Python Basics: A Practical Introduction to Python 3 PDF

Python Basics: A Practical Introduction to Python 3 Real Python Python Basics: A Practical Introduction to Python 3 Revised and Updated 4th Edition David Amos, Dan Bader, Joanna Jablonski, Fletcher Heisler Copyright © Real Python (realpython.com), 2012–2020 For online information and ordering of this and other books by Real Python, please visit realpython.com. For more information, please contact us at [email protected]. ISBN: 9781775093329 (paperback) ISBN: 9781775093336 (electronic) Cover design by Aldren Santos Additional editing and proofreading by Jacob Schmitt “Python” and the Python logos are trademarks or registered trade- marks of the Python Software Foundation, used by Real Python with permission from the Foundation. Thank you for downloading this ebook. This ebook is licensed for your personal enjoyment only. This ebook may not be resold or given away to other people. If you would like to share this book with another per- son, please purchase an additional copy for each recipient. If you’re reading this book and did not purchase it, or if it was not purchased for your use only, then please return to realpython.com/pybasics-book and purchase your own copy. Thank you for respecting the hard work behind this book. This is a sample from “Python Basics: A Practical Introduction to Python 3” With the full version of the book you get a complete Python curriculum to go all the way from beginner to intermediate-level. Every step along the way is explained and illustrated with short & clear code samples. Coding exercises within each chapter and our interactive quizzes help fast-track your progress and ensure you always know what to focus on next. Become a fluent Pythonista and gain programming knowledge you can apply in the real-world, today: If you enjoyed the sample chapters you can purchase a full version of the book at realpython.com/pybasics-book What Pythonistas Say About Python Basics: A Practical In- troduction to Python 3 “I love [the book]! The wording is casual, easy to understand, and makes the information ow well. I never feel lost in the material, and it’s not too dense so it’s easy for me to review older chapters over and over. I’ve looked at over 10 di erent Python tutorials/books/online courses, and I’ve probably learned the most from Real Python!” — Thomas Wong “Three years later and I still return to my Real Python books when I need a quick refresher on usage of vital Python commands.” — Rob Fowler “I oundered for a long time trying to teach myself. I slogged through dozens of incomplete online tutorials. I snoozed through hours of bor- ing screencasts. I gave up on countless crufty books from big-time publishers. And then I found Real Python. The easy-to-follow, step-by-step instructions break the big concepts down into bite-sized chunks written in plain English. The authors never forget their audience and are consistently thorough and detailed in their explanations. I’m up and running now, but I constantly refer to the material for guidance.” — Jared Nielsen “I love the book because at the end of each particular lesson there are real world and interesting challenges. I just built a savings estimator that actually re ects my savings account – neat!” — Drew Prescott “As a practice of what you taught I started building simple scripts for people on my team to help them in their everyday duties. When my managers noticed that, I was o ered a new position as a developer. I know there is heaps of things to learn and there will be huge chal- lenges, but I nally started doing what I really came to like. Once again: MANY THANKS!” — Kamil “What I found great about the Real Python courses compared to others is how they explain things in the simplest way possible. A lot of courses, in any discipline really, require the learning of a lot of jargon when in fact what is being taught could be taught quickly and succinctly without too much of it. The courses do a very good job of keeping the examples interesting.” — Stephen Grady “After reading the rst Real Python course I wrote a script to automate a mundane task at work. What used to take me three to ve hours now takes less than ten minutes!” — Brandon Youngdale “Honestly, throughout this whole process what I found was just me looking really hard for things that could maybe be added or improved, but this tutorial is amazing! You do a wonderful job of explaining and teaching Python in a way that people like me, a complete novice, could really grasp. The ow of the lessons works perfectly throughout. The exercises truly helped along the way and you feel very accomplished when you nish up the book. I think you have a gift for making Python seem more attainable to people outside the programming world. This is something I never thought I would be doing or learning and with a little push from you I am learning it and I can see that it will be nothing but bene cial to me in the future!” — Shea Klusewicz “The authors of the courses have NOT forgotten what it is like to be a beginner – something that many authors do – and assume noth- ing about their readers, which makes the courses fantastic reads. The courses are also accompanied by some great videos as well as plenty of references for extra learning, homework assignments and example code that you can experiment with and extend. I really liked that there was always full code examples and each line of code had good comments so you can see what is doing what. I now have a number of books on Python and the Real Python ones are the only ones I have actually nished cover to cover, and they are hands down the best on the market. If like me, you’re not a pro- grammer (I work in online marketing) you’ll nd these courses to be like a mentor due to the clear, u -free explanations! Highly recom- mended!” — Craig Addyman About the Authors At Real Python you’ll learn real-world programming skills from a com- munity of professional Pythonistas from all around the world. The realpython.com website launched in 2012 and currently helps more than three million Python developers each month with free programming tutorials and in-depth learning resources. Everyone who worked on this book is a practitioner with several years of professional experience in the software industry. Here are the mem- bers of the Real Python tutorial team who worked on Python Basics: David Amos is the content technical lead for Real Python. After leav- ing academia in 2015, David worked in various technical positions as a programmer and data scientist. In 2019, David joined Real Python full time to pursue his passion for education. He lead the charge on rewriting and updating the Python Basics curriculum to Python 3. Dan Bader is the owner and editor in chief of Real Python and the main developer of the realpython.com learning platform. Dan has been writing code for more than twenty years and holds a master’s degree in computer science. He’s the author of Python Tricks, a best- selling programming book for intermediate Python developers. Joanna Jablonski is the executive editor of Real Python. She likes natural languages just as much as she likes programming languages. Her love for puzzles, patterns, and pesky little details led her to follow a career in translation. It was only a matter of time before she would fall in love with a new language: Python! She joined Real Python in 2018 and has been helping Pythonistas level up ever since. Fletcher Heisler is the founder of Hunter2, where he teaches de- velopers how to hack and secure modern web apps. As one of the founding members of Real Python, Fletcher wrote the ﬁrst version of the Python curriculum this book is based on in 2012. Contents Contents 8 Foreword 13 1 Introduction 20 1.1 Why This Book?.................... 21 1.2 About Real Python.................. 23 1.3 How to Use This Book................. 24 1.4 Bonus Material and Learning Resources....... 25 2 Setting Up Python 29 2.1 A Note on Python Versions.............. 30 2.2 Windows....................... 31 2.3 macOS......................... 34 2.4 Ubuntu Linux..................... 37 3 Your First Python Program 42 3.1 Write a Python Program............... 43 3.2 Mess Things Up.................... 47 3.3 Create a Variable................... 50 3.4 Inspect Values in the Interactive Window...... 55 3.5 Leave Yourself Helpful Notes............. 58 3.6 Summary and Additional Resources......... 60 4 Strings and String Methods 62 4.1 What Is a String?................... 63 4.2 Concatenation, Indexing, and Slicing......... 69 8 Contents 4.3 Manipulate Strings With Methods.......... 79 4.4 Interact With User Input............... 85 4.5 Challenge: Pick Apart Your User’s Input....... 88 4.6 Working With Strings and Numbers......... 88 4.7 Streamline Your Print Statements.......... 94 4.8 Find a String in a String................ 96 4.9 Challenge: Turn Your User Into a L33t H4x0r.... 99 4.10 Summary and Additional Resources......... 100 5 Numbers and Math 102 5.1 Integers and Floating-Point Numbers........ 103 5.2 Arithmetic Operators and Expressions........ 107 5.3 Challenge: Perform Calculations on User Input... 115 5.4 Make Python Lie to You................ 116 5.5 Math Functions and Number Methods........ 118 5.6 Print Numbers in Style................ 123 5.7 Complex Numbers.................. 126 5.8 Summary and Additional Resources......... 130 6 Functions and Loops 132 6.1 What Is a Function, Really?.............. 133 6.2 Write Your Own Functions.............. 137 6.3 Challenge: Convert Temperatures.......... 146 6.4 Run in Circles..................... 147 6.5 Challenge: Track Your Investments.......... 156 6.6 Understand Scope in Python............. 157 6.7 Summary and Additional Resources......... 162 7 Finding and Fixing Code Bugs 164 7.1 Use the Debug Control Window........... 165 7.2 Squash Some Bugs.................. 171 7.3 Summary and Additional Resources......... 179 8 Conditional Logic and Control Flow 181 8.1 Compare Values.................... 182 8.2 Add Some Logic.................... 186 8.3 Control the Flow of Your Program.......... 