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https://github.com/discourse/discourse.git
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4cb3412a56
When we introduced unicode support in the regular expressions used in watched words (9a27803
) we didn't realize the cost adding the `u` flag would be.
Turns out, it's pretty bad when you have lots of regular expressions to test. A customer had slightly less than 200 watched words, and it would freeze the browser for about 2s on the first check of those regular expressions (roughly 10ms per regular expression).
This commit introduces a new field (`word`) to the serialized watched words which is then converted to a very fast and cheap regular expression on the client-side. We use that regexp to quicly check whether a matcher is even worth trying so that we don't incure the cost of compiling the expensive unicode regexp.
This commit also busts the `WordWatcher` cache since we added a new field to be serialized.
One nice side effect of using `matchAll` instead of a `while / exec` loop is that the likeliness of having a bad regexp matching infinitely is vastly reduced 🙌
270 lines
7.7 KiB
JavaScript
270 lines
7.7 KiB
JavaScript
import {
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createWatchedWordRegExp,
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toWatchedWord,
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} from "discourse-common/utils/watched-words";
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const MAX_MATCHES = 100;
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function isLinkOpen(str) {
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return /^<a[>\s]/i.test(str);
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}
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function isLinkClose(str) {
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return /^<\/a\s*>/i.test(str);
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}
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function findAllMatches(text, matchers) {
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const matches = [];
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for (const { word, pattern, replacement, link } of matchers) {
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if (matches.length >= MAX_MATCHES) {
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break;
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}
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if (word.test(text)) {
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for (const match of text.matchAll(pattern)) {
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matches.push({
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index: match.index + match[0].indexOf(match[1]),
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text: match[1],
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replacement,
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link,
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});
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if (matches.length >= MAX_MATCHES) {
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break;
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}
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}
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}
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}
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return matches.sort((a, b) => a.index - b.index);
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}
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// We need this to load after mentions and hashtags which are priority 0
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export const priority = 1;
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const NONE = 0;
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const MENTION = 1;
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const HASHTAG_LINK = 2;
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const HASHTAG_SPAN = 3;
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const HASHTAG_ICON_SPAN = 4;
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export function setup(helper) {
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const opts = helper.getOptions();
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helper.registerPlugin((md) => {
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const matchers = [];
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if (md.options.discourse.watchedWordsReplace) {
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Object.entries(md.options.discourse.watchedWordsReplace).forEach(
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([regexpString, options]) => {
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const word = toWatchedWord({ [regexpString]: options });
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matchers.push({
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word: new RegExp(options.word, options.case_sensitive ? "" : "i"),
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pattern: createWatchedWordRegExp(word),
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replacement: options.replacement,
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link: false,
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});
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}
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);
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}
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if (md.options.discourse.watchedWordsLink) {
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Object.entries(md.options.discourse.watchedWordsLink).forEach(
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([regexpString, options]) => {
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const word = toWatchedWord({ [regexpString]: options });
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matchers.push({
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word: new RegExp(options.word, options.case_sensitive ? "" : "i"),
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pattern: createWatchedWordRegExp(word),
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replacement: options.replacement,
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link: true,
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});
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}
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);
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}
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if (matchers.length === 0) {
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return;
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}
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const cache = new Map();
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md.core.ruler.push("watched-words", (state) => {
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for (let j = 0, l = state.tokens.length; j < l; j++) {
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if (state.tokens[j].type !== "inline") {
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continue;
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}
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let tokens = state.tokens[j].children;
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let htmlLinkLevel = 0;
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// We scan once to mark tokens that must be skipped because they are
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// mentions or hashtags
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let lastType = NONE;
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let currentType = NONE;
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for (let i = 0; i < tokens.length; ++i) {
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const currentToken = tokens[i];
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if (currentToken.type === "mention_open") {
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lastType = MENTION;
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} else if (
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(currentToken.type === "link_open" ||
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currentToken.type === "span_open") &&
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currentToken.attrs &&
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currentToken.attrs.some(
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(attr) =>
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attr[0] === "class" &&
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(attr[1] === "hashtag" ||
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attr[1] === "hashtag-cooked" ||
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attr[1] === "hashtag-raw")
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)
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) {
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lastType =
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currentToken.type === "link_open" ? HASHTAG_LINK : HASHTAG_SPAN;
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}
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if (
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currentToken.type === "span_open" &&
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currentToken.attrs &&
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currentToken.attrs.some(
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(attr) =>
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attr[0] === "class" && attr[1] === "hashtag-icon-placeholder"
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)
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) {
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currentType = HASHTAG_ICON_SPAN;
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}
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if (lastType !== NONE) {
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currentToken.skipReplace = true;
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}
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if (
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(lastType === MENTION && currentToken.type === "mention_close") ||
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(lastType === HASHTAG_LINK && currentToken.type === "link_close") ||
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(lastType === HASHTAG_SPAN &&
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currentToken.type === "span_close" &&
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currentType !== HASHTAG_ICON_SPAN)
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) {
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lastType = NONE;
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}
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}
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// We scan from the end, to keep position when new tags added.
