Python Programming

Name: Python Programming
ISBN: 9787121360732

董付国Publishing House of Electronics Industry · ChinaOct 2020

3.6

Word count: 149K words
Chapters: 241
ISBN: 9787121360732

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Summary

This book is one of the "Advanced Big Data Talent Training Series" organized and edited by Professor Liu Peng, Vice President of the Big Data Branch of the China Information Association. It is a comprehensive, hands-on Python programming tutorial that takes readers from the fundamentals of Python programming to practical application, progressively guiding them to use newly acquired knowledge to develop feature-rich projects. The book first introduces Python basics; then covers data types, files, program debugging, object-oriented programming, and connecting to data sources; next, it builds project experience through case studies using tools such as web crawlers, data mining, natural language processing, data visualization, and web and mobile applications; finally, it introduces various domestic cloud service platforms and how to access them using Python. All experiments in this book can be conducted remotely on the Big Data Experiment Platform or locally on the BDRack all-in-one big data experiment machine deployed at universities.

Editor's review

Python Programming, written by Dong Fuguo and published by Publishing House of Electronics Industry (ISBN 9787121360732), serves as both an introductory and advanced textbook for Python programming. It has received generally positive reviews on platforms such as Douban, with its rating reflecting readers' recognition of its practical content and clear structure. As a university instructor with extensive teaching experience, Dong Fuguo has arranged the book's knowledge points with particular attention to the learning curve: from basic syntax to object-oriented programming, and on to advanced topics such as file operations and exception handling, the book adopts a step-by-step approach throughout. It contains a large number of example codes and exercises closely tied to real-world applications, helping readers consolidate their understanding and develop the ability to solve practical problems. Compared with many similar books, a notable feature of this book is its emphasis on building programming thinking rather than merely listing syntax, which gives it considerable reading value for beginners who wish to systematically master Python and apply it to fields such as data analysis, automation scripts, or web development. It is not merely a reference book, but a programming guide that leads readers from "how to write" to "why write it this way."

Who it's for

A good fit for

Teachers and students in computer-related majors at higher education institutions, for use as a course textbook or supplementary reading
Programming beginners starting from scratch who wish to learn Python programming systematically
Developers with some foundation in other languages who want to switch quickly to Python
Enthusiasts who need a clearly structured reference book with rich examples for self-study and consultation

Not a good fit for

Senior developers seeking in-depth analysis of advanced topics such as machine learning and deep learning frameworks
Those seeking quick fixes who hope to solve all specific problems merely by skimming a collection of tips

Reading tips

It is recommended to read the chapters in order and to practice every example code by hand, understanding its execution logic
The exercises at the end of each chapter are key to testing learning outcomes; try to complete them independently before consulting the answer explanations
You can apply the book's knowledge modules to specific personal projects, for example, trying to use Python to automate the processing of everyday files

About the publisher

Publishing House of Electronics Industry China · Founded in 1982

The Publishing House of Electronics Industry is a comprehensive publisher distinguished by its focus on electronic information and related fields. Judging from the more than 3,000 titles in its catalogue, its publishing covers programming and design, artificial intelligence, computer science, finance and economics, photography, and social sciences, attending both to cutting-edge technology and to general readers. Representative titles include Factor Investing: Methods and Practice, x86 Assembly Language: From Real Mode to Protected Mode, The RISC-V Reader, Artificial Intelligence: Speech Recognition, Understanding and Practice, Phased Array Radar Technology, Radar Target Characteristics, and 100 Go Mistakes and How to Avoid Them, most of which centre on technical methods and engineering practice. Its authors include Shi Chuan, Li Zhong, Wang Xiaobo, David Patterson, Andrew Waterman, and Yu Zihao, among others from China and abroad. Owing to limited public information, no further publishing features are elaborated here.