194 9 Contents 8.4 Challenge: Find the Factors of a Number....... 206 8.5 Break Out of the Pattern............... 207 8.6 Recover From Errors................. 211 8.7 Simulate Events and Calculate Probabilities..... 217 8.8 Challenge: Simulate a Coin Toss Experiment..... 223 8.9 Challenge: Simulate an Election........... 223 8.10 Summary and Additional Resources......... 224 9 Tuples, Lists, and Dictionaries 226 9.1 Tuples Are Immutable Sequences........... 227 9.2 Lists Are Mutable Sequences............. 237 9.3 Nesting, Copying, and Sorting Tuples and Lists... 251 9.4 Challenge: List of lists................. 257 9.5 Challenge: Wax Poetic................ 258 9.6 Store Relationships in Dictionaries.......... 260 9.7 Challenge: Capital City Loop............. 270 9.8 How to Pick a Data Structure............. 272 9.9 Challenge: Cats With Hats.............. 273 9.10 Summary and Additional Resources......... 274 10 Object-Oriented Programming (OOP) 276 10.1 Deﬁne a Class..................... 277 10.2 Instantiate an Object................. 281 10.3 Inherit From Other Classes.............. 287 10.4 Challenge: Model a Farm............... 296 10.5 Summary and Additional Resources......... 297 11 Modules and Packages 298 11.1 Working With Modules................ 299 11.2 Working With Packages................ 310 11.3 Summary and Additional Resources......... 318 12 File Input and Output 320 12.1 Files and the File System............... 321 12.2 Working With File Paths in Python.......... 324 12.3 Common File System Operations........... 333 12.4 Challenge: Move All Image Files to a New Directory. 350 10 Contents 12.5 Reading and Writing Files.............. 351 12.6 Read and Write CSV Data............... 366 12.7 Challenge: Create a High Scores List......... 377 12.8 Summary and Additional Resources......... 378 13 Installing Packages With pip 379 13.1 Installing Third-Party Packages With pip....... 380 13.2 The Pitfalls of Third-Party Packages......... 390 13.3 Summary and Additional Resources......... 392 14 Creating and Modifying PDF Files 394 14.1 Extracting Text From a PDF............. 395 14.2 Extracting Pages From a PDF............. 402 14.3 Challenge: PdfFileSplitter Class........... 409 14.4 Concatenating and Merging PDFs.......... 410 14.5 Rotating and Cropping PDF Pages.......... 417 14.6 Encrypting and Decrypting PDFs........... 428 14.7 Challenge: Unscramble a PDF............ 433 14.8 Creating a PDF File From Scratch.......... 433 14.9 Summary and Additional Resources......... 440 15 Working With Databases 442 15.1 An Introduction to SQLite.............. 443 15.2 Libraries for Working With Other SQL Databases.. 455 15.3 Summary and Additional Resources......... 456 16 Interacting With the Web 458 16.1 Scrape and Parse Text From Websites........ 459 16.2 Use an HTML Parser to Scrape Websites....... 469 16.3 Interact With HTML Forms.............. 475 16.4 Interact With Websites in Real Time......... 481 16.5 Summary and Additional Resources......... 485 17 Scienti c Computing and Graphing 487 17.1 Use NumPy for Matrix Manipulation......... 488 17.2 Use Matplotlib for Plotting Graphs.......... 499 17.3 Summary and Additional Resources......... 522 11 Contents 18 Graphical User Interfaces 523 18.1 Add GUI Elements With EasyGUI.......... 524 18.2 Example App: PDF Page Rotator........... 536 18.3 Challenge: PDF Page Extraction Application..... 543 18.4 Introduction to Tkinter................ 544 18.5 Working With Widgets................ 548 18.6 Controlling Layout With Geometry Managers.... 573 18.7 Making Your Applications Interactive........ 592 18.8 Example App: Temperature Converter........ 602 18.9 Example App: Text Editor.............. 607 18.10 Challenge: Return of the Poet............. 616 18.11 Summary and Additional Resources......... 618 19 Final Thoughts and Next Steps 620 19.1 Free Weekly Tips for Python Developers....... 622 19.2 Python Tricks: The Book............... 622 19.3 Real Python Video Course Library.......... 623 19.4 Acknowledgements.................. 624 12 Foreword Hello, and welcome to Python Basics: A Practical Introduction to Python 3. I hope you’re ready to learn why so many professional and hobbyist developers are drawn to Python and how you can begin using it on your own projects, small and large, right away. This book is targeted at beginners who either know a little program- ming but not the Python language and ecosystem or are starting fresh with no programming experience whatsoever. If you don’t have a computer science degree, don’t worry. David, Dan, Joanna, and Fletcher will guide you through the important comput- ing concepts while teaching you the Python basics and, just as impor- tantly, skipping the unnecessary details at ﬁrst. Python Is a Full-Spectrum Language When learning a new programming language, you don’t yet have the experience to judge how well it will serve you in the long run. If you’re considering learning Python, let me assure you that this is a good choice. One key reason is that Python is a full-spectrum language. What do I mean by this? Some languages are very good for beginners. They hold your hand and make programming super easy. We can go to the extreme and look at visual languages such as Scratch. In Scratch, you get blocks that represent programming concepts like variables, loops, method calls, and so on, and you drag and drop them on a visual surface. Scratch may be easy to get started with for sim- 13 Contents ple programs, but you cannot build professional applications with it. Name one Fortune 500 company that powers its core business logic with Scratch. Come up empty? Me too, because that would be insanity. Other languages are incredibly powerful for expert developers. The most popular one in this category is likely C++ and its close relative, C. Whichever web browser you used today was likely written in C or C++. Your operating system running that browser was very likely also built with C/C++. Your favorite ﬁrst-person shooter or strategy video game? You nailed it: C/C++. You can do amazing things with these languages, but they are wholly unwelcoming to newcomers looking for a gentle introduction. You might not have read a lot of C++ code. It can almost make your eyes burn. Here’s an example, a real albeit complex one: template _Defer defer(const PID& pid, void (T::*method)(void)) { void (*dispatch)(const PID&, void (T::*)(void)) = &process::template dispatch; return std::tr1::bind(dispatch, pid, method); } Please, just no. Both Scratch and C++ are decidedly not what I would call full- spectrum languages. With Scratch, it’s easy to start, but you have to switch to a “real” language to build real applications. Conversely, you can build real apps with C++, but there’s no gentle on-ramp. You dive headﬁrst into all the complexity of the language, which exists to support these rich applications. 14 Contents Python, on the other hand, is special. It is a full-spectrum language. We often judge the simplicity of a language based on the Hello, World test. That is, what syntax and actions are necessary to get the language to output Hello, World to the user? In Python, it couldn’t be simpler: print("Hello, World") That’s it! However, I ﬁnd this an unsatisfying test. The Hello, World test is useful but really not enough to show the power or complexity of a language. Let’s try another example. Not every- thing here needs to make total sense—just follow along to get the Zen of it. The book covers these concepts and more as you go through. The next example is certainly something you could write as you get near the end of the book. Here’s the new test: What would it take to write a program that ac- cesses an external website, downloads the content to your app in mem- ory, then displays a subsection of that content to the user? Let’s try that experiment using Python 3 with the help of the requests package (which needs to be installed—more on that in chapter 12): import requests resp = requests.get("http://olympus.realpython.org") html = resp.text print(html[86:132]) Incredibly, that’s it! When run, the program outputs something like this: Please log in to access Mount Olympus: This is the easy, getting-started side of the Python spectrum. A few trivial lines can unleash incredible power. Because Python has access to so many powerful but well-packaged libraries, such as requests, it’s often described as having batteries included. 15 Contents So there you have a simple yet powerful starter example. On the real- world side of things, many incredible applications have been written in Python as well. YouTube, the world’s most popular video streaming site, is written in Python and processes more than a million requests per second. Insta- gram is another example of a Python application. Closer to home, we even have realpython.com and my sites, such as talkpython.fm. This full-spectrum aspect of Python means that you can start with the basics and adopt more advanced features as your application de- mands grow. Python Is Popular You might have heard that Python is popular. It may seem that it doesn’t really matter how popular a language is so long as you can build the app you want to build with it. But, for better or worse, the popularity of a programming language is a strong indicator of the quality of libraries you’ll have available as well the number of job openings you’ll ﬁnd. In short, you should tend to gravitate toward more popular technologies as there will be more choices and integrations available. So, is Python actually that popular? Yes it is. You’ll ﬁnd a lot of hype and hyperbole, but there are plenty of stats backing this claim. Let’s look at some analytics presented by stackoverflow.com, a popu- lar question-and-answer site for programmers. Stack Overflow runs a site called Stack Overflow Trends where you can look at the trends for various technologies by tag. When you compare 16 Contents Python to the other likely candidates you could pick to learn program- ming, you’ll see one is unlike the others: You can explore this chart and create similar charts to this one over at insights.stackoverflow.com/trends. Notice