Python One-Liners: Write Code Like an Expert cover

Python One-Liners: Write Code Like an Expert

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Word count
347 words
Chapters
29
ISBN
9787121419683

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Summary

This book is the Chinese translation of Python One-Liners by Christian Mayer, translated by Su Dan and published by Publishing House of Electronics Industry in 2021. It is aimed at Python learners who are moving from beginner to intermediate level. Its core purpose is not to teach you to make code as short as possible, but to use the one-liner as an extreme practice ground for training a deep understanding of Python language features and the ability to break code down. The book follows a consistent chapter rhythm: first it presents the background of a specific problem, then gives a one-line solution, and then unpacks segment by segment why that line works and which syntax and library functions it uses. The book has six chapters, covering Python language fundamentals (data structures, containers, comprehensions, control flow, functions and lambda), common programming techniques (filtering data with list comprehensions, reading files, finding matching substrings with slicing, combining map and lambda, and so on), data science computing based on NumPy, concise implementations of major machine learning algorithm models (such as linear regression and K-Means clustering), advanced regular expressions, and one-line implementations of several classic computer science algorithms. The appendix and afterword also touch on topics such as recursion. In the preface, the author specifically discusses the key premise of readability: one-liners are a microscope for understanding the language, not a style guide for engineering code. As readers follow the case breakdowns and analyses in the book, they will gradually master advanced techniques such as list comprehensions, generators, slicing, lambda, and functional-style coding, and learn to judge in real projects when to be concise and when to be clear. The book is about 347,000 Chinese characters, with more than 200 pages of main text, and is suitable as an advanced exercise book after learning basic Python syntax.

Editor's review

「把代码写成一行」听起来像炫技,但本书作者把它做成了严肃的教学法。每一节固定的三段式结构——问题背景、一行代码、逐段拆解——让读者不是抄代码,而是真正看懂代码:一个列表解析里嵌套了几个条件、切片如何与字符串索引配合、lambda 与 map 怎样替代循环、正则表达式如何在一行内完成匹配与提取。 译者是豆瓣后端工程师苏丹,理工科背景加一线 Python 实践,译文对术语处理较为准确,代码与注释保留原貌,便于对照运行。 本书的价值还在于它跨出了语法书的地盘:从列表解析一直走到 NumPy、线性回归、K-Means、正则表达式与经典算法,把 Python 的常用工具链串成一条线。读完你会发现,所谓「专家的写法」不是更短,而是对抽象、迭代与函数组合的理解更深。 需要提醒的是,作者本人反复强调可读性优先;请把书中代码当作练习与思维体操,而不是项目里的书写规范。想打牢 Python 底子、又厌倦了枯燥语法罗列的中级学习者,会在这本书里找到久违的兴奋感。

Who it's for

A good fit for

  • 已掌握 Python 基础语法,想突破「会写但写不好」瓶颈的学习者
  • 准备面试、需要用简洁实现复习算法与数据结构的人
  • 做数据分析、想更熟练使用 NumPy、列表解析与函数式写法的人
  • 对正则表达式与机器学习算法的代码实现感兴趣的工程师
  • 喜欢通过读代码、拆解代码来学习的自学者

Not a good fit for

  • 完全没有编程经验的零基础读者,书中假设已有 Python 语法基础
  • 希望系统学习 Python 工程规范、测试与项目架构的人
  • 需要完整机器学习理论推导的读者,本书侧重代码实现而非数学证明
  • 把书中一行代码直接照搬进生产项目的人

Reading tips

  1. 按章节顺序读,第1章务必读透,后面所有案例都建立在其语法基础上
  2. 每节先自己动手实现再对照书中代码,差异之处最能暴露理解盲点
  3. 准备一个 Jupyter 环境逐行运行并打印中间结果,验证拆解过程的每一步
  4. 读完一章后尝试用一行代码改写自己项目中的循环或数据清洗片段

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.

Contents

  1. Introduction
  2. Examples of Python One-Liners
  3. A Note on Readability
  4. Who Is This Book For?
  5. What Will You Learn?
  6. Online Resources
  7. Chapter 1 Python Refresher
  8. Basic Data Structures
  9. Numerical Data Types and Structures
  10. Boolean Values
  11. Strings
  12. The None Keyword
  13. Container Data Types: Lists, Stacks, Sets, Dictionaries
  14. Membership Testing
  15. List and Dictionary Comprehensions
  16. Control Flow: if, else, and elif
  17. Loops
  18. Functions and Lambda Functions
  19. Chapter 2 Python Tricks
  20. Finding the Highest Earner with List Comprehensions
  21. Finding Words with High Information Value with List Comprehensions
  22. Reading Files
  23. Using the lambda and map Functions
  24. Finding Matching Substrings and Their Context with Slicing
  25. Chapter 3 Data Science
  26. Chapter 4 Machine Learning
  27. Chapter 5 Regular Expressions
  28. Chapter 6 Algorithms
  29. Afterword

FAQ

这本书适合零基础学 Python 的人吗?
不太适合。书中默认读者已了解变量、循环、函数等基础语法,重点在进阶技巧与代码拆解。零基础读者建议先读一本 Python 入门书,再回来看本书,效果会好很多。
书中的一行代码可以直接用在项目里吗?
作者明确强调可读性优先。一行流更多是理解语言特性的练习与思维训练,工程代码应以清晰、可维护为准。遇到确实简洁又易读的场景,才可考虑采用。
读这本书需要哪些前置知识或工具?
需要 Python 3 基础语法,了解列表、字典等容器即可。书中涉及 NumPy 与机器学习算法,建议准备 Jupyter Notebook,便于逐行运行代码、观察中间结果。
这本书和市面上的 Python 进阶书有什么不同?
多数进阶书按知识点罗列,本书以「一行代码解决一个问题」为线索,把语法、数据科学、机器学习、正则与算法串起来,重在培养拆解任意代码的能力,而非覆盖全部知识点。
这本书讲 Python 2 还是 Python 3?
书中示例基于 Python 3,涉及 f-string、print 函数等现代写法。读者在 Python 3.6 及以上环境运行代码,兼容性会更好。

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