Genjuro
Genjuro

Reputation: 7745

How to call a Python function from Node.js

I have an Express Node.js application, but I also have a machine learning algorithm to use in Python. Is there a way I can call Python functions from my Node.js application to make use of the power of machine learning libraries?

Upvotes: 350

Views: 361417

Answers (14)

CherryDT
CherryDT

Reputation: 29062

You can use the node-calls-python module! The difference to child-process-based solutions is that this runs the Python code in-process, which is faster and allows much more flexibility because you can run individual functions within modules and you can pass data around more easily, including full-fledged Python objects (with support to call its methods).

python.py:

def add(a, b):
    return a + b

index.js:

import { interpreter as py } from 'node-calls-python'

const myModule = await py.load('./python.py')

console.log(await py.call(myModule, 'add', 1, 2)) // 3

In case this is more convenient and the operation you do does not take long, you could also use the synchronous method instead of the asynchronous one:

console.log(py.callSync(myModule, 'add', 1, 2)) // 3

You can of course also create nice JS function wrappers that call Python functions to make the integration more seamless. Check the docs linked above for more info such as how to create and use Python objects within JS, how to pass kwargs and more.

Upvotes: 1

Criminal_Affair_At_SO
Criminal_Affair_At_SO

Reputation: 3443

In 2023 I would also recommend you pymport.

It allows for total compatibility of all Python code with Node.js, including the binary modules. Unlike the other modules, it does not spawn a separate Python process - both the Python code and the Node.js code co-exist in a single shared memory process with synchronized garbage collectors.

npm install pymport
npx pympip3 install numpy

then simply in JavaScript:

const { pymport, proxify } = require('pymport');
const np = proxify(pymport('numpy'));

const a = np.array([2, 3, 4]);
console.log(a.toString());

(I am its author)

Upvotes: 3

Guy-dev
Guy-dev

Reputation: 31

you can check out my package on npm https://www.npmjs.com/package/@guydev/native-python

it provides a very simple and powerful way to run python functions from node

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 module

# 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'}

Upvotes: 1

theJoestJoeToEverJoe
theJoestJoeToEverJoe

Reputation: 4354

Easiest way I know of is to use "child_process" package which comes packaged with node.

Then you can do something like:

const spawn = require("child_process").spawn;
const pythonProcess = spawn('python',["path/to/script.py", arg1, arg2, ...]);

Then all you have to do is make sure that you import sys in your python script, and then you can access arg1 using sys.argv[1], arg2 using sys.argv[2], and so on.

To send data back to node just do the following in the python script:

print(dataToSendBack)
sys.stdout.flush()

And then node can listen for data using:

pythonProcess.stdout.on('data', (data) => {
 // Do something with the data returned from python script
});

Since this allows multiple arguments to be passed to a script using spawn, you can restructure a python script so that one of the arguments decides which function to call, and the other argument gets passed to that function, etc.

Hope this was clear. Let me know if something needs clarification.

Upvotes: 410

Muhammad Ahmed Hassan
Muhammad Ahmed Hassan

Reputation: 539

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 }
}

For more information visit official Nodejs child process page: https://nodejs.org/api/child_process.html#child_processexeccommand-options-callback

Upvotes: 0

Extreme
Extreme

Reputation: 364

Many of the examples are years out of date and involve complex setup. You can give JSPyBridge/pythonia a try (full disclosure: I'm the author). It's vanilla JS that lets you operate on foreign Python objects as if they existed in JS. In fact, it does interoperability so Python code can in return call JS through callbacks and passed functions.

numpy + matplotlib example, with the ES6 import system:

import { py, python } from 'pythonia'
const np = await python('numpy')
const plot = await python('matplotlib.pyplot')

// Fixing random state for reproducibility
await np.random.seed(19680801)
const [mu, sigma] = [100, 15]
// Inline expression evaluation for operator overloading
const x = await py`${mu} + ${sigma} * ${np.random.randn(10000)}`

// the histogram of the data
const [n, bins, patches] = await plot.hist$(x, 50, { density: true, facecolor: 'g', alpha: 0.75 })
console.log('Distribution', await n) // Always await for all Python access
await plot.show()
python.exit()

Through CommonJS (without top level await):

const { py, python } = require('pythonia')
async function main() {
  const np = await python('numpy')
  const plot = await python('matplotlib.pyplot')
  ...
  // the rest of the code
}
main().then(() => python.exit()) // If you don't call this, the process won't quit by itself.