the incredible growth of Python compared to the flat or even downward trend of the other usual candidates! If you’re betting your future on the success of a given technology, which one would you choose from this list? That’s just one chart—what does it really tell us? Well, let’s look at another. Stack Overflow does a yearly survey of developers. It’s com- prehensive and very well done. You can ﬁnd the full 2020 results at insights.stackoverflow.com/survey/2020. From that writeup, I’d like to call your attention to a section titled “Most Loved, Dreaded, and Wanted Languages.” In the “Most Wanted” section, you’ll ﬁnd data on the share of “developers who are not developing with the language or technology but have expressed interest in developing with it.” 17 Contents Again, in the graph below, you’ll see that Python is topping the charts and is well above even second place: If you agree with me that the relative popularity of a programming language matters, then Python is clearly a good choice. We Don’t Need You to Be a Computer Scientist One other point that I want to emphasize as you start your Python learning journey is that we don’t need you to be a computer scientist. If that’s your goal, then great. Learning Python is a powerful step in that direction. But the invitation to learn programming is often framed as “We have all these developer jobs going unﬁlled! We need software developers!” That may or may not be true. But, more importantly, programming (even a little programming) can be a personal superpower for you. To illustrate this idea, suppose you are a biologist. Should you drop out of biology and get a job as a front-end web developer? Probably not. But skills such as the one I opened this foreword with, using re- quests to get data from the Web, can be incredibly powerful for you as a biologist. Rather than manually exporting and scraping data from the Web or from spreadsheets, you can use Python to scrape thousands of data sources or spreadsheets in the time it takes you to do just one man- 18 Contents ually. Python skills can take your biology power and amplify it well beyond your colleagues’ to make it your superpower. Dan and Real Python Finally, let me leave you with a comment on your authors. Dan Bader and the other Real Python authors work day in and day out to bring clear and powerful explanations of Python concepts to all of us via realpython.com. They have a unique view into the Python ecosystem and are keyed into what beginners need to know. I’m conﬁdent leaving you in their hands on this Python journey. Go forth and learn this amazing language using this great book. Most importantly, remember to have fun! — Michael Kennedy, Founder of Talk Python (@mkennedy) 19 Chapter 1 Introduction Welcome to Real Python’s Python Basics book, fully updated for Python 3.9! In this book, you’ll learn real-world Python program- ming techniques, illustrated with useful and interesting examples. Whether you’re a new programmer or a professional software devel- oper looking to dive into a new language, this book will teach you all the practical Python that you need to get started on projects of your own. No matter what your ultimate goals may be, if you work with a com- puter at all, then you’ll soon be ﬁnding endless ways to improve your life by automating tasks and solving problems through Python pro- grams that you create. But what’s so great about Python as a programming language? For one, Python is open source freeware, meaning you can download it for free and use it for any purpose, commercial or not. Python also has an amazing community that has built a number of useful tools that you can use in your own programs. Need to work with PDF documents? There’s a comprehensive tool for that. Want to collect data from web pages? No need to start from scratch! 20 1.1. Why This Book? Python was built to be easier to use than other programming lan- guages. It’s usually much easier to read Python code and much faster to write code in Python than in other languages. For instance, here’s some basic code written in C, another commonly used programming language: #include int main(void) { printf("Hello, World\n"); } All the program does is show the text Hello, World on the screen. That was a lot of work to output one phrase! Here’s the same program writ- ten in Python: print("Hello, World") That’s pretty simple, right? The Python code is faster to write and easier to read. We ﬁnd that it looks friendlier and more approachable, too! At the same time, Python has all the functionality of other languages and more. You might be surprised by how many professional products are built on Python code: Instagram, YouTube, Reddit, Spotify, to name just a few. Python is not only a friendly and fun language to learn, but it also pow- ers the technology behind multiple world-class companies and oﬀers fantastic career opportunities for any programmer who masters it. 1.1 Why This Book? Let’s face it: there’s an overwhelming amount of information about Python on the Internet. But many beginners studying on their own have trouble ﬁguring out what to learn and in what order to learn it. 21 1.1. Why This Book? You may be asking yourself, What should I learn about Python in the beginning to get a strong foundation? If so, then this book is for you, no matter if you’re a complete beginner or if you’ve already dabbled in Python or other languages. Python Basics is written in plain English and breaks down the core concepts that you really need to know into bite-sized chunks. This means you’ll learn enough to be dangerous with Python, fast. Instead of just going through a boring list of language features, you’ll see exactly how the diﬀerent building blocks ﬁt together and what’s involved in building real applications and scripts with Python. Step by step, you’ll master fundamental Python concepts that will help you get started on your journey toward learning Python. Many programming books try to cover every last possible variation of every command, which makes it easy for readers to get lost in the details. This approach is great if you’re looking for a reference manual, but it’s a horrible way to learn a programming language. Not only do you spend most of your time cramming things into your head that you’ll never use, but you also don’t have any fun! This book is built on the 80/20 principle, which suggests that you can learn most of what you need to know by focusing on a few crucial con- cepts. We’ll cover the commands and techniques used in the vast ma- jority of cases and focus on how to program real-world solutions to everyday problems. This way, we guarantee that you will: Learn useful programming techniques quickly Spend less time struggling with unimportant complications Find more practical uses for Python in your own life Have more fun in the process 22 1.2. About Real Python Once you’ve mastered the material in this book, you will have gained a strong enough foundation that venturing out on your own into more advanced territory will be a breeze. What you’ll learn here is based on the ﬁrst part of the original Real Python Course initially released in 2012. Over the years, this Python curriculum has been battle-tested by thousands of Pythonistas, data scientists, and developers working for companies big and small, in- cluding Amazon, Red Hat, and Microsoft. For Python Basics, we’ve thoroughly expanded, reﬁned, and updated the material so you can build your Python skills quickly and eﬃciently. 1.2 About Real Python At Real Python, you’ll learn real-world programming skills from a community of professional Pythonistas from all around the world. The realpython.com website launched in 2012 and currently helps more than three million Python developers each month with books, programming tutorials, and other in-depth learning resources. Everyone who worked on this book is a Python practitioner recruited from the Real Python team with several years of professional experi- ence in the software industry. Here’s where you can ﬁnd Real Python on the Web: realpython.com @realpython on Twitter The Real Python Newsletter The Real Python Podcast 23 1.3. How to Use This Book 1.3 How to Use This Book The ﬁrst half of this book is a quick but thorough overview of all the Python fundamentals. You don’t need any prior experience with pro- gramming to get started. The second half is focused on ﬁnding practi- cal solutions to interesting, real-world coding problems. If you’re a beginner, then we recommend that you go through the ﬁrst half of this book from beginning to end. The second half covers topics that don’t overlap as much, so you can jump around more easily, but the chapters do increase in diﬃculty as you go along. If you’re a more experienced programmer, then you may ﬁnd yourself heading toward the second part of the book right away. But don’t ne- glect getting a strong foundation in the basics ﬁrst, and be sure to ﬁll in any knowledge gaps along the way. Most sections within a chapter are followed by review exercises to help you make sure that you’ve mastered all the topics covered. There are also a number of code challenges, which are more involved and usually require you to tie together several diﬀerent concepts from pre- vious chapters. The practice ﬁles that accompany this book also include full solutions to the challenges as well as some of the trickier exercises. But to get the most out of the material, you should try your best to solve the chal- lenge problems on your own before looking at the example solutions. If you’re completely new to programming, then you may want to sup- plement the ﬁrst few chapters with additional practice. We recom- mend working through the entry-level tutorials available for free at realpython.com to make sure you’re on solid footing. If you have any questions or feedback about the book, you’re always welcome to contact us directly. 