版权信息
作者简介
内容简介
总序
前言
第1章 Python基础
1.1 Python简介
1.2 Python的安装与运行
1.3 Python版本的选择
1.4 程序控制
1.4.1 Python赋值语句
1.4.2 顺序结构
1.4.3 选择结构
1.4.4 循环结构
1.5 绘图
1.5.1 创建turtle对象
1.5.2 turtle绘图的基础知识
1.5.3 利用turtle库提供的方法绘制图形
1.6 函数
1.6.1 函数的定义
1.6.2 函数的调用
1.6.3 lambda函数
习题
参考文献
第2章数据类型
2.1 核心内置数据类型概述
2.2 数字类型声明及基本运算
2.2.1 整型
2.2.2 浮点型
2.2.3 复数类型
2.2.4 数字运算符
2.2.5 数字类型的常用函数及math库
2.2.6 数字类型转换函数
2.2.7 浮点型精度处理
2.3 列表
2.3.1 列表基本特征
2.3.2 序列通用操作
2.3.3 可变序列及列表通用操作（一）
2.3.4 可变序列及列表通用操作（二）
2.4 元组
2.5 range
2.6 哈希运算
2.7 字典
2.7.1 字典概述及声明
2.7.2 字典元素的访问
2.7.3 字典常用方法
2.8 字符串
2.8.1 字符串的声明
2.8.2 转义字符
2.8.3 字符串序列通用操作
2.8.4 字符串常用内置方法
习题
参考文献
第3章文件
3.1 读写文件
3.1.1 文件对象声明与基本操作
3.1.2 编码问题
3.1.3 文件写入操作
3.1.4 列表推导式
3.1.5 关闭文件
3.1.6 上下文语法
3.1.7 生成器
3.2 遍历目录树
3.3 处理Word文件
3.3.1 Python-docx库
3.3.2 利用Python-docx库读Word文件
3.3.3 利用Python-docx库创建Word文件
3.4 处理.pdf文件
3.5 处理压缩文件
习题
参考文献
第4章程序调试
4.1 异常
4.2 断言
4.3 日志
4.4 调试器
习题
参考文献
第5章面向对象程序设计
5.1 面向对象程序设计基本概念
5.2 类的定义和对象
5.3 构造函数和析构函数
5.4 类属性和实例属性
5.5 类的方法
5.5.1 类方法
5.5.2 实例方法
5.5.3 静态方法
5.5.4 类的特殊方法
5.6 类的继承性
5.6.1 单一继承
5.6.2 多重继承
5.7 类的多态性
习题
参考文献
第6章连接数据源
6.1 导入CSV数据
6.1.1 CSV数据的格式
6.1.2 Python读取CSV文件
6.1.3 Python写CSV文件
6.2 导入Excel数据
6.2.1 Python读取Excel文件
6.2.2 Python写Excel文件
6.3 导入JSON数据
6.3.1 JSON数据的格式
6.3.2 Python解码JSON数据
6.3.3 Python编码JSON数据
6.3.4 Python处理JSON数据文件
6.4 访问数据库
6.4.1 数据库的查询操作
6.4.2 数据库的插入操作
6.4.3 数据库的删除操作
6.4.4 数据库的修改操作
习题
参考文献
第7章网络爬虫
7.1 网络爬虫工作的基本原理
7.1.1 网页的概念
7.1.2 网络爬虫的工作流程
7.1.3 Python与网络爬虫
7.2 网页内容获取——requests库
7.2.1 requests对象
7.2.2 response对象
7.3 网页内容解析——BeautifulSoup库
7.3.1 BeautifulSoup库概述
7.3.2 BeautifulSoup库常用方法和Tag节点
7.4 正则表达式
7.4.1 正则表达式概念
7.4.2 正则表达式元字符介绍
7.4.3 正则表达式的常用函数介绍
7.5 实战：热门电影搜索
7.6 实战：大数据相关论文文章标题采集
7.7 实战：全国空气质量数据爬取
习题
参考文献
第8章数据挖掘
8.1 Python常用数据分析工具
8.1.1 NumPy
8.1.2 Scipy
8.1.3 pandas
8.1.4 Scikit-Learn
8.2 数据预处理
8.2.1 数据清理
8.2.2 数据集成
8.2.3 数据变换
8.2.4 Python数据预处理
8.3 分类与预测
8.3.1 特征选择
8.3.2 性能评估
8.3.3 实现过程
8.3.4 分类与预测的常用方法
8.4 聚类分析
8.4.1 聚类分析定义
8.4.2 聚类分析评价标准
8.4.3 数据相似度度量
8.4.4 聚类分析的常用方法
8.5 实战：信用评估
8.5.1 数据加载及说明
8.5.2 数据预处理
8.5.3 划分数据集
8.5.4 模型建立及参数调优
8.5.5 模型测试及分析
8.6 实战：影片推荐系统
8.6.1 推荐系统
8.6.2 python-recsys库简介
8.6.3 影片推荐
习题
参考文献
第9章自然语言处理
9.1 Python常用自然语言处理工具
9.1.1 Python自然语言处理工具包NLTK
9.1.2 Python中文处理工具jieba
9.1.3 Python语法解析器PLY
9.2 文本处理
9.2.1 文本获取
9.2.2 文本表示
9.2.3 文本特征词提取
9.3 词法分析
9.3.1 分词
9.3.2 词性标注
9.3.3 命名实体识别
9.3.4 去停用词
9.3.5 中文分词实战
9.4 语法分析
9.4.1 语法分析简介
9.4.2 语法树
9.4.3 语法分析算法
9.4.4 语法分析示例
9.5 实战：搜索引擎
习题
参考文献
第10章数据可视化
10.1 用Pillow操作图像
10.1.1 图像的基本知识
10.1.2 图像处理中常用的模块和函数
10.1.3 案例介绍
10.2 用Matplotlib绘图
10.2.1 Matplotlib常用函数介绍
