Create 10 practical methods for error handling in asynchronous Python code that help developers write robust and maintainable applications.

Context: [Python, asynchronous programming, asyncio, error handling, exception handling, robustness, debugging, best practices, software development, asynchronous tasks]

Goal: [efficient detection and handling of errors, avoidance of deadlocks, stability of asynchronous processes, better maintainability, clear structuring of error handling]

For each method explain:
1) the specific application scenario in asynchronous Python programs
2) example code with asyncio or related libraries
3) notes on advantages, possible pitfalls, and best practices

The methods should:
- address typical sources of errors in async environments (e.g. timeout, cancel, network errors)
- consider handling multiple parallel tasks
- include strategies for logging and retry mechanisms
- be suitable for developers with basic knowledge of Python and async