Lecture on Creating and Testing APIs with Swagger and ChatGPT

Introduction

• Objective: Learn to create API server and test APIs using Swagger with the help of ChatGPT.
• Audience: QA Engineers, Software Developers, and Engineers.
• Presenter: Sergi Kenko, Founder of Kodify QA Boot Camp.

Tools and Technologies

• ChatGPT: Used for assistance in creating the API server.
• Node.js: Platform for running JavaScript on the server-side.
• Swagger: Tool for API documentation and testing.
• Visual Studio Code (VS Code): IDE used for coding.

Setting Up the Environment

1. Register and Log in to ChatGPT
   • Use either free version (3.5) or paid version (4).
2. Download and Set Up VS Code
   • Available for Windows and Mac.

Steps to Create an API Server

1. Initialize the Project
   • Use npm init -y to create a package.json file.
2. Install Dependencies
   • Express: Framework for running the API server.
   • Swagger UI Express: For Swagger UI.
   • YAML JS: To work with YAML file format.
3. Create Server File
   • File: server.js
   • Contains code for running the backend server.
4. Set Up Swagger Documentation
   • File: swagger.yaml
   • Used for defining API documentation in YAML.
5. Update Server File
   • Integrate Swagger UI into the server.

CRUD Operations with Swagger

• CRUD: Create, Read, Update, Delete operations.
• Endpoints:
  • GET: Retrieve data (localhost:port/items).
  • POST: Add new data.
  • PUT: Update existing data.
  • DELETE: Remove data.

Testing APIs with Swagger

1. POST Request
   • Add items with a name and automatically generated ID.
2. GET Request
   • Retrieve all items to verify additions/modifications.
3. PUT Request
   • Update item details using the ID.
4. DELETE Request
   • Remove items by ID.
5. Error Handling
   • Check for not found items with distinct responses.

Explanation of Key Concepts

• Ports: Specify different ports for running multiple servers.
• YAML: Configuration language used for writing Swagger documentation.
• Testing with Swagger: Validate API operations and responses.

Conclusion

• Encouragement: Like, comment, and share the video.
• Additional Learning: Links for further courses provided.