Does this skill support MongoDB?

Yes, it includes patterns for the Motor driver, which is the recommended asynchronous driver for MongoDB in Python applications.

When should I use async vs sync in FastAPI?

Use 'async def' for I/O-bound tasks like database queries or external API calls to prevent blocking the event loop. Use 'def' for CPU-bound tasks or when using libraries that do not support asyncio.

How are background tasks handled?

The skill provides patterns for using FastAPI's built-in BackgroundTasks class to perform operations after returning a response, such as sending emails or logging.

Can I use this for real-time notifications?

Absolutely. It includes implementation patterns for both WebSockets (bidirectional) and Server-Sent Events (SSE) for one-way server-to-client streaming.

FastAPI Async Patterns

Name: FastAPI Async Patterns
Author: TheBushidoCollective

byTheBushidoCollective

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API Development

Implements high-performance asynchronous patterns in FastAPI to handle concurrent requests and optimize resource usage.

About

This skill equips Claude with the expertise to design and implement efficient, non-blocking APIs using FastAPI's asynchronous capabilities. It provides standardized patterns for async route handlers, database integrations (including SQLAlchemy, asyncpg, and Motor), background tasks, and real-time communication protocols like WebSockets and Server-Sent Events (SSE). By applying these patterns, developers can ensure their backend services remain responsive under high concurrency and handle I/O-bound operations with minimal latency.

Key Features

Streaming response techniques for large files and live data feeds
Background task management for fire-and-forget operations
39 GitHub stars
Optimized async vs. sync route handler implementations
Real-time bidirectional communication via WebSocket managers
Asynchronous database patterns for SQL and NoSQL environments

Use Cases

Developing non-blocking microservices that interact with multiple external APIs
Building high-concurrency real-time dashboards and chat systems
Optimizing data-intensive applications using asynchronous ORMs and database drivers

About

Key Features

Streaming response techniques for large files and live data feeds
Background task management for fire-and-forget operations
39 GitHub stars
Optimized async vs. sync route handler implementations
Real-time bidirectional communication via WebSocket managers
Asynchronous database patterns for SQL and NoSQL environments

Use Cases

Developing non-blocking microservices that interact with multiple external APIs
Building high-concurrency real-time dashboards and chat systems
Optimizing data-intensive applications using asynchronous ORMs and database drivers