fediversity.eu/node_modules/sucrase/dist/esm/parser/tokenizer/readWord.js

65 lines
1.9 KiB
JavaScript
Raw Normal View History

2024-03-26 16:28:28 +01:00
import {input, state} from "../traverser/base";
import {charCodes} from "../util/charcodes";
import {IS_IDENTIFIER_CHAR} from "../util/identifier";
import {finishToken} from "./index";
import {READ_WORD_TREE} from "./readWordTree";
import {TokenType as tt} from "./types";
/**
* Read an identifier, producing either a name token or matching on one of the existing keywords.
* For performance, we pre-generate big decision tree that we traverse. Each node represents a
* prefix and has 27 values, where the first value is the token or contextual token, if any (-1 if
* not), and the other 26 values are the transitions to other nodes, or -1 to stop.
*/
export default function readWord() {
let treePos = 0;
let code = 0;
let pos = state.pos;
while (pos < input.length) {
code = input.charCodeAt(pos);
if (code < charCodes.lowercaseA || code > charCodes.lowercaseZ) {
break;
}
const next = READ_WORD_TREE[treePos + (code - charCodes.lowercaseA) + 1];
if (next === -1) {
break;
} else {
treePos = next;
pos++;
}
}
const keywordValue = READ_WORD_TREE[treePos];
if (keywordValue > -1 && !IS_IDENTIFIER_CHAR[code]) {
state.pos = pos;
if (keywordValue & 1) {
finishToken(keywordValue >>> 1);
} else {
finishToken(tt.name, keywordValue >>> 1);
}
return;
}
while (pos < input.length) {
const ch = input.charCodeAt(pos);
if (IS_IDENTIFIER_CHAR[ch]) {
pos++;
} else if (ch === charCodes.backslash) {
// \u
pos += 2;
if (input.charCodeAt(pos) === charCodes.leftCurlyBrace) {
while (pos < input.length && input.charCodeAt(pos) !== charCodes.rightCurlyBrace) {
pos++;
}
pos++;
}
} else if (ch === charCodes.atSign && input.charCodeAt(pos + 1) === charCodes.atSign) {
pos += 2;
} else {
break;
}
}
state.pos = pos;
finishToken(tt.name);
}