What is a productive approach for utilizing Async SQLAlchemy in Python?

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Here are some productive approaches for utilizing Async SQLAlchemy in Python:

1. Use async/await: Async SQLAlchemy is designed for asynchronous programming, so it's best to use async/await syntax. This syntax allows you to write asynchronous code that's easy to read and understand.

2. Utilize SQLAlchemy Core: SQLAlchemy Core is a lower-level abstraction layer that provides more control over database interaction. It also allows you to write SQL statements directly, which can be beneficial for performance.

3. Leverage Connection Pooling: Connection pooling is a technique that allows you to reuse database connections instead of opening and closing them every time you need to interact with the database. This can improve performance and reduce the number of resources used.

4. Use Context Managers: Async SQLAlchemy has built-in support for context managers. Using a context manager can simplify your code and ensure that database resources are properly closed after you're done with them.

5. Avoid Global Variables: When using async programming, global variables can cause issues with race conditions and unexpected behavior. Instead, pass variables around as function arguments or use a dependency injection framework like Flask-DI.