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// Use reversed logic in links start/end match
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for (let i = tokens.length - 1; i >= 0; i--) {
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const currentToken = tokens[i];
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// Skip content of markdown links
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if (currentToken.type === "link_close") {
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i--;
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while (
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tokens[i].level !== currentToken.level &&
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tokens[i].type !== "link_open"
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) {
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i--;
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}
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continue;
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}
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// Skip content of html tag links
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if (currentToken.type === "html_inline") {
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if (isLinkOpen(currentToken.content) && htmlLinkLevel > 0) {
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htmlLinkLevel--;
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}
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if (isLinkClose(currentToken.content)) {
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htmlLinkLevel++;
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}
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}
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// Skip content of mentions or hashtags
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if (currentToken.skipReplace) {
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continue;
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}
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if (currentToken.type === "text") {
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const text = currentToken.content;
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let matches;
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if (cache.has(text)) {
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matches = cache.get(text);
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} else {
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matches = findAllMatches(text, matchers);
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cache.set(text, matches);
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}
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// Now split string to nodes
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const nodes = [];
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let level = currentToken.level;
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let lastPos = 0;
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let token;
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for (let ln = 0; ln < matches.length; ln++) {
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if (matches[ln].index < lastPos) {
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continue;
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}
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if (matches[ln].index > lastPos) {
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token = new state.Token("text", "", 0);
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token.content = text.slice(lastPos, matches[ln].index);
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token.level = level;
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nodes.push(token);
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}
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if (matches[ln].link) {
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const url = state.md.normalizeLink(matches[ln].replacement);
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if (htmlLinkLevel === 0 && state.md.validateLink(url)) {
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token = new state.Token("link_open", "a", 1);
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token.attrs = [["href", url]];
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if (opts.discourse.previewing) {
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token.attrs.push(["data-word", ""]);
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}
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token.level = level++;
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token.markup = "linkify";
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token.info = "auto";
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nodes.push(token);
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token = new state.Token("text", "", 0);
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token.content = matches[ln].text;
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token.level = level;
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nodes.push(token);
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token = new state.Token("link_close", "a", -1);
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token.level = --level;
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token.markup = "linkify";
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token.info = "auto";
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nodes.push(token);
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}
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} else {
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token = new state.Token("text", "", 0);
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token.content = matches[ln].replacement;
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token.level = level;
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nodes.push(token);
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}
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lastPos = matches[ln].index + matches[ln].text.length;
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}
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if (lastPos < text.length) {
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token = new state.Token("text", "", 0);
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token.content = text.slice(lastPos);
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token.level = level;
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nodes.push(token);
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}
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// replace current node
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state.tokens[j].children = tokens = md.utils.arrayReplaceAt(
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tokens,
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i,
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nodes
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);
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}
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}
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}
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});
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});
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}
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