High Performance Python by Micha Gorelick and Ian Ozsvald
To a causal user of python, this book might not seem interesting or handful, but if one is working on an application that desires the maximum effeciency out of computer, no matter how the code is structured, there is a need to go deeper and find out how the code actually works and this starts from knowing how to best write the code that ensures minimum of cpu cycles and ram.
The book starts with an overview of the various data structures and libraries that python offers as well as detailing the internal structure of various computer architecture. It then moves on to profiling and detecting bottlenecks both via memory and cpu cycles. In sucessive chapters, this is further explained as different forms of data structures are discussed. Similarly the performance gains provided by third party libraries like NumPy are discussed in detail, which is a learning experience. The chapter on compilers is also informative - the benefits of compilation depending upon which compiler is chosen. Important concepts like concurrency and multiprocessing are discussed in detail for the I/O and CPU bound problems.
Overall this is a book that you would like to keep in handy as a reference while designing a performant architecture or improving a python based application's response time. For me, this was an eye opener and a reckoner for improving the designg and effeciency of a python application and many concepts were beyond me at times, but I hope to learn more about python internals and this is a book that I will visit in future - to confirm my findings and keep on learning deeper concepts.
Disclaimer: I have been provided a free copy of this book by OReilly under their Blogger review program.