tongwentang
TongWen Core converter
A fast converter between Traditional Chinese and Simplified Chinese and a helper DOM tree walker.
Installation
Install by npm:
npm install tongwen-coreInstall by yarn:
yarn add tongwen-coreExamples and Usages
Note: Example scripts are all written in TypeScript.
An example for how to use converter:
import { createConverterMap, createConverterObj, LangType, SrcPack } from 'tongwen-core';
const dics: SrcPack = { s2t: [{ 台湾: '台灣' }], t2s: [{ 台灣: '台湾' }] };
const mConv = createConverterMap(dics);
const oConv = createConverterObj(dics);
const result = [mConv.phrase(LangType.s2t, '台湾'), oConv.phrase(LangType.s2t, '台湾')];
console.log(result); // [ '台灣', '台灣' ]The difference between
createConverterMapandcreateConverterObjis the former use esMapand
the latter use plainObjectas internal data structure. Use depend on your environment,
but the es version is highly recommended, due performance boost can up to 2.x time faster.
Note: You should provide dictionaries when creating converter, no default dictionaries.
Here is an example for using converter and walker in web page.
import { createConverterMap, LangType, SrcPack, walkerNode } from 'tongwen-core';
const dics: SrcPack = { s2t: [{ 台湾: '台灣' }], t2s: [{ 台灣: '台湾' }] };
const mConv = createConverterMap(dics);
const parseds = walkNode(document);
parseds; // parsed result as an arrayimport { walkerNode } from 'tongwen-core';
// customize by passing custom function(s)
const parseds = walkNode(document, { isRejectNode: node => false });
parseds; // parsed result as an arrayDictionaries
Dictionaries that included in this project is use only for test, you can use them but not recommmanded, since they are for v1.5 New TongWenTang Core algorithm. We plan to release a independent repository in the future.
API and Types
For converter
// The source dictionaries collection
type SrcPack = {
s2t: Record<string, string>[];
t2s: Record<string, string>[];
};
const dics: SrcPack = { s2t: [{ 台湾: '台灣' }], t2s: [{ 台灣: '台湾' }] };
// Converter type
type Converter = {
set: (src: SrcPack) => undefined;
char: (type: LangType, text: string) => string;
phrase: (type: LangType, text: string) => string;
};For walker:
// ParsedResult
interface ParsedTextNode {
type: 'TEXT';
node: Node;
text: string;
}
interface ParsedElementNode {
type: 'ELEMENT';
node: Element;
attr: string;
text: string;
}
type ParsedResult = ParsedTextNode | ParsedElementNode;
// WalkNode
type WalkNode = (node: Node, anf?: Partial<AcceptNodeFn>) => ParsedResult[];
interface AcceptNodeFn {
hasTargetContent: (text: string | null) => boolean;
isRejectNode: (node: Node) => boolean;
isEditableElement: (elm: Element) => boolean;
hasTargetAttributes: (elm: Element) => boolean;
parseTextNode: (node: Node) => ParsedTextNode;
parseElementNode: (elm: Element) => ParsedElementNode[];
}For more detail, please check the source code.
Recommanded for development
- Editor: Visual Studio Code
- For best TypeScript support
- Packages: prettier - code formater, TypeScript Toolbox
- Environment
nodeyarn
npmscripts：test：test for any TypeScript error
Story
TongWenCore and TongWenParser derived from the core converter of New Tongwentang extension (version 1.5), which a browser extension that provide functionality for convert charaters between Traditional Chinese and Simplified Chinese who developed by softcup.
TongWenCore and TongWenParser extract from the extension as a independent repository and totally rewrite with TypeScript to make it more solid.
Convert speed of TongWenCore is faster than New Tongwentang Core (about 3.x time faster which tested in certain case). Convert Algorithm have been redesign, the idea was originally from cookwu and t7yang who implemented in TypeScript.
Lisence
MIT