Gain insights into using Python to consume and create REST APIs, delving into HTTP methods like GET and PUT. Ideal for enhancing intermediate Python skills.

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REST is the most used mechanism to publish APIs for general consumption. Each language has its own set of libraries and methods that help a developer consume these APIs. This course will teach you how to use Python and its libraries for consuming and creating REST APIs in the easiest way possible.

In the first part of this course, you’ll learn how to work with Python in using REST APIs for various scenarios. Then, in the second part, you’ll focus on building your own REST APIs using the HTTP methods, including GET, PUT, etc.

This course is geared toward intermediate users who have a basic understanding of Python and want to improve their skills in using existing REST APIs and building their REST API implementations.

Python REST API Development: A Comprehensive Guide

Until now, we've just been printing out the response content (the response body) as a string. That's fine when trying to understand the structure of the body. However, once ready to use the response body as part of our application, we'll require a way to extract the data into our application's data model objects.

Since JSON is the most commonly used format for the response content, we'll be focusing on working with the body in JSON format. We'll be using the air quality service provided by MET Norway. The URI is as follows: 

https://api.met.no/weatherapi/airqualityforecast/0.1/stations.

Python provides a JSON library that can convert a JSON string into a Python dictionary (`dict`). Let's see how to use the JSON library to extract data from the MET Norway service.

Understand how to use Python's built-in JSON library to parse response data.

Introduction

Client

Server

Project: Tickets API

Conclusion

Consume Response Content