李·沃恩的《不切实际的Python项目》：趣味编程提升智慧

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"Lee Vaughan的《Impractical Python Projects》是一本充满趣味性的编程活动书籍，旨在通过实践项目提升读者的编程智慧。这本书由No Starch Press于2018年出版，作者是Lee Vaughan，专注于Python编程的学习和探索。" 在《Impractical Python Projects》中，作者Lee Vaughan为读者提供了一系列不拘一格、富有创意的Python编程项目。这些项目旨在超越传统的教学方法，通过实践操作来提升读者的编程技能，使其在娱乐中学习，从而变得更聪明。书中的每个项目都是经过精心设计的，旨在激发读者的兴趣，同时挑战他们的思维。本书覆盖了多个主题，包括数据处理、游戏开发、网络应用以及可能涉及机器学习的项目。例如，其中可能包含了如何使用Python解析和处理复杂的数据集，或者构建互动式的小游戏。此外，书中还可能探讨了如何利用Python进行网络爬虫的编写，获取并分析互联网上的信息。为了确保读者能够顺利进行这些项目，Lee Vaughan邀请了多位专家作为技术审阅者，如Jeremy Kun、Michael Contraveos和Michele Pratusevich，他们对书中的代码和技术细节进行了严格审查，以保证内容的准确性和实用性。同时，还有专业的编辑团队负责内容的开发、校对和设计，以提供最佳的阅读体验。值得注意的是，书中的一些插图和图片，如Figure 4-1来自美国国会图书馆，Figure 7-1来源于vecteezy.com，以及Chapter 11中使用的door图像由Dood设计，这些都增强了内容的视觉吸引力，并帮助读者更好地理解和应用书中的概念。《Impractical Python Projects》是一本适合有一定Python基础，希望通过实际项目提升技能的读者的书籍。它鼓励读者跳出常规，通过有趣的实践项目来挑战自我，提升编程能力，使学习过程更加生动有趣。通过这本书，读者不仅可以掌握Python编程的实用技巧，还能在解决问题的过程中锻炼思维，提高创造力。

Calculating Eccentricity
Defining Functions to Make Labels
Mapping Soil Moisture
Casting a Shadow
Defining the main() Function
Instantiating Objects, Setting Up Orbit Verification, Mapping, and Timekeeping
Starting the Game Loop and Playing Sounds
Applying Gravity, Calculating Eccentricity, and Handling Failure
Rewarding Success and Updating and Drawing Sprites
Displaying Instructions and Telemetry and Casting a Shadow
Summary
Challenge Projects
Game Title Screen
Smart Gauges
Radio Blackout
Scoring
Strategy Guide
Aerobraking
Intruder Alert!
Over the Top
15
IMPROVING YOUR ASTROPHOTOGRAPHY WITH PLANET STACKING
Project #23: Stacking Jupiter
The pillow Module
Working with Files and Folders
Directory Paths
The Shell Utilities Module
The Video
The Strategy
The Code
The Cropping and Scaling Code
The Stacking Code
The Enhancing Code
Summary
Further Reading
Challenge Project: Vanishing Act
16

INTRODUCTION

Welcome to Impractical Python Projects! Here, you’ll use the Python programming language to

explore Mars, Jupiter, and the farthest reaches of the galaxy; the souls of poets; the world of high

finance; the underworld of espionage and vote tampering; the trickery of game shows; and more.

You’ll use techniques such as Markov chain analysis to write haiku, Monte Carlo simulation to model

financial markets, image stacking to improve your astrophotography, and genetic algorithms to

breed an army of gigantic rats, all while gaining experience with modules like pygame, Pylint,

pydocstyle, tkinter, python-docx, matplotlib, and pillow. And most of all, you’ll have fun.

Who This Book Is For

You can think of this as your second Python book. It’s designed to follow and complement either a

complete beginner’s book or an introductory class. You’ll be able to continue self-training using a

project-based approach, without wasting your money or shelf space on a thorough rehashing of

concepts you’ve already learned. But don’t worry, I won’t leave you hanging; all the code is

annotated and explained.

