Async Python Basics: How to Write Scripts That Reduce Wait Times

Async Python offers a programming paradigm that allows scripts to perform tasks concurrently rather than sequentially, which is particularly beneficial for operations involving a lot of network I/O, such as API calls, where synchronous execution leads to inefficiencies due to waiting times. By using async, a Python script can initiate a task and move on to another while waiting for the first to complete, thus optimizing performance and reducing idle time. This is achieved through key concepts like coroutines, the event loop, and the use of the `await` keyword, which pauses a coroutine to allow the event loop to manage other tasks. Using the Infrahub Python SDK as a practical example, the text illustrates how both synchronous and asynchronous methods can be implemented to perform tasks such as creating VLANs, demonstrating that the async approach is advantageous when dealing with multiple operations that can be executed in parallel. The text also highlights the need for async-compatible libraries, like aiohttp or httpx, for making HTTP calls within asynchronous contexts. The Infrahub SDK supports both synchronous and asynchronous operations, and the transition between the two involves minor changes, primarily concerning the client class and the syntax for async operations.