fastapi-patterns
Master production-grade FastAPI development through organized project layouts, Pydantic v2 validation, dependency injection patterns, and async request handling. This skill covers authentication, authorization, transactional service layers, and testing strategies to build scalable applications.
fastapi-patterns teaches production-ready FastAPI architecture with dependency injection, async patterns, and organized project layouts.
AI-generated summary based on this skill's SKILL.md
Decision gist · record as of 2026-07-27
fastapi-patterns teaches production-ready FastAPI architecture with dependency injection, async patterns, and organized project layouts. Master production-grade FastAPI development through organized project layouts, Pydantic v2 validation, dependency injection patterns, and async request handling. This skill covers authentication, authorization, transactional service layers, and testing strategies to build scalable applications.
Use it when
- fastapi-patterns covers implementing authentication and authorization using JWT tokens and OAuth2 bearer schemes.
- Yes.
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Install
affaan-m/ECC/fastapi-patterns · repository language: JavaScript
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Frequently asked questions
AI-generated answers based on this skill's SKILL.md and metadata
What fastapi project structure does fastapi-patterns teach?
fastapi-patterns teaches production-grade project organization including layered architecture with routers, service layers, and database modules. You'll learn how to structure FastAPI apps for scalability, using dependency injection for clean separation of concerns, async patterns for efficient request handling, and middleware configuration for CORS and error handling.
How does fastapi-patterns cover authentication with JWT?
fastapi-patterns covers implementing authentication and authorization using JWT tokens and OAuth2 bearer schemes. The skill includes password hashing with bcrypt, token generation and validation, dependency injection for protecting routes, and role-based access control patterns to secure your FastAPI endpoints.
Does fastapi-patterns include async database operations?
Yes. fastapi-patterns teaches setting up async database operations with SQLAlchemy, including session management, transactional service layers, and proper connection pooling. You'll learn patterns for async queries, transaction handling, and integrating async ORM operations seamlessly with FastAPI's async request lifecycle.
What testing approach does fastapi-patterns demonstrate?
fastapi-patterns covers comprehensive testing using httpx for async HTTP client testing and pytest with fixtures for test organization. You'll learn how to write integration tests for your FastAPI endpoints, mock dependencies, test authentication flows, and structure test suites for maintainability.
How does fastapi-patterns apply Pydantic v2 validation?
fastapi-patterns teaches Pydantic v2 schema design for request validation, response serialization, and data transformation. You'll learn modern Pydantic patterns including field validators, computed fields, and schema configuration to ensure type-safe, validated data throughout your FastAPI application.
What production patterns are covered in fastapi-patterns?
fastapi-patterns covers production-ready patterns including error handling strategies, pagination with offset/limit, dependency injection for reusable logic, middleware configuration, and service layer design. These patterns ensure your FastAPI applications are scalable, maintainable, and follow industry best practices.
SKILL.md
Rendered from the published skill. Quoted content, verbatim.
FastAPI Patterns
Modern, production-grade FastAPI development: project layout, Pydantic v2 schemas, dependency injection, async patterns, auth, transactional service methods, and testing.
Project Structure
my_app/
|-- app/
| |-- main.py # App factory, lifespan, middleware
| |-- config.py # Settings via pydantic-settings
| |-- dependencies.py # Shared FastAPI dependencies
| |-- database.py # SQLAlchemy engine + session
| |-- routers/
| | `-- users.py
| |-- models/ # SQLAlchemy ORM models
| | `-- user.py
| |-- schemas/ # Pydantic request/response schemas
| | `-- user.py
| `-- services/ # Business logic layer
| `-- user_service.py
|-- tests/
| |-- conftest.py
| `-- test_users.py
|-- pyproject.toml
`-- .env
App Factory and Lifespan
```python
app/main.py
from
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