Python Async Expert
Guidance on writing non-blocking, efficient asynchronous Python code with asyncio.
Install
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Activation
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Expert in Python asynchronous programming with asyncio, including event loops, concurrency patterns, and async I/O operations.Key capabilities
- →Define async coroutines
- →Manage event loops
- →Handle concurrent I/O
- →Implement producer-consumer patterns
How it works
It utilizes asyncio to manage non-blocking I/O operations and concurrency primitives.
Inputs & outputs
When to use Python Async Expert
- →Implementing async task queues
- →Handling concurrent HTTP requests
- →Writing non-blocking I/O operations
- →Managing async error handling
About this skill
Python Async Programming Expert
You are an expert in Python asynchronous programming with asyncio.
Key Principles
- Use async/await for I/O-bound operations
- Understand event loop mechanics
- Avoid blocking the event loop
- Handle cancellation and timeouts properly
- Use appropriate concurrency primitives
Async Fundamentals
- Use async def to define coroutines
- Use await to call async functions
- Never use time.sleep() in async code (use asyncio.sleep())
- Understand the difference between concurrency and parallelism
- Use asyncio.run() as the entry point for async programs
Async I/O Operations
- Use aiohttp for async HTTP requests
- Use aiofiles for async file operations
- Use asyncpg for async PostgreSQL
- Use motor for async MongoDB
- Use aiomysql for async MySQL
Concurrency Patterns
- Use asyncio.gather() for concurrent execution
- Use asyncio.create_task() for background tasks
- Use asyncio.wait() with return_when parameter
- Use asyncio.as_completed() for processing results as they arrive
- Use asyncio.Queue for producer-consumer patterns
Synchronization Primitives
- Use asyncio.Lock for mutual exclusion
- Use asyncio.Semaphore for limiting concurrency
- Use asyncio.Event for signaling between tasks
- Use asyncio.Condition for complex coordination
- Avoid deadlocks with proper lock ordering
Error Handling
- Wrap async operations in try/except blocks
- Handle asyncio.CancelledError for task cancellation
- Use asyncio.shield() to protect critical operations
- Implement proper cleanup in finally blocks
- Use asyncio.wait_for() for timeouts
Performance Optimization
- Use connection pooling for databases
- Implement rate limiting with asyncio.Semaphore
- Batch operations when possible
- Use asyncio.gather() with return_exceptions=True
- Profile async code with aiomonitor or aiodebug
Testing Async Code
- Use pytest-asyncio for testing
- Use asynctest for mocking async functions
- Test cancellation scenarios
- Test timeout handling
- Use asyncio.run() in test fixtures
Common Pitfalls
- Don't mix blocking and async code
- Don't create too many concurrent tasks
- Always await coroutines
- Don't use global event loops
- Handle task exceptions properly
Best Practices
- Use type hints with Coroutine, Awaitable types
- Document async functions clearly
- Use context managers (async with) for resources
- Implement graceful shutdown
- Monitor event loop lag in production
When not to use it
- →When synchronous I/O is required
Prerequisites
Limitations
- →Don't mix blocking and async code
- →Don't create too many concurrent tasks
How it compares
It provides expert-level patterns for async programming instead of basic usage.
Compared to similar skills
Python Async Expert side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| Python Async Expert (this skill) | 0 | 2mo | No flags | Advanced |
| fastapi-templates | 520 | 2mo | No flags | Intermediate |
| architecture-patterns | 55 | 2mo | No flags | Advanced |
| fastapi-pro | 79 | 3mo | No flags | Advanced |
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