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You're reading from Advanced Python Programming Build high performance, concurrent, and multi-threaded apps with Python using proven design patterns

Product type Course

Published in Feb 2019

Publisher Packt

ISBN-13 9781838551216

Length 672 pages

Edition 1st Edition

Languages

Python

Tools

Dask

Concepts

Design Patterns

Authors (3):

Dr. Gabriele Lanaro

Quan Nguyen

Sakis Kasampalis

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Table of Contents (36) Chapters

Preface

Benchmarking and Profiling FREE CHAPTER

Pure Python Optimizations

Fast Array Operations with NumPy and Pandas

C Performance with Cython

Exploring Compilers

Implementing Concurrency

Parallel Processing

Advanced Introduction to Concurrent and Parallel Programming

Amdahl's Law

Working with Threads in Python

Using the with Statement in Threads

Concurrent Web Requests

Working with Processes in Python

Reduction Operators in Processes

Concurrent Image Processing

Introduction to Asynchronous Programming

Implementing Asynchronous Programming in Python

Building Communication Channels with asyncio

Deadlocks

Starvation

Race Conditions

The Global Interpreter Lock

The Factory Pattern

The Builder Pattern

Other Creational Patterns

The Adapter Pattern

The Decorator Pattern

The Bridge Pattern

The Facade Pattern

Other Structural Patterns

The Chain of Responsibility Pattern

The Command Pattern

The Observer Pattern

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Appendix

Questions

What is asynchronous programming? What advantages does it provide?
What are the main elements in an asynchronous program? How do they interact with each other?
What are the async and await keywords? What purposes do they serve?
What options does the asyncio module provide, in terms of the implementation of asynchronous programming?
What are the improvements in regards to asynchronous programming provided in Python 3.7?
What are blocking functions? Why do they pose a problem for traditional asynchronous programming?
How does concurrent.futures provide a solution to blocking functions for asynchronous programming? What options does it provide?

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Authors (3)

Dr. Gabriele Lanaro

Dr. Gabriele Lanaro is passionate about good software and is the author of the chemlab and chemview open source packages. His interests span machine learning, numerical computing visualization, and web technologies. In 2013, he authored the first edition of the book High Performance Python Programming. He has been conducting research to study the formation and growth of crystals using medium and large-scale computer simulations. In 2017, he obtained his PhD in theoretical chemistry.

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Quan Nguyen

Quan Nguyen is a Python programmer and machine learning enthusiast. He is interested in solving decision-making problems under uncertainty. Quan has authored several books on Python programming and scientific computing. He is currently pursuing a Ph.D. degree in computer science at Washington University in St. Louis, researching Bayesian methods in machine learning.

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Sakis Kasampalis

Sakis Kasampalis is a software engineer living in the Netherlands. He is not dogmatic about particular programming languages and tools; his principle is that the right tool should be used for the right job. One of his favorite tools is Python because he finds it very productive. Sakis was also the technical reviewer of Mastering Object-oriented Python and Learning Python Design Patterns, published by Packt Publishing.

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