What is this book about?

During those last years, I've been able to contribute to the biggest open source project written in Python – namely OpenStack. During that time, I had the opportunity to learn a lot of things about writing scalable code, by reaching the boundaries of Python and its ecosystem, and by rubbing shoulders with some of the greatest Python developers – some of them being developer of the Python language itself.

After doing tons of code reviews and mentoring with my fellow engineers, I decided it was time to teach everyone what should be known about Python to achieve large scalability.

Distributed and resilient applications with Python

In The Hacker's Guide to Scaling Python I want to share what I learned those last years working on distributed applications in Python. It takes years of practice, research, trial and errors to build experience and knowledge along the way. Simple questions such as "How do I make my code faster?" or "How do I make sure there is no bottleneck?" cost hours to find good answers. Without enough background on the topic, you'll never be sure that any answer you'll come up with will be correct.

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About the author

Hi, I'm Julien Danjou, a Free Software hacker for more than 16 years now. I wear a lot of different hats in the open source ecosystem, and maybe you already encountered me or used one of my software: I am a Debian developer for 15 years, a Freedesktop contributor, a GNU Emacs committer, and the awesome window manager creator.

These last 10 years, I've been developing software using Python. Five years ago, I started to work on OpenStack, a cloud platform written in Python and the largest existing open source Python code base (2.5 millions of lines of Python) – where I am one of the Project Team Leader and acted as a member of the Technical Committee.

This book is the next step after The Hacker's Guide to Python – my previous book originally published in 2014 and appraised by thousands of Python developers. In this, I wrote everything I knew about writing state of the art Python code, for people that want to learn Python beyond basics.