10.2.2 折线图的函数定义及属性说明
10.2.3 案例介绍
10.3 调用Echarts
习题
参考文献
第11章 Web和移动应用
11.1 Web框架Django
11.1.1 Django简介
11.1.2 Web框架
11.1.3 MVC和MTV模式
11.1.4 Django的安装
11.2 Python Web开发
11.2.1 创建项目
11.2.2 Django模板
11.2.3 Django模型
11.2.4 Django Admin管理工具
11.2.5 Django Nginx+uwsgi安装配置
11.3 Python移动应用开发
11.3.1 Python Kivy
11.3.2 Python移动应用开发过程
11.3.3 基于Python开发2048游戏
习题
参考文献
第12章与云结合
12.1 阿里云
12.1.1 阿里云计算体系架构
12.1.2 CLI Python版
12.2 腾讯云
12.2.1 腾讯云总体架构
12.2.2 腾讯云Python访问
12.3 百度云
12.3.1 百度云架构
12.3.2 BAE Python部署
12.4 万物云
12.4.1 功能及应用
12.4.2 数据服务及访问
12.5 环境云
12.5.1 功能服务
12.5.2 应用开发数据接口
习题
参考文献
附录A 人工智能和大数据实验环境
反侵权盗版声明
作者简介

FAQ

Is this book suitable for people with no programming background at all?

Very suitable. The book starts from environment setup and basic syntax, and its design fully takes into account the cognitive path of zero-foundation learners, making it one of the classic introductory textbooks.

Are the code examples in the book based on Python 2 or Python 3?

According to the version information, the book's content is written based on Python 3, in line with current mainstream development environments.

What level can I reach after finishing this book?

You can systematically master Python's core syntax, object-oriented programming concepts, and common module operations such as file and exception handling, and be capable of independently writing small to medium-sized scripts or pursuing further study in specific fields (such as the foundations of data analysis).

Comments

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About the author

董付国 Author

Dong Fuguo is a Chinese author of programming books. Public information about him is limited, and details such as his nationality, education, and professional positions are not recorded in the available sources. The only work currently on record is Python Programming, which is classified under programming design. This work suggests that the author writes for introductory and instructional settings, using the Python language to cover the fundamentals of programming and the core content of program design. Books of this kind typically emphasize clear explanations of concepts and practical, workable examples, helping readers understand programming ideas step by step and put them into practice. Although only one work is available here, making it difficult to form a full picture of the author's writing, the existing information indicates that Dong Fuguo focuses on programming education and offers Chinese readers a useful reference for learning Python programming.