,7 @@ export const {
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qmc2DeleteKey,
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qmc2ClearKeys,
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qmc2ImportKeys,
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qmc2AllowFuzzyNameSearch,
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commitStagingChange,
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discardStagingChanges,
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17
src/util/__tests__/levenshtein.test.ts
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17
src/util/__tests__/levenshtein.test.ts
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@ -0,0 +1,17 @@
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import { closestByLevenshtein, levenshtein } from '../levenshtein';
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test('levenshtein quick test', () => {
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expect(levenshtein('cat', '')).toStrictEqual(3);
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expect(levenshtein('', 'cat')).toStrictEqual(3);
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expect(levenshtein('cat', 'cat')).toStrictEqual(0);
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expect(levenshtein('cat', 'cut')).toStrictEqual(1);
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expect(levenshtein('kitten', 'sitting')).toStrictEqual(3);
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expect(levenshtein('tier', 'tor')).toStrictEqual(2);
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expect(levenshtein('mississippi', 'swiss miss')).toStrictEqual(8);
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});
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test('closestByLevenshtein quick test', () => {
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expect(closestByLevenshtein('cat', ['cut', 'dog', 'bat'])).toStrictEqual('cut');
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expect(closestByLevenshtein('dag', ['dog', 'pumpkin'])).toStrictEqual('dog');
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expect(closestByLevenshtein('hello', ['jello', 'yellow', 'bello'])).toStrictEqual('jello');
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});
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src/util/levenshtein.ts
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77
src/util/levenshtein.ts
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@ -0,0 +1,77 @@
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const textEncoder = new TextEncoder();
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// translation of pseudocode from Wikipedia:
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// https://en.wikipedia.org/wiki/Levenshtein_distance#Iterative_with_two_matrix_rows
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export function levenshtein(str1: string, str2: string) {
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if (str1 === str2) {
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return 0;
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}
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if (str1.length === 0) {
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return str2.length;
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} else if (str2.length === 0) {
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return str1.length;
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}
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// Convert them to Uint8Array to avoid expensive string APIs.
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const s = textEncoder.encode(str1.toLowerCase());
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const t = textEncoder.encode(str2.toLowerCase());
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const m = s.byteLength;
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const n = t.byteLength;
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// create two work vectors of integer distances
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let v0 = new Uint32Array(n + 1);
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let v1 = new Uint32Array(n + 1);
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// initialize v0 (the previous row of distances)
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// this row is A[0][i]: edit distance from an empty s to t;
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// that distance is the number of characters to append to s to make t.
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for (let i = 0; i <= n; i++) {
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v0[i] = i;
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}
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for (let i = 0; i < m; i++) {
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// calculate v1 (current row distances) from the previous row v0
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// first element of v1 is A[i + 1][0]
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// edit distance is delete (i + 1) chars from s to match empty t
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v1[0] = i + 1;
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// use formula to fill in the rest of the row
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for (let j = 0; j < n; j++) {
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// calculating costs for A[i + 1][j + 1]
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const deletionCost = v0[j + 1] + 1;
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const insertionCost = v1[j] + 1;
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const substitutionCost = v0[j] + (s[i] === t[j] ? 0 : 1);
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v1[j + 1] = Math.min(deletionCost, insertionCost, substitutionCost);
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}
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// copy v1 (current row) to v0 (previous row) for next iteration
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// since data in v1 is always invalidated, a swap without copy could be more efficient
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[v0, v1] = [v1, v0];
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}
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// after the last swap, the results of v1 are now in v0
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return v0[n];
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}
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export function closestByLevenshtein(str: string, candidates: string[]) {
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// Faster than pre-calculate all and pass scores to Math.min.
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const n = candidates.length;
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if (n === 0) {
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throw new Error('empty candidates');
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}
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let lowestIdx = 0;
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let lowestScore = levenshtein(str, candidates[0]);
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for (let i = 1; i < n; i++) {
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const score = levenshtein(str, candidates[i]);
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if (score < lowestScore) {
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lowestScore = score;
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lowestIdx = i;
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}
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}
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return candidates[lowestIdx];
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}
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