These projects are for anyone who wants to use programming to conduct experiments, test

theories, simulate nature, or just have fun. This includes people who use programming as part of

their jobs (like scientists and engineers) but who aren’t programmers per se, as well as those I call the

“determined non-specialists”—dilettantes and dabblers who enjoy programming problems as a fun

pastime. If you’ve wanted to toy with the concepts presented here but found starting potentially

complicated projects from scratch too daunting or time-consuming, this book is for you.

What’s in This Book

As you work through the projects, you’ll increase your knowledge of useful Python libraries and

modules; learn more shortcuts, built-in functions, and helpful techniques; and practice designing,

testing, and optimizing programs. Additionally, you’ll be able to relate what you’re doing to real-

world applications, datasets, and issues.

To quote Ralph Waldo Emerson, “Nothing great was ever achieved without enthusiasm.” This

includes the learning experience. The ultimate goal of this book is to spark your imagination and
lead you to develop interesting projects of your own. Don’t worry if they seem too ambitious at first;
a little diligence and a lot of googling can work miracles—and faster than you think.
The following is an overview of the chapters in this book. You don’t have to work through them
sequentially, but the easiest projects are at the beginning, and I explain new concepts, modules, and
techniques more thoroughly when they’re first introduced.
Chapter 1: Silly Name Generator This warm-up project introduces the Python PEP 8 and
PEP 257 style guides as well as the Pylint and pydocstyle modules, which analyze your code’s
conformance to these guidelines. The end product is a goofy-name generator inspired by the
USA Network TV show Psych.
Chapter  2:  Finding  Palingram  Spells  Learn  how  to  profile  your  code  while  saving  DC
Comics  sorceress  Zatanna  from  a  painful  death.  Search  online  dictionaries  for  the  magical
palingrams that Zatanna needs to beat a time-reversing villain.
Chapter  3:  Solving  Anagrams Write a program that helps a user  create a phrase anagram
from their name; for example, Clint Eastwood yields old west action. Then help Tom Marvolo
Riddle derive his anagram, “I am Lord Voldemort,” using linguistic sieves.
Chapter 4: Decoding American Civil War Ciphers Investigate and crack one of the most
successful  military  ciphers  in  history, the  Union  route cipher. Then  help  spies  on  both  sides
send and decode secret messages using the zig-zagging rail fence cipher.
Chapter 5: Encoding English Civil War Ciphers Read a message hidden in plain sight by
decoding a  null  cipher  from  the  English  Civil  War.  Then  save  the head  of Mary,  Queen  of
Scots, by designing and implementing code to accomplish the more difficult task of writing  a
null cipher.
Chapter 6: Writing in Invisible Ink Help a corporate mole betray Sherlock Holmes’s dad
and evade detection with invisible electronic ink. This chapter is based on an episode of the CBS
television show Elementary.
Chapter  7:  Breeding  Giant  Rats  with  Genetic  Algorithms  Use  genetic  algorithms—
inspired by Darwinian evolution—to breed a race of super-rats the size of female bullmastiffs.
Then help James Bond crack a safe with 10 billion possible combinations in the blink of an eye.
Chapter 8: Counting Syllables for Haiku Poetry Teach your computer to count syllables
in English as a prelude to writing Japanese poetry, or haiku, in the next chapter.
Chapter 9: Writing Haiku  with  Markov Chain  Analysis Teach your computer to write
haiku by combining the syllable-counting module from Chapter 8 with Markov chain analysis
and a training corpus of several hundred ancient and modern haiku.
Chapter  10:  Are  We  Alone?  Exploring  the  Fermi  Paradox  Investigate  the absence  of
alien  radio  signals  using  Drake’s  equation,  the  dimensions  of  the  Milky  Way  galaxy,  and
assumptions about the size of detectable “emissions bubbles.” Learn and use the popular tkinter