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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
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Index

Using coroutines in asynchronous programming

Coroutines have evolved to be the unit of concurrency in asynchronous programming in Python. Because they are executed in a single thread they are not constrained by the global interpreter lock (GIL), and task switching is more lightweight than the same operation executed on threads or processes. Coroutines are suitable for many modern use cases that involve non-blocking I/O operations over data streams or network connections.

Support for asynchronous coroutines has also evolved. In early versions of Python (up to CPython 3.4), the recommended way to develop asynchronous capabilities for coroutines was to use the @asyncio.coroutine decorator over coroutine functions. This changed with the inclusion of the asyncio module in CPython 3.4 and the addition of the async/await expressions in CPython 3.5.

Important note

Since the asyncio.coroutine decorator has been deprecated in CPython 3.8 and removed in 3.11, we are going...

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