24 1.4. Bonus Material and Learning Resources Learning by Doing This book is all about learning by doing, so be sure to actually type in the code snippets you encounter in the book. For best results, we recommend that you avoid copying and pasting the code examples. You’ll learn the concepts better and pick up the syntax faster if you type out each line of code yourself. Plus, if you screw up—which is to- tally normal and happens to all developers on a daily basis—the simple act of correcting typos will help you learn how to debug your code. Try to complete the review exercises and code challenges on your own before getting help from outside resources. With enough practice, you’ll master this material—and have fun along the way! How Long Will It Take to Finish This Book? If you’re already familiar with a programming language, then you could ﬁnish this book in as little as thirty-ﬁve to forty hours. If you’re new to programming, then you may need to spend up to one hundred hours or more. Take your time and don’t feel like you have to rush. Programming is a super-rewarding but complex skill to learn. Good luck on your Python journey. We’re rooting for you! 1.4 Bonus Material and Learning Resources This book comes with a number of free bonus resources and down- loads that you can access online at the link below. We’re also main- taining an errata list with corrections there: realpython.com/python-basics/resources 25 1.4. Bonus Material and Learning Resources Interactive Quizzes Most chapters in this book come with a free online quiz to check your learning progress. You can access the quizzes using the links provided at the end of the chapter. The quizzes are hosted on the Real Python website and can be viewed on your phone or computer. Each quiz takes you through a series of questions related to a particu- lar chapter in the book. Some of them are multiple choice, some will ask you to type in an answer, and some will require you to write ac- tual Python code. As you make your way through each quiz, it will keep score of which questions you answered correctly. At the end of the quiz, you’ll receive a grade based on your result. If you don’t score 100 percent on your ﬁrst try, don’t fret! These quizzes are meant to challenge you. It’s expected that you’ll go through them several times, improving your score with each run. Exercises Code Repository This book has an accompanying code repository on the Web contain- ing example source code as well as the answers to exercises and code challenges. The repository is broken up by chapter, so you can check your code against the solutions provided by us after you ﬁnish each chapter. Here’s the link: realpython.com/python-basics/exercises Note The code found in this book has been tested with Python 3.9 on Windows, macOS, and Linux. 26 1.4. Bonus Material and Learning Resources Example Code License The example Python scripts associated with this book are licensed un- der a Creative Commons Public Domain (CC0) License. This means that you’re welcome to use any portion of the code for any purpose in your own programs. Formatting Conventions Code blocks will be used to present example code: # This is Python code: print("Hello, World") Terminal commands follow the Unix format: $ # This is a terminal command: $ python hello-world.py (The dollar signs are not part of the command.) Monospace text will be used to denote a ﬁlename: hello-world.py. Bold text will be used to denote a new or important term. Keyboard shortcuts will be formatted as follows: Ctrl + S Menu shortcuts will be formatted as follows: File New File Notes and important information will be highlighted as follows: Note This is a note ﬁlled in with placeholder text. The quick brown fox jumps over the lazy dog. The quick brown Python slithers over the lazy hog. 27 1.4. Bonus Material and Learning Resources Feedback and Errata We welcome ideas, suggestions, feedback, and the occasional rant. Did you ﬁnd a topic confusing? Did you ﬁnd an error in the text or code? Did we leave out a topic that you’d love to know more about? We’re always looking to improve our teaching materials. Whatever the reason, please send in your feedback at the link below: realpython.com/python-basics/feedback 28 Chapter 2 Setting Up Python This book is about programming computers with Python. You could read this book from cover to cover without ever touching a keyboard, but you’d miss out on the fun part—coding! To get the most out of this book, you need a computer with Python installed on it and a way to create, edit, and save Python code ﬁles. In this chapter, you’ll learn how to: Install the latest version of Python 3 on your computer Open IDLE, Python’s built-in Integrated Development and Learning Environment Let’s get started! 29 2.1. A Note on Python Versions 2.1 A Note on Python Versions Many operating systems, including macOS and Linux, come with Python preinstalled. The version of Python that comes with your operating system is called the system Python. The system Python is used by your operating system and is usually out of date. It’s essential that you have the most recent version of Python so that you can successfully follow along with the examples in this book. Important Do not attempt to uninstall the system Python! You can have multiple versions of Python installed on your computer. In this chapter, you’ll install the latest version of Python 3 alongside any system Python that may already exist on your machine. Note Even if you already have Python 3.9 installed, it’s still a good idea to skim this chapter to double-check that your environ- ment is set up for following along with this book. This chapter is split into three sections: Windows, macOS, and Ubuntu Linux. Find the section for your operating system and follow the steps to get set up, then skip ahead to the next chapter. If you have a diﬀerent operating system, then check out Real Python’s “Python 3 Installation & Setup Guide” to see if your OS is covered. Readers on tablets and mobile devices can refer to the “Online Python Interpreters” section for some browser-based options. 30 2.2. Windows 2.2 Windows Follow these steps to install Python 3 and open IDLE on Windows. Important The code in this book is tested only against Python installed as described in this section. Be aware that if you have installed Python through some other means, such as Anaconda Python, you may encounter problems when running some of the code examples. Install Python Windows doesn’t typically come with a system Python. Fortunately, installation involves little more than downloading and running the Python installer from the Python.org website. Step 1: Download the Python 3 Installer Open a web browser and navigate to the following URL: https://www.python.org/downloads/windows/ Click Latest Python 3 Release - Python 3.x.x located beneath the “Python Releases for Windows” heading near the top of the page. As of this writing, the latest version was Python 3.9. Then scroll to the bottom and click Windows x86-64 executable in- staller to start the download. Note If your system has a 32-bit processor, then you should choose the 32-bit installer. If you aren’t sure if your computer is 32-bit or 64-bit, stick with the 64-bit installer mentioned above. 31 2.2. Windows Step 2: Run the Installer Open your Downloads folder in Windows Explorer and double-click the ﬁle to run the installer. A dialog that looks like the following one will appear: It’s okay if the Python version you see is greater than 3.9.0 as long as the version is not less than 3. Important Make sure you select the box that says Add Python 3.x to PATH. If you install Python without selecting this box, then you can run the installer again and select it. Click Install Now to install Python 3. Wait for the installation to ﬁnish, then continue to open IDLE. 32 2.2. Windows Open IDLE You can open IDLE in two steps: 1. Click the Start menu and locate the Python 3.9 folder. 2. Open the folder and select IDLE (Python 3.9). IDLE opens a Python shell in a new window. The Python shell is an interactive environment that allows you to type in Python code and execute it immediately. It’s a great way to get started with Python! Note While you’re free to use a code editor other than IDLE if you prefer, note that some chapters, especially chapter 7, “Finding and Fixing Code Bugs,” do contain material speciﬁc to IDLE. The Python shell window looks like this: At the top of the window, you can see the version of Python that is running and some information about the operating system. If you see a version less than 3.9, then you may need to revisit the installation instructions in the previous section. 33 2.3. macOS The >>> symbol that you see is called a prompt. Whenever you see this, it means that Python is waiting for you to give it some instruc- tions. Interactive Quiz This chapter comes with a free online quiz to check your learn- ing progress. You can access the quiz using your phone or com- puter at the following web address: realpython.com/quizzes/pybasics-setup Now that you have Python installed, let’s get straight into writing your ﬁrst Python program! Go ahead and move on to chapter 3. 2.3 macOS Follow these steps to install Python 3 and open IDLE on macOS. Important The code in this book is tested only against Python installed as described in this section. Be aware that if you have installed Python through some other means, such as Anaconda Python, you may encounter problems when running some of the code examples. Install Python To install the latest version of Python 3 on macOS, download and run the oﬃcial installer from the Python.org website. Step 1: Download the Python 3 Installer Open a web browser and navigate to the following URL: https://www.python.org/downloads/mac-osx/ 34 2.3. macOS Click Latest Python 3 Release - Python 3.x.x located beneath the “Python Releases for Mac OS X” heading near the top of the page. As of this writing, the latest version was Python 3.9. Then scroll to the bottom of the page and click macOS 64-bit installer to start the download. Step 2: Run the Installer Open Finder and double-click the downloaded ﬁle to run the installer. A dialog box that looks like the following will appear: Press Continue a few times until you are asked to agree to the software license agreement. Then click Agree. You’ll be shown a window that tells you where Python will be installed and how much space it will take. You most likely don’t want to change the default location, so go ahead and click Install to start the installa- tion. 35 2.3. macOS When the installer is ﬁnished copying ﬁles, click Close to close the installer window. Open IDLE You can open IDLE in three steps: 1. Open Finder and click Applications. 