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
/*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。
其他回答
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
有Python背景，想要在Node.js应用程序中集成机器学习模型的人:
它使用了child_process核心模块:
const express = require('express')
const app = express()
app.get('/', (req, res) => {
const { spawn } = require('child_process');
const pyProg = spawn('python', ['./../pypy.py']);
pyProg.stdout.on('data', function(data) {
console.log(data.toString());
res.write(data);
res.end('end');
});
})
app.listen(4000, () => console.log('Application listening on port 4000!'))
它不需要Python脚本中的sys模块。
下面是使用Promise执行任务的更模块化的方式:
const express = require('express')
const app = express()
let runPy = new Promise(function(success, nosuccess) {
const { spawn } = require('child_process');
const pyprog = spawn('python', ['./../pypy.py']);
pyprog.stdout.on('data', function(data) {
success(data);
});
pyprog.stderr.on('data', (data) => {
nosuccess(data);
});
});
app.get('/', (req, res) => {
res.write('welcome\n');
runPy.then(function(fromRunpy) {
console.log(fromRunpy.toString());
res.end(fromRunpy);
});
})
app.listen(4000, () => console.log('Application listening on port 4000!'))
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")
/*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。
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()
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