How async/await works in Python
a year ago
- #Python
- #AsyncAwait
- #Concurrency
- Async/await in Python allows programs to perform useful tasks while waiting for I/O operations to complete.
- Understanding async/await requires familiarity with concepts like concurrency, parallelism, event loops, and coroutines.
- Python's implementation of async/await involves generators, native coroutines, and the yield/yield from syntax.
- Concurrency enables a program to handle multiple tasks simultaneously, even if they don't run at the same physical time.
- Thread-based concurrency is easy to implement but doesn't scale well due to high memory usage.
- I/O multiplexing with selectors allows single-threaded programs to handle multiple connections efficiently.
- Generators can be used as coroutines to write concurrent code that resembles synchronous code.
- The yield from syntax simplifies running subgenerators, making coroutine calls more intuitive.
- Async/await, introduced in Python 3.5, provides syntactic sugar over generators to distinguish coroutines from regular functions.
- asyncio is Python's standard library for async programming, offering an event loop and utilities for coroutine management.