2. Double-click the Python 3.9 folder. 3. Double-click the IDLE icon. IDLE opens a Python shell in a new window. The Python shell is an interactive environment that allows you to type in Python code and execute it immediately. It’s a great way to get started with Python! Note While you’re free to use a code editor other than IDLE if you prefer, note that some chapters, especially chapter 7, “Finding and Fixing Code Bugs,” do contain material speciﬁc to IDLE. The Python shell window looks like this: 36 2.4. Ubuntu Linux At the top of the window, you can see the version of Python that is running and some information about the operating system. If you see a version less than 3.9, then you may need to revisit the installation instructions in the previous section. The >>> symbol that you see is called a prompt. Whenever you see this, it means that Python is waiting for you to give it some instruc- tions. Interactive Quiz This chapter comes with a free online quiz to check your learn- ing progress. You can access the quiz using your phone or com- puter at the following web address: realpython.com/quizzes/pybasics-setup Now that you have Python installed, let’s get straight into writing your ﬁrst Python program! Go ahead and move on to chapter 3. 2.4 Ubuntu Linux Follow these steps to install Python 3 and open IDLE on Ubuntu Linux. Important The code in this book is tested only against Python installed as described in this section. Be aware that if you have installed Python through some other means, such as Anaconda Python, you may encounter problems when running some of the code examples. 37 2.4. Ubuntu Linux Install Python There’s a good chance that your Ubuntu distribution already has Python installed, but it probably won’t be the latest version, and it may be Python 2 instead of Python 3. To ﬁnd out what version(s) you have, open a terminal window and try the following commands: $ python --version $ python3 --version One or more of these commands should respond with a version, as below: $ python3 --version Python 3.9.0 Your version number may vary. If the version shown is Python 2.x or a version of Python 3 that is less than 3.9, then you want to in- stall the latest version. How you install Python on Ubuntu depends on which version of Ubuntu you’re running. You can determine your local Ubuntu version by running the following command: $ lsb_release -a No LSB modules are available. Distributor ID: Ubuntu Description: Ubuntu 18.04.1 LTS Release: 18.04 Codename: bionic Look at the version number next to Release in the console output, and follow the corresponding instructions below. 38 2.4. Ubuntu Linux Ubuntu 18.04 or Greater Ubuntu version 18.04 does not come with Python 3.9 by default, but it is in the Universe repository. You can install it with the following commands in the Terminal application: $ sudo apt-get update $ sudo apt-get install python3.9 idle-python3.9 python3-pip Note that because the Universe repository is usually behind the Python release schedule, you may not get the latest version of Python 3.9. However, any version of Python 3.9 will work for this book. Ubuntu 17 and Lower For Ubuntu versions 17 and lower, Python 3.9 is not in the Universe repository. You need to get it from a Personal Package Archive (PPA). To install Python from the deadsnakes PPA, run the following com- mands in the Terminal application: $ sudo add-apt-repository ppa:deadsnakes/ppa $ sudo apt-get update $ sudo apt-get install python3.9 idle-python3.9 python3-pip You can check that the correct version of Python was installed by run- ning python3 --version. If you see a version number less than 3.9, then you may need to type python3.9 --version. Now you can open IDLE and get ready to write your ﬁrst Python program. Open IDLE You can open IDLE from the command line by typing the following: $ idle-python3.9 39 2.4. Ubuntu Linux On some Linux installations, you can open IDLE with the following shortened command: $ idle3 IDLE opens a Python shell in a new window. The Python shell is an interactive environment that allows you to type in Python code and execute it immediately. It’s a great way to get started with Python! Note While you’re free to use a code editor other than IDLE if you prefer, note that some chapters, especially chapter 7, “Finding and Fixing Code Bugs,” do contain material speciﬁc to IDLE. The Python shell window looks like this: At the top of the window, you can see the version of Python that is running and some information about the operating system. If you see a version less than 3.9, then you may need to revisit the installation instructions in the previous section. 40 2.4. Ubuntu Linux Important If you open IDLE with the idle3 command and see a version less than 3.9 displayed in the Python shell window, then you’ll need to open IDLE with the idle-python3.9 command. The >>> symbol that you see in the IDLE window is called a prompt. Whenever you see this, it means that Python is waiting for you to give it some instructions. Interactive Quiz This chapter comes with a free online quiz to check your learn- ing progress. You can access the quiz using your phone or com- puter at the following web address: realpython.com/quizzes/pybasics-setup Now that you have Python installed, let’s get straight into writing your ﬁrst Python program! Go ahead and move on to chapter 3. 41 Chapter 3 Your First Python Program Now that you have the latest version of Python installed on your com- puter, it’s time to start coding! In this chapter, you will: Write your ﬁrst Python program Learn what happens when you run a program with an error Learn how to declare a variable and inspect its value Learn how to write comments Ready to begin your Python journey? Let’s go! 42 3.1. Write a Python Program 3.1 Write a Python Program If you don’t already have IDLE open, then go ahead and open it. There are two main windows that you’ll work with in IDLE: the interactive window, which is the one that opens when you start IDLE, and the editor window. You can type code into both the interactive window and the editor win- dow. The diﬀerence between the two windows is in how they execute code. In this section, you’ll learn how to execute Python code in both windows. The Interactive Window IDLE’s interactive window contains a Python shell, which is a tex- tual user interface used to interact with the Python language. You can type a bit of Python code into the interactive window and press Enter to immediately see the results. Hence the name interactive window. The interactive window opens automatically when you start IDLE. You’ll see the following text, with some minor diﬀerences depending on your setup, displayed at the top of the window: Python 3.9.0 (tags/v3.9.0:1b293b6) [MSC v.1916 32 bit (Intel)] on win32 Type "help", "copyright", "credits" or "license" for more information. >>> This text shows the version of Python that IDLE is running. You can also see information about your operating system and some commands you can use to get help and view information about Python. The >>> symbol in the last line is called the prompt. This is where you’ll type in your code. 43 3.1. Write a Python Program Go ahead and type 1 + 1 at the prompt and press Enter : >>> 1 + 1 2 >>> Python evaluates the expression, displays the result (2), then displays another prompt. Every time you run some code in the interactive win- dow, a new prompt appears directly below the result. Executing Python in the interactive window can be described as a loop with three steps: 1. Python reads the code entered at the prompt. 2. Python evaluates the code. 3. Python prints the result and waits for more input. This loop is commonly referred to as a read-evaluate-print loop and is abbreviated as REPL. Python programmers sometimes refer to the Python shell as the Python REPL, or just “the REPL” for short. Let’s try something a little more interesting than adding numbers. A rite of passage for every programmer is writing a program that prints the phrase “Hello, World” on the screen. At the prompt in the interactive window, type the word print followed by a set of parentheses with the text "Hello, World" inside: >>> print("Hello, World") Hello, World 44 3.1. Write a Python Program A function is code that performs some task and can be invoked by a name. The above code invokes, or calls, the print() function with the text "Hello, World" as input. The parentheses tell Python to call the print() function. They also en- close everything that gets sent to the function as input. The quotation marks indicate that "Hello, World" really is text and not something else. Note IDLE highlights parts of your code in diﬀerent colors as you type to make it easier for you to identify the diﬀerent parts. By default, functions are highlighted in purple and text is high- lighted in green. The interactive window executes a single line of code at a time. This is useful for trying out small code examples and exploring the Python language, but it has a major limitation: you have to enter your code one line at a time! Alternatively, you can save Python code in a text ﬁle and execute all of the code in the ﬁle to run an entire program. The Editor Window You’ll write your Python ﬁles using IDLE’s editor window. You can open the editor window by selecting File New File from the menu at the top of the interactive window. The interactive window stays open when you open the editor window. It displays the output generated by code in the editor window, so you’ll want to arrange the two windows so that you can see them both at the same time. 45 3.1. Write a Python Program In the editor window, type in the same code you used to print "Hello, World" in the interactive window: print("Hello, World") IDLE highlights code typed into the editor window just like in the in- teractive window. Important When you write code in a Python ﬁle, you don’t need to include the >>> prompt. Before you run your program, you need to save it. Select File Save from the menu and save the ﬁle as hello_world.py. Note On some systems, the default directory for saving ﬁles in IDLE is the Python installation directory. Do not save your ﬁles to this directory. Instead, save them to your desktop or to a folder in your user’s home directory. The.py extension indicates that a ﬁle contains Python code. In fact, saving your ﬁle with any other extension removes the code highlight- ing. IDLE only highlights Python code when it’s stored in a.py ﬁle. Running Python Programs in the Editor Window To run your program, select Run Run Module from the menu in the editor window. Note Pressing F5 also runs a program from the editor window. Program output always appears in the interactive window. 