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Asynchronous Programming in Python

Asynchronous Programming in Python

By : Nicolas Bohorquez
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Asynchronous Programming in Python

Asynchronous Programming in Python

By: Nicolas Bohorquez

Overview of this book

Asynchronous programming is one of the most effective but often misunderstood techniques for building fast, scalable, and responsive systems in Python. While it can significantly improve performance, efficiency, and sustainability, using async without a clear understanding of its trade-offs can lead to fragile designs and hard-to-debug issues. This book offers a structured approach to applying asynchronous programming in Python. It begins with a conceptual framework to help you distinguish between synchronous and asynchronous execution models, and shows how async relates to other concurrency strategies such as multithreading and multiprocessing. From there, you will explore the core tools available for building async applications in Python. You will also learn how to measure the impact of async programming in practical scenarios, profile and debug asynchronous code, and evaluate performance improvements using real-world metrics. The final chapters focus on applying async techniques to common cloud-based systems, such as web frameworks, database interactions, and data-pipelines tools. Designed for developers looking to apply async programming with confidence, this book blends real-world examples with core concepts to help you write efficient, maintainable Python code.
Table of Contents (14 chapters)
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12
Other Books You May Enjoy
13
Index

Summary

In this chapter we have navigated through some of the most common implementation errors that can be incurred when you use asynchronous programming with the standard asyncio library. These errors can have a direct impact on the performance of your solutions and serve to remind us that asynchronous programming doesn't invariably imply better performance instantly. To summarize the practices presented in this chapter:

  • Do not mix blocking code inside asynchronous coroutines/tasks
  • Avoid waiting for a coroutine or task to finish before launching another one
  • Favor launching enough tasks concurrently to maximize the usage of the underlying resources
  • Do not launch a huge number of small tasks, to avoid incuring unnecessary context switching between them
  • Apply consistent management of exceptions inside the coroutines/tasks and proper handling of exceptions in parent threads
  • Separate logging tasks from the main execution thread to maximize the throughput of your solutions

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