In the late 1990s, Python went through a series of 1.x versions, most notably Python1.5.2, which remained the gold standard for Python for a long time. The growth of the Python community since its creation in December 1989 and the maturity of Python 1 set the stage for a broader range of extensions to Python 2. Today, the latest Python3.9 development schedule is on the table…
Guido has stepped back from the background, but he still believes in Python’s future. Python is also making progress all the time. In the future, Python will shine in cloud computing, artificial intelligence, crawler, automated operation and maintenance, financial analysis and other fields with higher development efficiency, faster running speed and stronger functions.
This list of Python books covers getting started, getting advanced, and upgrading your skills in a particular industry, so whether you’re new to Python or already have some experience, these tips are worth reading!
An introduction to
Get started with Python programming — automate tedious tasks
Author: Al Sweigart
Translator: Wang Haipeng
Brief Introduction:
This book is a quick guide to Python, a beginner friendly language. The book contains many practical examples for readers to learn and relate to.
Through this book, we can learn how to solve a lot of practical tasks and requirements, including the search text pattern in one or more files, by creating a modified mobile and rename files and folders to organize computer, fetching data and information, update the Excel spreadsheet, automatically send email and text message, organization computer periodic tasks, and so on.
Stupid way to learn Python 3
By Zed A. Shaw
Translator: Wang Weiwei
Brief Introduction:
This book is an introduction to Python. It guides readers to learn programming step by step through exercises, from simple printing to the implementation of complete projects, so that beginners can start with basic programming techniques and finally experience the basic process of software development. This book is based on python version 3.6. There are 52 exercises in this book. Each chapter is roughly the same format, starting with code exercises, following instructions to write code, running and checking the results, and then doing additional exercises.
Python Mathematical Programming
By Amit Saha
Translator: Xu Yangyi, Liu Xuhua
Brief Introduction:
This book combines programming and mathematics, starting with simple projects that use Python to solve math problems in high school and early college, such as geometry, probability, statistics, and calculus. It provides a solid foundation for further learning of more complex mathematics and the Python programming language. The book also serves as a beginner’s guide to Python, where you can improve your programming skills and skills by learning examples and completing programming challenges.
Data structures (Python)
Author: Kenneth A. Lambert
Translator: Li Jun
Brief Introduction:
For computer science students, hobbyists, and practitioners, Python is an introduction to object-oriented design and data structures.
This book first introduces the basic knowledge and features of Python language, and then combined with a variety of data structures, respectively with Python analysis and implementation. The book covers topics such as polymorphism and inheritance, as well as multiple implementations of collection interfaces, analysis of space and time costs, and implementations of various collections. At the end of each chapter, exercises are given to help the reader consolidate and think.
The Python algorithm in detail
Author: Zhang Lingling
Editor: Zhang Tao
Brief Introduction:
Of 13 chapters of the book, Python respectively based on the algorithm is the soul of the program, data structures, algorithms of thoughts, linear tables and stack, queue, tree, graph, search algorithms, internal sorting algorithms, data structure of the classic problem, solving math problems, classic algorithms problem, solve the problem of image, the content such as game and algorithm. The content of the book is “technical solution” throughout the book, leading readers to fully grasp the core technology of the algorithm.
Python Scripting Guide for system administrators
Ganesh Sanjiv Naik (India)
Translator: Zhang Chengwu
Brief Introduction:
This book is an advanced introduction to Python programming, covering a number of topics on Python scripting design. The 18-chapter book begins with a quick review of Python basics, followed by a step-by-step introduction to practical topics, including debugging and analyzing Python scripts, writing unit tests, system administration, working with files and data, archiving, and text processing. It then covers more advanced topics like network programming, handling E-mail, remotely controlling hosts, creating graphical user interfaces, working with log files, writing web crawlers, data collection and visualization, and operating databases.
Each knowledge point in this book is combined with working source code to help readers better master Python scripting. This book requires a basic knowledge of Python, and is ideal for readers who have a basic understanding of Python programming and are interested in extending their programming skills to command-line scripts and system administration.
