Skip to content

Latest commit

 

History

History
44 lines (26 loc) · 2.16 KB

README.md

File metadata and controls

44 lines (26 loc) · 2.16 KB

Overview

This project is a Django-based application designed to serve as a learning platform for utilizing GitHub Copilot in software development. The application features a series of labs that guide users through the process of creating API routes, generating sample data, and testing APIs. The project aims to demonstrate the power of GitHub Copilot in streamlining development tasks and enhancing productivity.

Getting Started

Before diving into the labs, ensure you have Django installed and the project's dependencies are set up. Navigate to the project's root directory and run the following commands:

cd copilot
python -m pip install -r requirements.txt

To start the server, execute:

python manage.py runserver

Labs Overview

In this lab, participants will learn how to add a new API route to the Django application. The new route will return a simple "Hello World" JSON response. This lab also includes writing tests for the new route to ensure it behaves as expected.

This lab focuses on generating sample data for the application. Participants will create an API that lists Microsoft Azure VMs information, fetched from a local JSON file. This lab covers the entire flow from generating the sample data to testing the new API endpoint.

The details for Lab 3 are not provided in the context. However, based on the naming convention, it's likely focused on creating a homepage for the Django application, possibly involving front-end development aspects and integrating the APIs developed in previous labs.

Testing

The project includes a suite of tests to validate the functionality of the API routes. To run the tests, ensure the server is not running and execute:

python manage.py test

Conclusion

This project serves as a practical guide to leveraging GitHub Copilot in developing and testing web applications. Through a series of hands-on labs, participants will gain insights into efficient coding practices and automated testing strategies.