1. To run on ios, compile jxcore
$ mkdir ~/jxcore
$ cd ~/jxcore
$ git clone https://github.com/jxcore/jxcore.git
$ cd ~/jxcore/jxcore
$ ./build_scripts/ios-compile.sh
If there is a problem with import which module not found, then install python which
through the following statementsudo easy_install tools/which-1.1.0-py2.7.egg
If other problems occur, you can refer to the prerequisites for compiling ios with jxcore and take corresponding measures.
https://github.com/jxcore/jxcore/blob/master/doc/HOW_TO_COMPILE.md
* GCC 4.2 or newer (for SpiderMonkey builds 4.7 )
* Python 2.6 or 2.7
* GNU Make 3.81 or newer
* libexecinfo (FreeBSD and OpenBSD only)
* for SpiderMonkey: 'which' python module (sudo easy_install tools/which-1.1.0-py2.7.egg)
2. Install jxcore on mac
$ ./configure
$ sudo make install
3. Create the cordova program. If cordova is not installed, you can install it yourself.
$ cordova create hello com.example.hello HelloWorld
$ cd hello
4. Download and install the jxcore-cordova plug-in
$ git clone https://github.com/jxcore/jxcore-cordova
Using jxcore-cordova’s template index.html
$ cp ./jxcore-cordova/sample/www/index.html ./www/
Copy the jxcore package compiled for running on ios in the first step
$ cp -r ~/jxcore/jxcore/out_ios/ios/bin jxcore-cordova/io.jxcore.node/
5. Add cordova’s ios platform
$ cordova platforms add ios
$ cordova plugin add jxcore-cordova/io.jxcore.node/
$ cordova build
$ cordova run ios
If the build error occurs, "C does not support default arguments"
Just removing the default value will usually solve the problem.
will
JXCORE_EXTERN(void)
JX_SetString(JXValue *value, const char *val, const int32_t length = 0);
Modify to
JXCORE_EXTERN(void)
JX_SetString(JXValue *value, const char *val, const int32_t length);
Just rebuild
6. You should be able to see the cordova running interface at this time.
7. Add nodejs server in Resources/jxcore_app/app.js
Add the following code at the end of app.js
function getIP() {
var os = require('os');
var nets = os.networkInterfaces();
console.log(nets);
for ( var a in nets) {
var ifaces = nets[a];
for (var o in ifaces) {
If (ifaces[o].family == "IPv4" && !ifaces[o].internal) { return ifaces[o].address; }
return null; }
var ip = getIP();
if (!ip) {
console.error("You should connect to a network!");
Return;
}
var http = require('http');
http.createServer(function(req, res) {
res.writeHead(200, { ‘Content-Type’: ‘text/plain’
});
var cur_client = "";
If(req.connection && req.connection.remoteAddress) {
console.log(req.connection.remoteAddress);
cur_client = req.connection.remoteAddress; } else if(req.headers) {
console.log("request header X-Forwarded-For");
console.log(req.headers['X-Forwarded-For']);
cur_client = req.headers['X-Forwarded-For']; cordova('log').call('client( ' cur_client ' ) come');
res.end('Hello ' cur_client ', I am server on iphone app(' ip '). ' Date.now() 'n');
}).listen(1337, ip);
console.log('Server running at http://' ip ':1337/');
Run the program, you can see the iPhone's IP in the xcode log information, and then you can browse the web through the web page.

JavaScript runs in browsers and Node.js environments and relies on the JavaScript engine to parse and execute code. 1) Generate abstract syntax tree (AST) in the parsing stage; 2) convert AST into bytecode or machine code in the compilation stage; 3) execute the compiled code in the execution stage.

The future trends of Python and JavaScript include: 1. Python will consolidate its position in the fields of scientific computing and AI, 2. JavaScript will promote the development of web technology, 3. Cross-platform development will become a hot topic, and 4. Performance optimization will be the focus. Both will continue to expand application scenarios in their respective fields and make more breakthroughs in performance.

Both Python and JavaScript's choices in development environments are important. 1) Python's development environment includes PyCharm, JupyterNotebook and Anaconda, which are suitable for data science and rapid prototyping. 2) The development environment of JavaScript includes Node.js, VSCode and Webpack, which are suitable for front-end and back-end development. Choosing the right tools according to project needs can improve development efficiency and project success rate.

Yes, the engine core of JavaScript is written in C. 1) The C language provides efficient performance and underlying control, which is suitable for the development of JavaScript engine. 2) Taking the V8 engine as an example, its core is written in C, combining the efficiency and object-oriented characteristics of C. 3) The working principle of the JavaScript engine includes parsing, compiling and execution, and the C language plays a key role in these processes.

JavaScript is at the heart of modern websites because it enhances the interactivity and dynamicity of web pages. 1) It allows to change content without refreshing the page, 2) manipulate web pages through DOMAPI, 3) support complex interactive effects such as animation and drag-and-drop, 4) optimize performance and best practices to improve user experience.

C and JavaScript achieve interoperability through WebAssembly. 1) C code is compiled into WebAssembly module and introduced into JavaScript environment to enhance computing power. 2) In game development, C handles physics engines and graphics rendering, and JavaScript is responsible for game logic and user interface.

JavaScript is widely used in websites, mobile applications, desktop applications and server-side programming. 1) In website development, JavaScript operates DOM together with HTML and CSS to achieve dynamic effects and supports frameworks such as jQuery and React. 2) Through ReactNative and Ionic, JavaScript is used to develop cross-platform mobile applications. 3) The Electron framework enables JavaScript to build desktop applications. 4) Node.js allows JavaScript to run on the server side and supports high concurrent requests.

Python is more suitable for data science and automation, while JavaScript is more suitable for front-end and full-stack development. 1. Python performs well in data science and machine learning, using libraries such as NumPy and Pandas for data processing and modeling. 2. Python is concise and efficient in automation and scripting. 3. JavaScript is indispensable in front-end development and is used to build dynamic web pages and single-page applications. 4. JavaScript plays a role in back-end development through Node.js and supports full-stack development.


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