AniWorld Project Overview

📁 Folder Structure

The project follows a modular, layered architecture inspired by MVC and Clean Architecture principles. The main directories are:

src/
  controllers/    # API endpoints and route handlers
  services/       # Business logic and orchestration
  repositories/   # Data access layer (DB, external APIs)
  schemas/        # Pydantic models for validation/serialization
  utils/          # Utility functions and helpers
  config/         # Configuration management (env, settings)
tests/
  unit/           # Unit tests for core logic
  integration/    # Integration tests for end-to-end scenarios

🏗️ Architecture

MVC & Clean Architecture: Separation of concerns between controllers (views), services (business logic), and repositories (data access).
Dependency Injection: Used for service/repository wiring, especially with FastAPI's Depends.
Event-Driven & Microservices Ready: Modular design allows for future scaling into microservices or event-driven workflows.
Centralized Error Handling: Custom exceptions and error middleware for consistent API responses.

🧰 Used Libraries & Frameworks

Python (PEP8, PEP257, type hints)
FastAPI: High-performance async web API framework
Pydantic: Data validation and serialization
Poetry: Dependency management and packaging
dotenv / os.environ: Environment variable management
logging / structlog: Structured logging
pytest / unittest: Testing frameworks
aiohttp: Async HTTP client (where needed)
SQLAlchemy / asyncpg / databases: Database ORM and async drivers (if present)
Prometheus: Metrics endpoint integration
Other: As required for integrations (webhooks, third-party APIs)

🧩 Patterns & Conventions

Repository Pattern: All data access is abstracted via repositories.
Service Layer: Business logic is encapsulated in services, not controllers.
Pydantic Models: Used for all input/output validation.
Async Endpoints: All I/O-bound endpoints are async for scalability.
Environment Configuration: All secrets/configs are loaded from .env or environment variables.
Logging: All logs are structured and configurable.
Testing: High coverage with fixtures and mocks for external dependencies.

🛡️ Security & Performance

JWT Authentication: Secure endpoints with token-based auth.
Input Validation: All user input is validated via Pydantic.
No Hardcoded Secrets: All sensitive data is externalized.
Performance Optimization: Async I/O, caching, and profiling tools.

🎨 UI & CLI

Theme Support: Light/dark/auto modes.
Accessibility: Screen reader, color contrast, keyboard shortcuts.
CLI Tool: For bulk operations, scanning, and management.

📚 References

For details on individual features and endpoints, see features.md.

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