Skip to content
Related Articles

Related Articles

Improve Article

Python | Build a REST API using Flask

  • Difficulty Level : Easy
  • Last Updated : 02 Aug, 2019

Prerequisite: Introduction to Rest API

REST stands for REpresentational State Transfer and is an architectural style used in modern web development. It defines a set or rules/constraints for a web application to send and receive data.

In this article, we will build a REST API in Python using the Flask framework. Flask is a popular micro framework for building web applications. Since it is a micro-framework, it is very easy to use and lacks most of the advanced functionality which is found in a full-fledged framework. Therefore, building a REST API in Flask is very simple.

There are two ways of creating a REST API in Flask:

  1. Using Flask without any external libraries
  2. Using flask_restful library

Libraries required:

flask_restful can be installed via the pip command:

 sudo pip3 install flask-restful 

Method 1: using only Flask

Here, there are two functions: One function to just return or print the data sent through GET or POST and another function to calculate the square of a number sent through GET request and print it.

# Using flask to make an api
# import necessary libraries and functions
from flask import Flask, jsonify, request
# creating a Flask app
app = Flask(__name__)
# on the terminal type: curl
# returns hello world when we use GET.
# returns the data that we send when we use POST.
@app.route('/', methods = ['GET', 'POST'])
def home():
    if(request.method == 'GET'):
        data = "hello world"
        return jsonify({'data': data})
# A simple function to calculate the square of a number
# the number to be squared is sent in the URL when we use GET
# on the terminal type: curl / home / 10
# this returns 100 (square of 10)
@app.route('/home/<int:num>', methods = ['GET'])
def disp(num):
    return jsonify({'data': num**2})
# driver function
if __name__ == '__main__': = True)


Executing the square function:

Method 2: Using flask-restful

Flask Restful is an extension for Flask that adds support for building REST APIs in Python using Flask as the back-end. It encourages best practices and is very easy to set up. Flask restful is very easy to pick up if you’re already familiar with flask.

In flask_restful, the main building block is a resource. Each resource can have several methods associated with it such as GET, POST, PUT, DELETE, etc. for example, there could be a resource that calculates the square of a number whenever a get request is sent to it. Each resource is a class that inherits from the Resource class of flask_restful. Once the resource is created and defined, we can add our custom resource to the api and specify a URL path for that corresponding resource.

# using flask_restful
from flask import Flask, jsonify, request
from flask_restful import Resource, Api
# creating the flask app
app = Flask(__name__)
# creating an API object
api = Api(app)
# making a class for a particular resource
# the get, post methods correspond to get and post requests
# they are automatically mapped by flask_restful.
# other methods include put, delete, etc.
class Hello(Resource):
    # corresponds to the GET request.
    # this function is called whenever there
    # is a GET request for this resource
    def get(self):
        return jsonify({'message': 'hello world'})
    # Corresponds to POST request
    def post(self):
        data = request.get_json()     # status code
        return jsonify({'data': data}), 201
# another resource to calculate the square of a number
class Square(Resource):
    def get(self, num):
        return jsonify({'square': num**2})
# adding the defined resources along with their corresponding urls
api.add_resource(Hello, '/')
api.add_resource(square, '/square/<int:num>')
# driver function
if __name__ == '__main__': = True)


 Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.  

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning – Basic Level Course

My Personal Notes arrow_drop_up
Recommended Articles
Page :