2018 Latest Python Book list

Python, the ubiquitous programming language, learns it, with a high salary to no friends. At the beginning of 2018 these Python books are worth paying attention to, and be sure to collect them as you step into the Python academy. Extra, the asynchronous community to recruit reviewers, if you are interested in joining, in the background to reply to the "book review", you can join us, free to read the new book.
Let's take a look at some of the Python books below.
"Python Programming (3rd edition)"

Python's father order recommendation
Getting started with Python programming classic
Editor's recommendation:
Extensive use of computer graphics-this book provides a simple graphics package graphics.py as an example.
A lively and interesting example-this book contains complete programming examples to solve real-world problems.
A kind and natural writing--introduces the important computer science concepts in the natural narrative style.
The flexible spiral learning process-simply presents the concept, gradually introduces new ideas, and strengthens them at the end of the chapter.
The timing of the introduction of the object-the book is not a strict "early-speaking object", nor "late-speaking object", but on the basis of command-based programming briefly introduced the concept of the object.
Provide a wealth of teaching materials--provide a large number of chapter-end exercises. Code samples and instructional PPT downloads are also available.

This book teaches computer programming in the Python language as a tool. This book emphasizes problem solving, design and programming as the core skills of computer science. The book features vivid, interesting examples, easy to read and easy to learn, suitable for Python programmers to read, but also suitable for university computer professional teachers and students reference.
Data structure (description of Python language)

A detailed explanation of the basic programming grammar of data structure based on Python language
Python Learning Essentials
Editor's recommendation:
In computer science, data structure is an advanced course, the concept of abstraction, the difficulty is greater. The Python language is simple in syntax and highly interactive. The use of Python to explain the data structure and other topics, more than the C language to achieve easier and clearer.
The 1th chapter of this book briefly introduces the basic knowledge and features of the Python language. The 2nd Chapter to the 4th chapter has introduced the abstract data type, the data structure, the complexity analysis, the array and the linear list structure, the 5th chapter and the 6th chapter emphatically introduced the object-oriented design related knowledge, the 5th chapter includes the interface and the realization the key difference, the polymorphism as well as the information hiding and so on content, The 6th chapter mainly explains the knowledge of inheritance, and the 7th chapter to the 9th chapter introduces the related knowledge of linear set, which is represented by stack, queue and list. The 10th chapter introduces the various tree structure, the 11th chapter explains the set and the dictionary related content, 12th chapter introduced the graph and the graph processing algorithm. At the end of each chapter, the review questions and case studies are given to help readers consolidate and think.
"Selenium automation Test-based on Python language"

A practical Guide to Web Automation testing using Python and Selenium!
Test Nest Team Translation!
Editor's recommendation:
This book directly hit these two aspects, for testers relieved the worries.
(1) Selenium Webdriver, as a common testing framework in the industry, is not only the standard of web testing, but also the core driving framework in the field of mobile testing. So mastering the selenium webdriver allows us to be able to write automated tests for Web products and mobile products.
(2) Python, as a dynamic language, simplifies the rigorous programming syntax and makes it easier for testers to master. Python also provides rich APIs and extensions that enable testers to easily invoke or integrate programs and class libraries written in other languages to improve the efficiency of writing automated tests.

The efficient calculation of Python physics

A practical guide to applying Python to the physical world
Many physicists also play the role of software developers in their research work. But even for physicists, not all software development tasks are simple. This book is a practice guide that introduces many of the basic skills of software development to help readers automate almost all aspects of the physics field.
Written by two PhD in nuclear engineering, this book contains a number of practical cases in the field of physics. By reading this book, readers will learn how to collect, analyze, build software, publish results and other skills in Python programming languages.
The book is divided into 4 parts.
Getting started: Mastering python, command line, data containers, functions, process controls, and logic, classes, and objects.
Getting Started: Learning regular expressions, analyzing and visualizing, NumPy, storing data with files and HDF5, important data structures in physics, parallel computing, and deploying software.
Perfect: Build processes and software; Use local and remote versions to control, debug, and test your code.
Publish: Generate documents for code, publish research results, improve collaboration efficiency, and understand the process of software license, ownership, and copyright.

