Leveraging Generators for Improved Asynchronous Programming in Python

Discover how combining generators and async/await enhances concurrent tasks handling

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Introduction

Python has become increasingly popular among developers due to its simplicity and versatility, especially regarding web development and asynchronous programming. One lesser-known but essential technique combines two powerful language features — generators and async/await.

In this article, we will learn why these pairings improve asynchronous programming efficiency and readability by exploring theory and providing updated code examples. Let’s get started!

Why Combine Generators & Async/Await?

Before diving into specifics, understanding why these technologies work well together is crucial. Here are three main reasons behind this synergy:

• Efficiency: Generators allow lazy evaluation, consuming less memory compared to holding complete results in RAM. When combined with async functionality, they enable better resource management and lower latency.
• Simplicity: Using familiar constructs such as yield simplifies complex callback chains typically found in asynchronous codebases.