So to run above Python script, provided it is called script.py, we could add following to out server.js:Ĭonst path = require ( ' path ' ) const ) server. The child_process.spawn() method spawns a new process using the given command, with command line arguments in args. One of the accessible commands provided in Node.js API is child_process.spawn(). Lets start with the former by creating simple Node.js program, call it server.js and prepare to fill in the code. $ python script.py -h - prints help text.$ python script.py -foo sometext - similar as above.$ python script.py -f sometext - pass sometext as a value for option foo.We do not want to use it sequentially in a webapp as this might takes quite long time to execute. argv )Ībove script will not execute immediately which makes it necessary to hold on to the process and read from its output until it finishes. ctime ()) if _name_ = "_main_" : main ( sys. sleep ( 5 ) print ( argument ) print ( "End : %s" % time. exit () elif opt in ( "-f", "-foo" ): argument = arg # print output exit ( 2 ) for opt, arg in opts : if opt = '-h' : print ( usage ) sys. Import sys, getopt, time def main ( argv ): argument = '' usage = 'usage: script.py -f ' # parse incoming arguments You could also go directly to the Github repository which contains sample node server implementation ivarprudnikov/use-python-in-node Python scriptįor the purpose of my example I will use a simple Python script which outputs messages to standard output along the way: I’ve written about it as well in another post “Run Tensorflow scripts from Node.js server deployed on AWS as Docker container” It uses a Python script which is an implementation of Recurrent Neural Network (RNN) character generator written in Tensorflow framework. I still managed to wrap that half finished attempt in Docker and deploy to AWS though.Īnother more elaborate and a bit more successful implementation of this idea using Node.js can be found in Github repository ivarprudnikov/char-rnn-tensorflow. Writing webapp with Flask, which is one of the popular choices among Python developers, was a tedious experience for me compared to development process with Express( Node.js) or Spring Boot( Java). There was an attempt to use Python alone for both the server and scripting, unfortunately it failed, most likely due to the fact that I am mostly Javascript / Java programmer these days. So I decided to write an example of how would it look like to be able to call Python scripts from withing a running server application, hence this article. Unfortunately I was not aware of any obvious way to easily reuse those scripts in a webapp. Latter allows writing and running and executing scripts in a browser window. A while back ago I was learning/playing with machine/deep learning but all that was only in Python, in a Jupyter Notebook.
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