Upvotes: 14

Soumik Rakshit
Soumik Rakshit

Reputation: 889

The python-shell module by extrabacon is a simple way to run Python scripts from Node.js with basic, but efficient inter-process communication and better error handling.

Installation:

With npm: npm install python-shell.

Or with yarn: yarn add python-shell

Running a simple Python script:

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

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

Running a Python script with arguments and options:

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);
});

For the full documentation and source code, check out https://github.com/extrabacon/python-shell

Upvotes: 63

Yorkie
Yorkie

Reputation: 69

The Boa is good for your needs, see the example which extends Python tensorflow keras.Sequential class in JavaScript.

const fs = require('fs');
const boa = require('@pipcook/boa');
const { tuple, enumerate } = boa.builtins();

const tf = boa.import('tensorflow');
const tfds = boa.import('tensorflow_datasets');

const { keras } = tf;
const { layers } = keras;

const [
  [ train_data, test_data ],
  info
] = tfds.load('imdb_reviews/subwords8k', boa.kwargs({
  split: tuple([ tfds.Split.TRAIN, tfds.Split.TEST ]),
  with_info: true,
  as_supervised: true
}));

const encoder = info.features['text'].encoder;
const padded_shapes = tuple([
  [ null ], tuple([])
]);
const train_batches = train_data.shuffle(1000)
  .padded_batch(10, boa.kwargs({ padded_shapes }));
const test_batches = test_data.shuffle(1000)
  .padded_batch(10, boa.kwargs({ padded_shapes }));

const embedding_dim = 16;
const model = keras.Sequential([
  layers.Embedding(encoder.vocab_size, embedding_dim),
  layers.GlobalAveragePooling1D(),
  layers.Dense(16, boa.kwargs({ activation: 'relu' })),
  layers.Dense(1, boa.kwargs({ activation: 'sigmoid' }))
]);

model.summary();
model.compile(boa.kwargs({
  optimizer: 'adam',
  loss: 'binary_crossentropy',
  metrics: [ 'accuracy' ]
}));

The complete example is at: https://github.com/alibaba/pipcook/blob/master/example/boa/tf2/word-embedding.js

I used Boa in another project Pipcook, which is to address the machine learning problems for JavaScript developers, we implemented ML/DL models upon the Python ecosystem(tensorflow,keras,pytorch) by the boa library.

Upvotes: 4

nas_levente
nas_levente

Reputation: 21

/*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);
}); 

This worked for me. Your python.exe must be added to you path variables for this code snippet. Also, make sure your python script is in your project folder.

Upvotes: 2

Geordie
Geordie

Reputation: 2184

You can now use RPC libraries that support Python and Javascript such as zerorpc

From their front page:

Node.js Client

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 Server

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()

Upvotes: 21

bormat
bormat

Reputation: 1379

Most of previous answers call the success of the promise in the on("data"), it is not the proper way to do it because if you receive a lot of data you will only get the first part. Instead you have to do it on the end event.

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;

Call:

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")

Upvotes: 9

Jonathan
Jonathan

Reputation: 7128

You could take your python, transpile it, and then call it as if it were javascript. I have done this succesfully for screeps and even got it to run in the browser a la brython.

Upvotes: 3

1mike12
1mike12

Reputation: 3453

I'm on node 10 and child process 1.0.2. The data from python is a byte array and has to be converted. Just another quick example of making a http request in python.

node

const process = spawn("python", ["services/request.py", "https://www.google.com"])

return new Promise((resolve, reject) =>{
    process.stdout.on("data", data =>{
        resolve(data.toString()); // <------------ by default converts to utf-8
    })
    process.stderr.on("data", reject)
})

request.py

import urllib.request
import sys

def karl_morrison_is_a_pedant():   
    response = urllib.request.urlopen(sys.argv[1])
    html = response.read()
    print(html)
    sys.stdout.flush()

karl_morrison_is_a_pedant()

p.s. not a contrived example since node's http module doesn't load a few requests I need to make

Upvotes: 5

Amit Upadhyay
Amit Upadhyay

Reputation: 7401

Example for people who are from Python background and want to integrate their machine learning model in the Node.js application:

It uses the child_process core module:

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!'))

It doesn't require sys module in your Python script.

Below is a more modular way of performing the task using Promise:

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!'))

Upvotes: 232

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