Backend Project Structure

The backend project is organized as follows:

backend/
│
├── app/
│   ├── api/
│   │   ├── controllers/
│   │   │   └── config/
│   │   └── ...
│   ├── client/
│   │   └── ...
│   ├── datagenerator/
│   │   └── ...
│   ├── harness/
│   │   └── ...
│   ├── middlewares/
│   │   └── ...
│   └── schemas/
│       └── ...
├── database/
│   └── ...
├── dependencies/
│   └── ...
├── logs/
│   └── ...
├── models/
│   └── ...
├── repository/
│   └── ...
├── routes/
│   └── ...
├── services/
│   └── ...
├── utils/
│   └── ...
├── .env
├── main.py
├── settings.py
├── .gitignore
├── README.md
└── requirements.txt

Directory Descriptions

• app: The main application package.
  • api: Contains API-related code and endpoints.
    • controllers: Individual API Controllers (endpoints) are defined here.
  • schemas: Contains data models or Pydantic models.
  • services: Houses business logic or service layer components.
  • utils: Contains utility functions or helper modules.
• database: Handles database-related code, such as database connection and schemas.
• dependencies: Contains dependencies or dependency providers.
• main.py: Entry point of the application.
• routes: Base Routes Configuration.
• settings.py: Configuration settings for the application.
• logs: Directory for application logs.
• tests: Contains test modules and test cases.
• .env: Environment variables for the project.
• .gitignore: Specifies the files and directories to be ignored by Git.
• requirements.txt: List of project dependencies.

Technologies Used

• FastAPI: A modern, fast (high-performance) web framework for building APIs with Python 3.7+ based on standard Python type hints.
• Pydantic: Used for data validation and settings management through Python type annotations.
• Uvicorn: A lightning-fast ASGI server implementation, using uvloop and httptools.
• SQLAlchemy: The SQL toolkit and Object-Relational Mapping (ORM) system for Python.
• Alembic: A lightweight database migration tool for use with SQLAlchemy.
• Python Dotenv: For loading environment variables from a .env file.
• Pydantic-Settings: For enhanced settings management with Pydantic.
• Logging: Python’s built-in logging module for tracking application behavior and errors.