46 3.2. Mess Things Up Every time you run code from a ﬁle, you’ll see something like the fol- lowing output in the interactive window: >>> =================== RESTART =================== IDLE restarts the Python interpreter, which is the computer program that actually executes your code, every time you run a ﬁle. This makes sure that programs are executed the same way each time. Opening Python Files in the Editor Window To open an existing ﬁle in IDLE, select File Open from the menu, then select the ﬁle you want to open. IDLE opens every ﬁle in a new editor window, so you can have several ﬁles open at the same time. You can also open a ﬁle from a ﬁle manager, such as Windows Explorer or macOS Finder. Right-click the ﬁle icon and select Edit with IDLE to open the ﬁle in IDLE’s editor window. Double-clicking on a.py ﬁle from a ﬁle manager executes the pro- gram. However, this usually runs the ﬁle with the system Python, and the program window disappears immediately after the program terminates—often before you can even see any output. For now, the best way to run your Python programs is to open them in IDLE’s editor window and run them from there. 3.2 Mess Things Up Everybody makes mistakes—especially while programming! In case you haven’t made any mistakes yet, let’s get a head start and mess something up on purpose to see what happens. Mistakes in programs are called errors. You’ll experience two main types of errors: syntax errors and runtime errors. 47 3.2. Mess Things Up Syntax Errors A syntax error occurs when you write code that isn’t allowed in the Python language. Let’s create a syntax error by removing the last quotation mark from the code in the hello_world.py ﬁle that you created in the last section: print("Hello, World) Save the ﬁle and press F5 to run it. The code won’t run! IDLE dis- plays an alert box with the following message: EOL while scanning string literal. There are two terms in this message that may be unfamiliar: 1. A string literal is text enclosed in quotation marks. World" is a string literal. "Hello, 2. EOL stands for end of line. So, the message tells you that Python got to the end of a line while reading a string literal. String literals must be terminated with a quo- tation mark before the end of a line. IDLE highlights the line containing print("Hello, World) in red to help you quickly ﬁnd the line of code with the syntax error. Without the second quotation mark, everything after the ﬁrst quotation mark— including the closing parenthesis—is part of a string literal. Runtime Errors IDLE catches syntax errors before a program starts running. In con- trast, runtime errors only occur while a program is running. To generate a runtime error, remove both quotation marks in the hello_world.py ﬁle: 48 3.2. Mess Things Up print(Hello, World) Did you notice how the text color changed to black when you removed the quotation marks? IDLE no longer recognizes Hello, World as text. What do you think will happen when you run the program? Press F5 to ﬁnd out! The following text displays in red in the interactive window: Traceback (most recent call last): File "/home/hello_world.py", line 1, in print(Hello, World) NameError: name 'Hello' is not defined Whenever an error occurs, Python stops executing the program and displays several lines of text called a traceback. The traceback shows useful information about the error. Tracebacks are best read from the bottom up: The last line of the traceback tells you the name of the error and the error message. In this case, a NameError occurred because the name Hello is not deﬁned anywhere. The second to last line shows you the code that produced the error. There’s only one line of code in hello_world.py, so it’s not hard to guess where the problem is. This information is more helpful for larger ﬁles. The third to last line tells you the name of the ﬁle and the line num- ber so you can go to the exact spot in your code where the error occurred. In the next section, you’ll see how to deﬁne names for values in your code. Before you move on, though, you can get some practice with syntax errors and runtime errors by working on the review exercises. 49 3.3. Create a Variable Review Exercises You can nd the solutions to these exercises and many other bonus resources online at realpython.com/python-basics/resources 1. Write a program that IDLE won’t run because it has a syntax error. 2. Write a program that crashes only while it’s running because it has a runtime error. 3.3 Create a Variable In Python, variables are names that can be assigned a value and then used to refer to that value throughout your code. Variables are fundamental to programming for two reasons: 1. Variables keep values accessible: For example, you can as- sign the result of some time-consuming operation to a variable so that your program doesn’t have to perform the operation each time you need to use the result. 2. Variables give values context: The number 28 could mean lots of diﬀerent things, such as the number of students in a class, the number of times a user has accessed a website, and so on. Giving the value 28 a name like num_students makes the meaning of the value clear. In this section, you’ll learn how to use variables in your code, as well as some of the conventions Python programmers follow when choosing names for variables. The Assignment Operator An operator is a symbol, such as +, that performs an operation on one or more values. For example, the + operator takes two numbers, one to the left of the operator and one to the right, and adds them together. 50 3.3. Create a Variable Values are assigned to variable names using a special symbol called the assignment operator (=). The = operator takes the value to the right of the operator and assigns it to the name on the left. Let’s modify the hello_world.py ﬁle from the previous section to assign some text in a variable before printing it to the screen: >>> greeting = "Hello, World" >>> print(greeting) Hello, world On the ﬁrst line, you create a variable named greeting and assign it the value "Hello, World" using the = operator. displays the output Hello, World because Python looks for the name greeting, ﬁnds that it’s been assigned the value "Hello, print(greeting) World", and replaces the variable name with its value before calling the function. If you hadn’t executed greeting = "Hello, World" before executing print(greeting), then you would have seen a NameError like you did when you tried to execute print(Hello, World) in the previous section. Note Although = looks like the equals sign from mathematics, it has a diﬀerent meaning in Python. This distinction is important and can be a source of frustration for beginner programmers. Just remember, whenever you see the = operator, whatever is to the right of it is being assigned to a variable on the left. Variable names are case sensitive, so a variable named greeting is not the same as a variable named Greeting. For instance, the following code produces a NameError: 51 3.3. Create a Variable >>> greeting = "Hello, World" >>> print(Greeting) Traceback (most recent call last): File "", line 1, in NameError: name 'Greeting' is not defined If you have trouble with an example in this book, double-check that every character in your code—including spaces—matches the example exactly. Computers have no common sense, so being almost correct isn’t good enough! Rules for Valid Variable Names Variable names can be as long or as short as you like, but there are a few rules that you must follow. Variable names may contain upper- case and lowercase letters (A–Z, a–z), digits (0–9), and underscores (_), but they cannot begin with a digit. For example, each of the following is a valid Python variable name: string1 _a1p4a list_of_names The following aren’t valid variable names because they start with a digit: 9lives 99_balloons 2beOrNot2Be In addition to English letters and digits, Python variable names may contain many diﬀerent valid Unicode characters. Unicode is a standard for digitally representing characters used in most of the world’s writing systems. That means variable names can contain letters from non-English alphabets, such as decorated letters 52 3.3. Create a Variable like é and ü, and even Chinese, Japanese, and Arabic symbols. However, not every system can display decorated characters, so it’s a good idea to avoid them if you’re going to share your code with people in diﬀerent regions. Note You’ll learn more about Unicode in chapter 12. You can also read about Python’s support for Unicode in the oﬃcial Python documentation. Just because a variable name is valid doesn’t necessarily mean that it’s a good name. Choosing a good name for a variable can be surprisingly diﬃcult. For- tunately, there are some guidelines that you can follow to help you choose better names. Descriptive Names Are Better Than Short Names Descriptive variable names are essential, especially for complex programs. Writing descriptive names often requires using multiple words. Don’t be afraid to use long variable names. In the following example, the value 3600 is assigned to the variable s: s = 