"Python Bayesian Analysis"

Pymol Community of active people dedicated!
Discover the power of Python Bayesian analysis!
Edit Recommendation:
This book introduces the main concepts in Bayesian statistics and how to apply them to data analysis. This book uses a practical method of programming computing to introduce the basics of Bayesian modeling, to interpret and explore the core concepts in the Bayesian framework using some hand-constructed data and some simple real data, and then in the model covered in this book, the linear model is abstracted to solve regression and classification problems, In addition, the mixed model and layered model are explained in detail, and the model selection is discussed in a separate chapter, and the non-parametric model and Gaussian process are briefly introduced.
python Physics Modeling Beginner's Guide

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Discover the power of Python Bayesian analysis!
Edit Recommendation:
Python is a widely used programming language. This book is designed to help Python learners acquire enough python programming skills for physical modeling. The
Book is divided into 8 chapters and 5 appendices, including Python fundamentals, data structure and program control, data entry and output, Python advanced knowledge, and advanced technology, which run through three different directions and difficult physical modeling experiments. The Appendix section describes the installation of Python, error messages, version differences, and topics that can be used for in-depth learning.
This book is suitable for beginners in python, especially for readers who want to use Python for scientific computing and physical modeling.

All Bayesian models in this book are implemented with PyMC3. PyMC3 is a Python library for probabilistic programming, and many of its features are described in the book. With the help of this book and PyMC3, readers will learn to implement, examine, and expand Bayesian statistical models to solve a series of data analysis problems.
Python Game Programming Quick Start (4th edition)

Beginner Learning Game Development Combat Guide
Editor's recommendation:
Book by writing a small, Interesting game to teach Python programming, and to use a direct display of the game's source code and through an example to explain how the programming principle. A total of 21 chapters, 12 game programs and examples throughout, the Python basic knowledge, data types, functions, Process Control, program debugging, flowchart design, string manipulation, lists and dictionaries, Cartesian coordinate system, cryptography Foundation, game AI simulation, animation graphics, collision detection, Programming knowledge in all aspects of sound and image. This book can help readers to master the basic skills of Python game programming in a fun and easy process.
Python Advanced Programming (2nd edition)

Basic Python3.5 Writing
Python Advanced Treasure
Editor's recommendation:
This book is based on the Python version 3.5, and the depth of the 13 chapters reveals advanced techniques for Python programming. This book begins with the Python language and its community, and provides a comprehensive and systematic explanation of the important topics of Python syntax, naming conventions, Python package authoring, deployment code, extender development, code management, document writing, test development, coding optimization, concurrency programming, design patterns, and more.
This book is suitable for readers who want to further improve their Python programming skills, as well as reference learning for readers interested in Python programming. The book combines a typical and practical development case to help readers create high-performance, reliable, and maintainable python applications.
"Python Digital Signal processing application"

A practical guide to applying digital signal processing via Python
Editor's recommendation:
This book describes how to implement digital signal processing in Python language. A total of 11 chapters, the Python code as an example to the reader to introduce the digital signal processing of the relevant knowledge and applications. The book deals with the digital signal processing techniques of periodic signals and their spectrum, waveform harmonic structure, aperiodic signal and spectral graph, noise, autocorrelation function, discrete cosine transform and discrete Fourier transform, filtering, convolution, differential and integral, modulation sampling and so on. Each chapter starts with an example and guides the reader through programming to understand the concept in a precise way. In addition, each chapter of the book provides exercises and code examples to help readers understand this knowledge.
This book is suitable for readers who are interested in digital signal processing and have a certain Python base, and are also suitable for students majoring in electronic and communication related reading.
"Python neural network Programming"

* * One of the leaders of the London Python community Tariq Rashid new work

Editor's recommendation: * *
The main purpose of this book is to reveal the concepts behind neural networks to as many people as possible. There are 3 main parts:
The first part, a list of the mathematical ideas used in the simple neural network;
The second part, learn Python and learn how to use Python to implement your own neural network;
The third part is to understand the simple neural network model.

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2018 Latest Python Book list