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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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Index

Understanding asynchronous capabilities in Flask

Flask is a minimalistic framework in which you can implement your own interpretation of the MVC pattern. The framework is loosely constrained in terms of what you can do, but in its roots Flask is conceived as a Web Server Gateway Interface (WSGI) supported application. WSGI defines a standard interface between HTTP and Python, which means that to deploy a Flask-based solution you need a Web server that handles HTTP requests, translates them into Python through WSGI, and then returns the responses back to the client. Figure 7.2 shows how WSGI applications operate:

Figure 7.2: WSGI application operation

You will notice that in this schema there are two points at which you can address concurrency in your applications: the web server and the application itself. Interestingly, you can test different approaches to handling concurrency approaches, including asynchronous, in some WSGI servers (like Gunicorn https://docs.gunicorn...

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