Book Image

Python High Performance, Second Edition - Second Edition

By : Dr. Gabriele Lanaro
Book Image

Python High Performance, Second Edition - Second Edition

By: Dr. Gabriele Lanaro

Overview of this book

Python is a versatile language that has found applications in many industries. The clean syntax, rich standard library, and vast selection of third-party libraries make Python a wildly popular language. Python High Performance is a practical guide that shows how to leverage the power of both native and third-party Python libraries to build robust applications. The book explains how to use various profilers to find performance bottlenecks and apply the correct algorithm to fix them. The reader will learn how to effectively use NumPy and Cython to speed up numerical code. The book explains concepts of concurrent programming and how to implement robust and responsive applications using Reactive programming. Readers will learn how to write code for parallel architectures using Tensorflow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark. By the end of the book, readers will have learned to achieve performance and scale from their Python applications.
Table of Contents (10 chapters)

Choosing a suitable strategy

Many packages are available for improving the performance of programs, but how do we determine the best optimization strategy for our program? A variety of factors dictate the decision on which method to use. In this section, we will try to answer this question as comprehensively as possible, based on broad application categories.

The first aspect to take into consideration is the type of application. Python is a language that serves multiple and very diverse communities that span web services, system scripting, games, machine learning, and much more. Those different applications will require optimization efforts for different parts of the program.

For example, a web service can be optimized to have a very short response time. Also, it has to be able to answer as many requests as possible using as little resources as possible (that is, it will try to achieve lower latency), while numerical...