The advanced
Python geek project programming
Author: Mahesh Venkitachalam
Translator: Wang Haipeng
Brief Introduction:
This book combines the interests of software development engineers to teach Python programming in action. The book is divided into 14 chapters in five parts, starting with the basics, then simulation games, then graphics, 3D graphics, and hardware, respectively, to show the reader how to apply Python programming skills to real projects in a hands-on way.
This book fully considers the reader’s learning interest and habits, the use of high value cases, is a real guide to help intermediate programmers quickly get started using Pyhton.
Python Core Programming (Version 3)
Author: Wesley Chun
Translator: Sun Boxiang, Li Bin, Li Han
Brief Introduction:
The book is divided into three parts. Part 1 covers regular expressions, network programming, Internet client programming, multithreaded programming, GUI programming, database programming, Microsoft Office programming, extending Python, and more. Part 2 covers Web clients and servers, CGI and WSGI-related Web programming, The Django Web framework, cloud computing, and advanced Web services. Part 3 covers text processing, among other things.
Python Cookbook (3rd edition) Chinese Version
Author: David Beazley, Brian K.Jones
Translator: Chen Ge
Brief Introduction:
Some of this book introduces the Python application in various fields to use techniques and methods, its theme covers data structures and algorithms, and text string, number, date and time, the iterator and generator, files and I/O, data coding and processing, functions, classes and objects, metaprogramming, modules and packages, network and Web programming, concurrent, Practical script and system management, testing, debugging and exception, C language extension, etc.
The Stupid Way to Learn Python 3 Advanced tutorials
By Zed A. Shaw
Translator: Wang Weiwei
Brief Introduction:
This book is an advanced part of Learning Python 3 the Stupid Way, which introduces you to the basics of programming in Python 3, and helps you go beyond the basics with 52 well-designed problem sets.
Each of the 52 problem sets, most combined with practical demonstrations and additional challenges, helps readers master a key practical skill, This includes using a text editor to manage complex projects, leveraging powerful data structures, applying algorithms to data structures, mastering the necessary text analysis and processing techniques, using SQL to model and store data efficiently and logically, and learning powerful command line tools.
This book is designed to help you become an advanced Python programmer by moving from simply writing code that works to writing high-quality Python code that solves real problems. This book is suitable for all technical people who have started using Python, including junior developers and experienced Python programmers who have upgraded to Python version 3.6 or higher.
Python High Performance Programming
Micha Gorelick, Ian Ozsvald
Translator: Hu Shijie, Xu Xubin
Brief Introduction:
Aimed at Python programmers with some foundation, this book will guide readers through various approaches to code optimization. Readers will learn how to use intelligent algorithms, as well as various related technologies such as Numpy, Cython, CPython, and various multi-threaded and multi-node strategies. There is a consistent lack of tutorials on how to do highly computational tasks in Pyhton, and this book is a rare read on the subject.
Security technology
Python Cryptographic Programming (version 2)
Author: Al Sweigart
Inner Mongolia
Brief Introduction:
Since the advent of the Internet, network security has been the focus of attention. Since the middle of the 20th century, cryptographic algorithms spread for thousands of years have been put into the application of network security; Then, in the 1970s, a cryptosystem completely different from classical cryptography — public key cryptography algorithm suddenly appeared, the development of cryptography completed a leap. Python was born in the 1990s. It is a high-level programming language that combines the characteristics of object-oriented language and interpreted language. It has been widely used.
This book combines The Python language with cryptography, from simple classical cryptography, all the way to public key cryptography, concise and detailed explanation and interpretation. Each cryptographic algorithm is explained in a principles section, implementation section, and cracking section (public key algorithm does not include cracking section), the latter two of which are accompanied by detailed Python code with concise and readable comments. At the end of each chapter, some exercises are provided to help the reader consolidate what has been learned and gain further understanding. This book is for anyone who wants to learn Python programming and has an interest in cryptography. This book does not require much in the way of basic Python programming, and beginners can read it with confidence. I believe this book will bring readers an excellent reading experience.
Financial technology
Financial Analysis and Risk Management based on Python
Author: Sven
Editor: Joon-young Hu
Brief Introduction:
This book focuses on the application of Python to financial analysis and risk management. It is divided into 12 chapters: Introductory, Basic, and advanced. In the introductory chapter, we introduced Python and demonstrated basic Python operations in conjunction with finance. In the basic part, we will explain how to use Python modules such as NumPy, Pandas and SciPy. In the enhanced chapter, we discuss in detail the use of Python to analyze interest rates, bonds, stocks, futures, options, and value-at-risk.