3600 The name s is totally ambiguous. Using a full word makes it a lot easier to understand what the code means: seconds = 3600 53 3.3. Create a Variable is a better name than s because it provides more context. But it still doesn’t convey the full meaning of the code. Is 3600 the number seconds of seconds it takes for a process to ﬁnish, or is it the length of a movie? There’s no way to tell. The following name leaves no doubt about what the code means: seconds_per_hour = 3600 When you read the above code, there’s no question that 3600 is the number of seconds in an hour. seconds_per_hour takes longer to type than both the single letter s and the word seconds, but the payoﬀ in clarity is massive. Although naming variables descriptively means using longer variable names, you should avoid using excessively long names. A good rule of thumb is to limit variable names to three or four words maximum. Python Variable Naming Conventions In many programming languages, it’s common to write variable names in mixedCase. In this system, you capitalize the ﬁrst letter of every word except the ﬁrst and leave all other letters in lowercase. For example, numStudents and listOfNames are written in mixedCase. In Python, however, it’s more common to write variable names in lower_case_with_underscores. In this system, you leave every letter in lowercase and separate each word with an underscore. For instance, both num_students and list_of_names are written using the lower_case_with_underscores system. There’s no rule mandating that you write your variable names in lower_case_with_underscores. The practice is codiﬁed, though, in a document called PEP 8, which is widely regarded as the oﬃcial style guide for writing Python. 54 3.4. Inspect Values in the Interactive Window Note PEP stands for Python Enhancement Proposal. A PEP is a de- sign document used by the Python community to propose new features to the language. Following the standards outlined in PEP 8 ensures that your Python code is readable by most Python programmers. This makes sharing code and collaborating with other people easier for everyone involved. Review Exercises You can nd the solutions to these exercises and many other bonus resources online at realpython.com/python-basics/resources 1. Using the interactive window, display some text using print(). 2. Using the interactive window, assign a string literal to a variable. Then print the contents of the variable using the print() function. 3. Repeat the ﬁrst two exercises using the editor window. 3.4 Inspect Values in the Interactive Window Type the following into IDLE’s interactive window: >>> greeting = "Hello, World" >>> greeting 'Hello, World' When you press Enter after typing greeting a second time, Python prints the string literal assigned to greeting even though you didn’t use the print() function. This is called variable inspection. 55 3.4. Inspect Values in the Interactive Window Now print the string assigned to greeting using the print() function: >>> print(greeting) Hello, World Can you spot the diﬀerence between the output displayed by using print() and the output displayed by just entering the variable name and pressing Enter ? When you type the variable name greeting and press Enter , Python prints the value assigned to the variable as it appears in your code. You assigned the string literal "Hello, World" to greeting, which is why 'Hello, World' is displayed with quotation marks. Note String literals can be created with single or double quotation marks in Python. At Real Python, we use double quotes wher- ever possible, whereas IDLE output appears in single quotes by default. Both "Hello, World" and 'Hello, World' mean the same thing in Python—what’s most important is that you be consistent in your usage. You’ll learn more about strings in chapter 4. On the other hand, print() displays a more human-readable represen- tation of the variable’s value which, for string literals, means display- ing the text without quotation marks. Sometimes, both printing and inspecting a variable produce the same output: >>> x = 2 >>> x 2 >>> print(x) 2 56 3.4. Inspect Values in the Interactive Window Here, you assign the number 2 to x. Both using print(x) and inspecting x display output without quotation marks because 2 is a number and not text. In most cases, though, variable inspection gives you more useful information than print(). Suppose you have two variables: x, which is assigned the number 2, and y, which is assigned the string literal "2". In this case, print(x) and print(y) both display the same thing: >>> x = 2 >>> y = "2" >>> print(x) 2 >>> print(y) 2 However, inspecting x and y shows the diﬀerence between each vari- able’s value: >>> x 2 >>> y '2' The key takeaway here is that print() displays a readable representa- tion of a variable’s value, while variable inspection displays the value as it appears in the code. Keep in mind that variable inspection works only in the interactive window. For example, try running the following program from the editor window: greeting = "Hello, World" greeting The program executes without any errors, but it doesn’t display any output! 57 3.5. Leave Yourself Helpful Notes 3.5 Leave Yourself Helpful Notes Programmers sometimes read code they wrote a while ago and won- der, “What does this do?” When you haven’t looked at code in a while, it can be diﬃcult to remember why you wrote it the way you did! To help avoid this problem, you can leave comments in your code. Comments are lines of text that don’t aﬀect the way a program runs. They document what code does or why the programmer made certain decisions. How to Write a Comment The most common way to write a comment is to begin a new line in your code with the # character. When you run your code, Python ig- nores lines starting with #. Comments that start on a new line are called block comments. You can also write inline comments, which are comments that appear on the same line as the code they reference. Just put a # at the end of the line of code, followed by the text in your comment. Here’s an example of a program with both kinds of comments: # This is a block comment. greeting = "Hello, World" print(greeting) # This is an inline comment. Of course, you can still use the # symbol inside a string. For instance, Python won’t mistake the following for the start of a comment: >>> print("#1") #1 In general, it’s a good idea to keep comments as short as possible, but sometimes you need to write more than reasonably ﬁts on a single line. In that case, you can continue your comment on a new line that also begins with the # symbol: 58 3.5. Leave Yourself Helpful Notes # This is my first program. # It prints the phrase "Hello, World" # The comments are longer than the code! greeting = "Hello, World" print(greeting) You can also use comments to comment out code while you’re test- ing a program. Putting a # at the beginning of a line of code lets you run your program as if that line of code didn’t exist, but it doesn’t ac- tually delete the code. To comment out a section of code in IDLE, highlight one or more lines to be commented and press: Windows: Alt + 3 macOS: Ctrl + 3 Ubuntu Linux: Ctrl + D To remove comments, highlight the commented lines and press: Windows: Alt + 4 macOS: Ctrl + 4 Ubuntu Linux: Ctrl + Shift + D Now let’s look at some common conventions for code comments. Conventions and Pet Peeves According to PEP 8, comments should always be written in complete sentences with a single space between the # and the ﬁrst word of the comment: # This comment is formatted to PEP 8. #this one isn't For inline comments, PEP 8 recommends at least two spaces between 59 3.6. Summary and Additional Resources the code and the # symbol: phrase = "Hello, World" # This comment is PEP 8 compliant. print(phrase)# This comment isn't. PEP 8 recommends that comments be used sparingly. A major pet peeve among programmers is comments that describe what is already obvious from reading the code. For example, the comment in the following code is unnecessary: # Print "Hello, World" print("Hello, World") The comment is unnecessary because the code itself explicitly de- scribes what’s happening. Comments are best used to clarify code that may be diﬃcult to understand or to explain why something is coded a certain way. 3.6 Summary and Additional Resources In this chapter, you wrote and executed your ﬁrst Python program! You wrote a small program that displays the text "Hello, World" using the print() function. Then you learned about syntax errors, which occur before IDLE ex- ecutes a program that contains invalid Python code, and runtime errors, which only occur while a program is running. You saw how to assign values to variables using the assignment operator (=) and how to inspect variables in the interactive window. Finally, you learned how to write helpful comments in your code for when you or someone else looks at it in the future. 60 3.6. Summary and Additional Resources Interactive Quiz This chapter comes with a free online quiz to check your learn- ing progress. You can access the quiz using your phone or com- puter at the following web address: realpython.com/quizzes/pybasics-ﬁrst-program Additional Resources To learn more, check out the following resources: “11 Beginner Tips for Learning Python Programming” “Writing Comments in Python (Guide)” For links and additional resources to further deepen your Python skills, visit realpython.com/python-basics/resources 61 Chapter 4 Strings and String Methods Many programmers, regardless of their specialty, deal with text on a daily basis. For example, web developers work with text input from web forms. Data scientists process text to extract data and perform tasks like sentiment analysis, which can help identify and classify opinions in a body of text. Collections of text in Python are called strings. Special functions called string methods are used to manipulate strings. There are string methods for changing a string from lowercase to uppercase, re- moving whitespace from the beginning or end of a string, replacing parts of a string with diﬀerent text, and much more. In this chapter, you’ll learn how to: Manipulate strings with string methods Work with user input Deal with strings of numbers Format strings for printing Let’s get started! 