Python is a wonderful programming language that allows writing applications quickly. But how do you make those applications scale for thousands of users and requests? 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. The Hacker's Guide to Scaling Python will help you solve that by providing guidelines, tips and best practice. Adding a few interview of experts on the subject, you will learn how you can distribute your Python application so it is able to process thousands of requests.
A Free Software hacker since 1999. He wears multiple hats in the Free and Open Source community, among them: Debian developer, Freedesktop contributor, GNU Emacs committer, the awesome window manager creator, Project Technical Leader for OpenStack Telemetry and contributor to Python.
For the last few years, he has been hacking using Python a lot, especially when working on OpenStack, a cloud-computing platform. During that time, He had the chance to work with many fabulous Python hackers, and learned a lot from them and the surrounding community.
Meh. While it contains some good information for things like performance profiling and multithreading, it's generally such a cursory overview of each topic that it's not really all that useful to someone at my level. Either I already know a chapter in much greater depth (e.g. PaaS, where I've used every service they describe for years....it even contains an error where it shows the Heroku dashboard instead of the EBS at one point), it's something I don't really need for what I do (e.g. locking), or it's such a brief overview that it doesn't do anything but make me need to seek out more thorough resources.
There are hit and misses in the book. Some of them provide good concept, and some of them not. Also most of the concept and examples of the book related to external libraries, not to the core of the Python. I wish book would go to more details of each chapter. Make sure you read PDF format of the book. MOBY format is not very well formatted.
I gave this five stars mainly for the interviews at the end of the chapters with experienced coders and core maintainers of the language. This provides valuable insight and a style that I have not seen in other books.
It'd be great reference book, but it's quite opinionated, not very deep coverage of different topics and code contains errors (e.g. snippet with aiohttp).
Given that, basic price of $39 is maybe justified, but hardly more expensive packages ($49-$199).