我有一个Express Node.js应用程序,但我也有一个机器学习算法在Python中使用。是否有一种方法可以从我的Node.js应用程序调用Python函数来利用机器学习库的强大功能?


当前回答

通过extrabacon, Python -shell模块是一种从Node.js运行Python脚本的简单方法,具有基本但有效的进程间通信和更好的错误处理。

安装:

npm: NPM安装python-shell。

或者用纱线: 纱线加蟒壳

运行一个简单的Python脚本:

const PythonShell = require('python-shell').PythonShell;

PythonShell.run('my_script.py', null, function (err) {
  if (err) throw err;
  console.log('finished');
});

运行带有参数和选项的Python脚本:

const PythonShell = require('python-shell').PythonShell;

var options = {
  mode: 'text',
  pythonPath: 'path/to/python',
  pythonOptions: ['-u'],
  scriptPath: 'path/to/my/scripts',
  args: ['value1', 'value2', 'value3']
};

PythonShell.run('my_script.py', options, function (err, results) {
  if (err) 
    throw err;
  // Results is an array consisting of messages collected during execution
  console.log('results: %j', results);
});

要获得完整的文档和源代码,请访问https://github.com/extrabacon/python-shell

其他回答

您现在可以使用支持Python和Javascript的RPC库,例如zerorpc

从他们的头版:

node . js的客户

var zerorpc = require("zerorpc");

var client = new zerorpc.Client();
client.connect("tcp://127.0.0.1:4242");

client.invoke("hello", "RPC", function(error, res, more) {
    console.log(res);
});

Python服务器

import zerorpc

class HelloRPC(object):
    def hello(self, name):
        return "Hello, %s" % name

s = zerorpc.Server(HelloRPC())
s.bind("tcp://0.0.0.0:4242")
s.run()

你可以在NPM上查看我的套餐 https://www.npmjs.com/package/@guydev/native-python

它提供了一种非常简单而强大的方式来从node运行python函数

import { runFunction } from '@guydev/native-python'

const example = async () => {
   const input = [1,[1,2,3],{'foo':'bar'}]
   const { error, data } = await runFunction('/path/to/file.py','hello_world', '/path/to/python', input)

   // error will be null if no error occured.
   if (error) {
       console.log('Error: ', error)
   }

   else {
       console.log('Success: ', data)
       // prints data or null if function has no return value
   }
}

python模块

# module: file.py

def hello_world(a,b,c):
    print( type(a), a) 
    # <class 'int'>, 1

    print(type(b),b)
    # <class 'list'>, [1,2,3]

    print(type(c),c)
    # <class 'dict'>, {'foo':'bar'}
/*eslint-env es6*/
/*global require*/
/*global console*/
var express = require('express'); 
var app = express();

// Creates a server which runs on port 3000 and  
// can be accessed through localhost:3000
app.listen(3000, function() { 
    console.log('server running on port 3000'); 
} ) 

app.get('/name', function(req, res) {

    console.log('Running');

    // Use child_process.spawn method from  
    // child_process module and assign it 
    // to variable spawn 
    var spawn = require("child_process").spawn;   
    // Parameters passed in spawn - 
    // 1. type_of_script 
    // 2. list containing Path of the script 
    //    and arguments for the script  

    // E.g : http://localhost:3000/name?firstname=Levente
    var process = spawn('python',['apiTest.py', 
                        req.query.firstname]);

    // Takes stdout data from script which executed 
    // with arguments and send this data to res object
    var output = '';
    process.stdout.on('data', function(data) {

        console.log("Sending Info")
        res.end(data.toString('utf8'));
    });

    console.log(output);
}); 

这对我很管用。必须将python.exe添加到此代码段的路径变量中。另外,确保你的python脚本在你的项目文件夹中。

const util = require('util');
const exec = util.promisify(require('child_process').exec);
    
function runPythonFile() {
  const { stdout, stderr } = await exec('py ./path_to_python_file -s asdf -d pqrs');
  if (stdout) { // do something }
  if (stderr) { // do something }
}

欲了解更多信息,请访问Nodejs官方子进程页面:https://nodejs.org/api/child_process.html#child_processexeccommand-options-callback

之前的大多数答案都将承诺的成功称为on(“数据”),这不是正确的方法,因为如果你收到很多数据,你只会得到第一部分。相反,你必须在end事件上做。

const { spawn } = require('child_process');
const pythonDir = (__dirname + "/../pythonCode/"); // Path of python script folder
const python = pythonDir + "pythonEnv/bin/python"; // Path of the Python interpreter

/** remove warning that you don't care about */
function cleanWarning(error) {
    return error.replace(/Detector is not able to detect the language reliably.\n/g,"");
}

function callPython(scriptName, args) {
    return new Promise(function(success, reject) {
        const script = pythonDir + scriptName;
        const pyArgs = [script, JSON.stringify(args) ]
        const pyprog = spawn(python, pyArgs );
        let result = "";
        let resultError = "";
        pyprog.stdout.on('data', function(data) {
            result += data.toString();
        });

        pyprog.stderr.on('data', (data) => {
            resultError += cleanWarning(data.toString());
        });

        pyprog.stdout.on("end", function(){
            if(resultError == "") {
                success(JSON.parse(result));
            }else{
                console.error(`Python error, you can reproduce the error with: \n${python} ${script} ${pyArgs.join(" ")}`);
                const error = new Error(resultError);
                console.error(error);
                reject(resultError);
            }
        })
   });
}
module.exports.callPython = callPython;

电话:

const pythonCaller = require("../core/pythonCaller");
const result = await pythonCaller.callPython("preprocessorSentiment.py", {"thekeyYouwant": value});

python:

try:
    argu = json.loads(sys.argv[1])
except:
    raise Exception("error while loading argument")