FastAPI + PostgreSQL Project

This project is a learning exploration of FastAPI, PostgreSQL, and Python best practices, with CRUD operations implemented for a Book entity.

What I Learned

During this project, I explored:

• FastAPI basics: routes, decorators, and syntax (@app.get, @app.put)
• Controllers and service logic: separating route handling from database operations
• Python packages:
  • Pydantic: for data validation and schema definitions
  • SQLAlchemy ORM: for interacting with PostgreSQL using classes and objects
  • Uvicorn: as the ASGI server to run the FastAPI app
• Virtual environments: how to create and use venv in Python to isolate dependencies
• PostgreSQL + pgAdmin: connecting to and managing databases
• Models and Schemas: defining SQLAlchemy models and Pydantic schemas for data structure
• Project structure: organizing the project with app/ folder, models, schemas, routes, services
• Environment variables: storing sensitive data like database URL
• Pydantic BaseSettings: how to manage environment variables and configuration using BaseSettings
• CRUD operations: performing create, read, update, and delete actions for a Book entity
• Key functions and concepts learned: model_dump, declarative_base(), db.add(), db.commit(), unpacking operator (**), response_model, and how they work in practice

Key Points

• Routes handle HTTP requests, call service functions, and return responses
• Controllers/Services contain the business logic for database operations
• Database interactions are done via SQLAlchemy ORM and sessions
• Environment variables keep sensitive data safe and separate from code
• Models and Schemas define how data is structured in the database

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This project helped me understand how to structure a FastAPI project properly, connect to PostgreSQL, manage configuration and secrets, and write clean, modular code.