Python Financial Big Data Analysis 2nd edition
By [Germany] Yves Hilpisch
Translator: Yao Jun
Brief Introduction:
Python Financial Big Data Analysis 2nd edition is divided into five parts with 21 chapters. Part 1 introduces the use of Python in finance. It covers the reasons why Python is used in finance, Python’s infrastructure and tools, and some concrete introductory examples of Python in econometric finance.
Part 2 covers the basics of Python and the well-known Python libraries NumPy and PANDAS toolsets, as well as object-oriented programming; The third part introduces the basic techniques and methods related to financial data science, including data visualization, input/output operations and finacy-related knowledge in mathematics.
Part 4 introduces the application of Python in algorithmic trading, focusing on common algorithms, including machine learning, deep neural network and other ARTIFICIAL intelligence related algorithms; The fifth part explains the application of options and derivatives pricing based on Monte Carlo simulation, which covers the introduction of valuation framework, simulation of financial models, derivatives valuation, portfolio valuation and other knowledge.
The Python Financial Big Data Analysis 2nd Edition is suitable for financial industry developers who are interested in using Python for big data analysis and processing.
Python Finance case in point
Author: Sven
Editor: Joon-young Hu
Brief Introduction:
With the advent of the fintech era, Python’s influence in finance is already evident. Mastering Python in financial practice has become a must-have skill for fintech professionals.
The book, a complementary case set to Python-based Financial Analysis and Risk Management, combines 88 original cases from real-world financial markets and everyday practice, covering 308 programming tasks and over 6,000 lines of Python code.
The book includes a variety of financial scenarios, including interest rates, exchange rates, bonds, stocks, funds, forwards, stock index futures, foreign exchange futures, Treasury bond futures, stock options, commodity options and other financial products. Also involved in commercial Banks, securities companies, futures companies, insurance companies, trust companies, asset management companies, fund management companies, the financial holding company and so on various types of financial institutions, is introduced, including China, emerging markets, and introduces the mature financial markets Europe and America, and include the financial practice may be involved in the various scenarios of Python programming.
The book looks at a range of financial practice cases that practitioners might be involved in, and provides efficient solutions combined with Python programming. Through reading this book, readers will be able to fully understand the operation of the financial market, a deep insight into the work skills behind various positions.
Python futures quantitative trading practice
Author: Feng Shichang, LIU Chengyan
Translator: Xi Songhe
Brief Introduction:
To stay competitive in corporate and investment finance today, it’s no longer enough to master spreadsheets and calculators; traditional tools and data sets just don’t cut it. This book will use Python programming to solve futures quantitative trading problems and introduce practical solutions through more than 110 tips.
This book is based on the case of Taiwan Futures Exchange. From the perspective of data analysis, the book goes deep into the data in the form of skills, so that readers can understand the relevant technical indicators starting from the basic futures trading rules, and be able to skillfully use Python programming to embark on the road of quantitative trading. This book is suitable for both futures practitioners and programmers who want to enter the financial field.
Artificial intelligence (ai)
Python natural language processing
Steven Bird, Ewan, Klein, Edward Loper
Translator: Chen Tao, Zhang Xu, Cui Yang, Liu Haiping
Brief Introduction:
This book provides a very easy to learn introduction to natural language processing, which covers a wide range of language processing techniques, from text and E-mail predictive filtering to automatic summarization and translation. You will learn to write Python programs to handle large amounts of unstructured text, and you will understand the main algorithms used to analyze the content and structure of written communication.
Python 3 Ice-breaking ARTIFICIAL Intelligence: From beginning to Action
Author: Huang Haitao
Editor: Zhang Shuang
Brief Introduction:
This book mainly consists of two parts. The first part is the basic part (understanding relevant algorithms in the form of mathematical modeling competitions over the years, and explaining common Python packages under relevant AI modules). The second part is the practical part, introducing the basic principles of common algorithms and building practical cases. It also includes examples of natural language processing and TensorFlow.
