How to Execute R Machine Learning Model using Python REST API

Published: 23 November 2023
on channel: CodeGPT

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Certainly! Executing an R machine learning model using a Python REST API involves integrating R and Python, and leveraging RESTful APIs for communication. In this tutorial, we'll go through the steps of creating a simple example using the plumber package in R for creating a REST API, and the requests library in Python for making HTTP requests.
Make sure you have the necessary packages installed. In R, install the plumber package:
In Python, install the requests library:
Create an R script (e.g., ml_api.R) with a simple Plumber API that uses a pre-trained model. For demonstration purposes, let's assume you have a model that predicts the price of a house based on its size.
Run the R script in your R environment. This will start a local server at http://localhost:8000.
Create a Python script (e.g., python_client.py) that sends a request to the API using the requests library:
Run the Python script. It should make a request to the R API, and you should see the predicted price printed in the console.
This example demonstrates a simple integration of an R machine learning model with a Python script through a REST API. Depending on your actual use case and model, you may need to adjust the code accordingly.
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