Python High Performance Programming 
Author: Gabriele Lanaro
Published: Decmber 23, 2013
Publisher: Packt Publishing
ISBN: 9781783288458
Format: Retail PDF
Reader Required: Adobe Reader, Adobe Digital Editions
Pages: 108
Skill Level: Experienced 

Tested on the above readers with no problems on laptop and Android tablet. 
Please allow a couple seconds for the seedboxes to kick in, then it should move pretty quick.
Enjoy! :D
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Boost the performance of your Python programs using advanced techniques

Overview
Identify the bottlenecks in your applications and solve them using the best profiling techniques
Write efficient numerical code in NumPy and Cython
Adapt your programs to run on multiple processors with parallel programming

In Detail
Python is a programming language with a vibrant community known for its simplicity, code readability, and expressiveness. The massive selection of third party libraries make it suitable for a wide range of applications. This also allows programmers to express concepts in fewer lines of code than would be possible in similar languages. The availability of high quality numerically-focused tools has made Python an excellent choice for high performance computing. The speed of applications comes down to how well the code is written. Poorly written code means poorly performing applications, which means unsatisfied customers.

This book is an example-oriented guide to the techniques used to dramatically improve the performance of your Python programs. It will teach optimization techniques by using pure python tricks, high performance libraries, and the python-C integration. The book will also include a section on how to write and run parallel code.

This book will teach you how to take any program and make it run much faster. You will learn state-of the art techniques by applying them to practical examples. This book will also guide you through different profiling tools which will help you identify performance issues in your program. You will learn how to speed up your numerical code using NumPy and Cython. The book will also introduce you to parallel programming so you can take advantage of modern multi-core processors.