Data science
Python statistical analysis
Thomas Haslwanter (Austria)
Translator: Li Rui
Brief Introduction:
Focusing on basic statistics and hypothesis testing, this book provides a concise overview of Python’s use in data analysis, visualization, and statistical modeling. It includes a simple introduction to Python, study design, data management, probability distributions, hypothesis testing for different data types, generalized linear models, survival analysis, and Bayesian statistics, ranging from introductory to advanced.
Using the open source language Python, this book not only provides an intuitive understanding of data analysis and statistical tests, but also provides a simple explanation of relevant mathematical formulas. This book is very operable, supporting the relevant code and data, readers can according to the book, reproduce and deepen the understanding of the relevant knowledge.
The book is for those interested in statistics and Python, especially students and researchers in experimental disciplines who need to harness the power of Python for data processing and statistical analysis.
Bayesian thinking: A Python learning approach to statistical modeling
By Allen B. Downey
Translator: Xu Yangyi
Brief Introduction:
Bayesian statistical methods are becoming increasingly important and popular. But there are few resources on the market for beginners. This book is based on university courses taught by the author and should help readers get a good start in programming in Python, dealing with estimation, prediction, decision analysis, hypothesis testing and so on in statistics. The book contains simple examples such as rolling dice, as well as practical examples that solve real-world problems.
Web crawler
Proficient in Python crawler framework Scrapy
Author: Dimitrios Kouzis-Loukas
Translator: Li Bin
Brief Introduction:
This book is a how-to guide to the open source crawler framework. It starts with the basics of the Scrapy framework, and then shows you how to use Python and third-party apis to extract data from any source, process it, and render it on demand. It then explains the process of storing the crawled data into the database, the search engine, and using Spark Streaming for real-time analysis.
Writing web crawlers in Python (version 2)
By Katharine Jarmul and Richard Lawson
Translator: Li Bin
Brief Introduction:
Book includes the definition of web crawler and how to crawl web, how to use several kinds of library to extract data from web pages, how to avoid the repeated downloads by caching the results of problem, how to accelerate data fetching through parallel downloads, how to use different ways to extract data from dynamic website, how to use the uncle and navigation and other expression to search and login, How to access captcha image protected data, how to use Scrapy crawler framework for fast parallel crawler, and use Portia’s Web interface to build Web crawlers.
Teen programming
Teach Your child programming (Python)
Author: Bryson Payne
Translator: Li Jun
Brief Introduction:
This book is designed to provide parents and teachers with a guide to programming and problem solving in Python. It also includes some very typical and useful examples to facilitate learning. Through step by step guidance, let the students understand the computer thinking, and can grasp variables, cycles, functions and other basic concepts, in order to improve the children’s brain and hands-on ability.
Whether you have some programming experience or are a zero-based reader, you will be the best first teacher a child can have in computer programming.
Fun Python — Teach your child how to program
Author: Jason R. Briggs
Translator: Yin Zhe
Brief Introduction:
This book takes the reader into the world of Python in a breezy way. The author will take readers through unique, novel and fun examples to learn Python programming. Where terms are specifically prompted and code is color-coded, analyzed, and explained. The illustrations are also playful.
Each chapter of the book contains well-designed programming puzzles that allow readers to use their brains to fully understand what they have learned and what they are learning. The book concludes with an introduction to writing two complete games. This method of teaching by writing games can greatly motivate readers to learn.
Programming Python for children
Authors: Li Qiang, Li Ruoyu
Editor: Chen Jikang
Brief Introduction:
Python is easy to learn and powerful, making it the language of choice for young children to learn programming. The book is a fun guide for children to learn Python programming. The book consists of 17 chapters, organized in a step-by-step way from simple to difficult.
This book starts with the introduction of Python, first introduces the installation of Python and the use of IDLE, then introduces variables, numbers and strings, lists, tuples and dictionaries, Boolean types and other data types, as well as conditions, loops, exceptions and comments, functions, object-oriented programming, file operations and other basic knowledge. Turtle drawing, Pygame fundamentals and game programming, as well as the application of Python in natural language processing are explained through practical cases.
The book is carefully selected, moderately difficult and interesting, and the language is easy to understand and the code examples are abundant. At the end of the chapters, some exercises and solutions are given.
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