Book Image

Advanced Python Programming - Second Edition

By : Quan Nguyen
Book Image

Advanced Python Programming - Second Edition

By: Quan Nguyen

Overview of this book

Python's powerful capabilities for implementing robust and efficient programs make it one of the most sought-after programming languages. In this book, you'll explore the tools that allow you to improve performance and take your Python programs to the next level. This book starts by examining the built-in as well as external libraries that streamline tasks in the development cycle, such as benchmarking, profiling, and optimizing. You'll then get to grips with using specialized tools such as dedicated libraries and compilers to increase your performance at number-crunching tasks, including training machine learning models. The book covers concurrency, a major solution to making programs more efficient and scalable, and various concurrent programming techniques such as multithreading, multiprocessing, and asynchronous programming. You'll also understand the common problems that cause undesirable behavior in concurrent programs. Finally, you'll work with a wide range of design patterns, including creational, structural, and behavioral patterns that enable you to tackle complex design and architecture challenges, making your programs more robust and maintainable. By the end of the book, you'll be exposed to a wide range of advanced functionalities in Python and be equipped with the practical knowledge needed to apply them to your use cases.
Table of Contents (32 chapters)
1
Section 1: Python-Native and Specialized Optimization
8
Section 2: Concurrency and Parallelism
18
Section 3: Design Patterns in Python

Automatic parallelism

Examples of packages that implement automatic parallelism are the (by now) familiar just-in-time (JIT) compilers numexpr and Numba. Other packages have been developed to automatically optimize and parallelize array and matrix-intensive expressions, which are crucial in specific numerical and machine learning (ML) applications.

Theano is a project that allows you to define a mathematical expression on arrays (more generally, tensors), and compile them to a fast language, such as C or C++. Many of the operations that Theano implements are parallelizable and can run on both the CPU and GPU.

TensorFlow is another library that, similar to Theano, is targeted toward array-intensive mathematical expressions but, rather than translating the expressions to specialized C code, executes the operations on an efficient C++ engine.

Both Theano and TensorFlow are ideal when the problem at hand can be expressed in a chain of matrix and element-wise operations (such as...