62 4.1. What Is a String? 4.1 What Is a String? In chapter 3, you created the string "Hello, World" and printed it in IDLE’s interactive window using print(). In this section, you’ll get a deeper look into exactly what strings are and the various ways you can create them in Python. The String Data Type Strings are one of the fundamental Python data types. The term data type refers to what kind of data a value represents. Strings are used to represent text. Note There are several other data types built into Python. For exam- ple, you’ll learn about numerical data types in chapter 5 and Boolean data types in chapter 8. We say that strings are a fundamental data type because they can’t be broken down into smaller values of a diﬀerent type. Not all data types are fundamental. You’ll learn about compound data types, also known as data structures, in chapter 9. The string data type has a special abbreviated name in Python: str. You can see this by using type(), which is a function used to determine the data type of a given value. Type the following into IDLE’s interactive window: >>> type("Hello, World") The output indicates that the value "Hello, World" is an instance of the str data type. That is, "Hello, World" is a string. 63 4.1. What Is a String? Note For now, you can think of the word class as a synonym for data type, although it actually refers to something more speciﬁc. You’ll see just what a class is in chapter 10. type() also works for values that have been assigned to a variable: >>> phrase = "Hello, World" >>> type(phrase) Strings have three important properties: 1. Strings contain individual letters or symbols called characters. 2. Strings have a length, deﬁned as the number of characters the string contains. 3. Characters in a string appear in a sequence, which means that each character has a numbered position in the string. Let’s take a closer look at how strings are created. String Literals As you’ve already seen, you can create a string by surrounding some text with quotation marks: string1 = 'Hello, World' string2 = "1234" You can use either single quotes (string1) or double quotes (string2) to create a string as long as you use the same type at the beginning and end of the string. Whenever you create a string by surrounding text with quotation marks, the string is called a string literal. The name indicates that the string is literally written out in your code. All the strings you’ve seen thus far are string literals. 64 4.1. What Is a String? Note Not every string is a string literal. Sometimes strings are input by a user or read from a ﬁle. Since they’re not typed out with quotation marks in your code, they’re not string literals. The quotes surrounding a string are called delimiters because they tell Python where a string begins and where it ends. When one type of quotes is used as the delimiter, the other type can be used inside the string: string3 = "We're #1!" string4 = 'I said, "Put it over by the llama."' After Python reads the ﬁrst delimiter, it considers all the characters after it part of the string until it reaches a second matching delimiter. This is why you can use a single quote in a string delimited by double quotes, and vice versa. If you try to use double quotes inside a string delimited by double quotes, you’ll get an error: >>> text = "She said, "What time is it?"" File "", line 1 text = "She said, "What time is it?"" ^ SyntaxError: invalid syntax Python throws a SyntaxError because it thinks the string ends after the second ", and it doesn’t know how to interpret the rest of the line. If you need to include a quotation mark that matches the delimiter in- side a string, then you can escape the character using a backslash: >>> text = "She said, \"What time is it?\"" >>> print(text) She said, "What time is it?" 65 4.1. What Is a String? Note When you work on a project, it’s a good idea to use only single quotes or only double quotes to delimit every string. Keep in mind that there really isn’t a right or wrong choice! The goal is to be consistent because consistency helps make your code easier to read and understand. Strings can contain any valid Unicode character. For example, the string "We're #1!" contains the pound sign (#) and "1234" contains num- bers. "×Pýŧħøŋ×" is also a valid Python string! Determine the Length of a String The number of characters contained in a string, including spaces, is called the length of the string. For example, the string "abc" has a length of 3, and the string "Don't Panic" has a length of 11. Python has a built-in len() function that you can use to determine the length of a string. To see how it works, type the following into IDLE’s interactive window: >>> len("abc") 3 You can also use len() to get the length of a string that’s assigned to a variable: >>> letters = "abc" >>> len(letters) 3 First, you assign the string "abc" to the variable letters. Then you use len() to get the length of letters, which is 3. 66 4.1. What Is a String? Multiline Strings The PEP 8 style guide recommends that each line of Python code con- tain no more than seventy-nine characters—including spaces. Note PEP 8’s seventy-nine-character line length is a recommenda- tion, not a rule. Some Python programmers prefer a slightly longer line length. In this book, we’ll strictly follow PEP 8’s recommended line length. Whether you follow PEP 8 or choose a longer line length, sometimes you’ll need to create string literals with more characters than your cho- sen limit. To deal with long strings, you can break them up across multiple lines into multiline strings. For example, suppose you need to ﬁt the following text into a string literal: This planet has—or rather had—a problem, which was this: most of the people living on it were unhappy for pretty much of the time. Many solutions were suggested for this problem, but most of these were largely con- cerned with the movements of small green pieces of paper, which is odd because on the whole it wasn’t the small green pieces of paper that were unhappy. — Douglas Adams, The Hitchhiker’s Guide to the Galaxy This paragraph contains far more than seventy-nine characters, so any line of code containing the paragraph as a string literal violates PEP 8. So, what do you do? There are a couple of ways to tackle this. One way is to break the string up across multiple lines and put a backslash (\) at the end of all but the 67 4.1. What Is a String? last line. To be PEP 8 compliant, the total length of the line, including the backslashes, must be seventy-nine characters or fewer. Here’s how you could write the paragraph as a multiline string using the backslash method: paragraph = "This planet has—or rather had—a problem, which was \ this: most of the people living on it were unhappy for pretty much \ of the time. Many solutions were suggested for this problem, but \ most of these were largely concerned with the movements of small \ green pieces of paper, which is odd because on the whole it wasn't \ the small green pieces of paper that were unhappy." Notice that you don’t have to close each line with a quotation mark. Normally, Python would get to the end of the ﬁrst line and complain that you didn’t close the string with a matching double quote. With a backslash at the end, you can keep writing the same string on the next line. When you print() a multiline string that’s broken up by backslashes, the output is displayed on a single line: >>> long_string = "This multiline string is \ displayed on one line" >>> print(long_string) This multiline string is displayed on one line You can also create multiline strings using triple quotes (""" or ''') as delimiters. Here’s how to write a long paragraph using this approach: paragraph = """This planet has—or rather had—a problem, which was this: most of the people living on it were unhappy for pretty much of the time. Many solutions were suggested for this problem, but most of these were largely concerned with the movements of small green pieces of paper, which is odd because on the whole it wasn't the small green pieces of paper that were unhappy.""" 68 4.2. Concatenation, Indexing, and Slicing Triple-quoted strings preserve whitespace, including newlines. This means that running print(paragraph) would display the string on mul- tiple lines, just as it appears in the string literal. This may or may not be what you want, so you’ll need to think about the desired output before you choose how to write a multiline string. To see how whitespace is preserved in a triple-quoted string, type the following into IDLE’s interactive window: >>> print("""An example of a... string that spans across multiple lines... and also preserves whitespace.""") An example of a string that spans across multiple lines and also preserves whitespace. Notice how the second and third lines in the output are indented in exactly the same way as the string literal. Review Exercises You can nd the solutions to these exercises and many other bonus resources online at realpython.com/python-basics/resources 1. Print a string that uses double quotation marks inside the string. 2. Print a string that uses an apostrophe inside the string. 3. Print a string that spans multiple lines with whitespace preserved. 4. Print a string that is coded on multiple lines but gets printed on a single line. 4.2 Concatenation, Indexing, and Slicing Now that you know what a string is and how to declare string literals in your code, let’s explore some of the things you can do with strings. 69 4.2. Concatenation, Indexing, and Slicing In this section, you’ll learn about three basic string operations: 1. Concatenation, which joins two strings together 2. Indexing, which gets a single character from a string 3. Slicing, which gets several characters from a string at once Let’s dive in! String Concatenation You can combine, or concatenate, two strings using the + operator: >>> string1 = "abra" >>> string2 = "cadabra" >>> magic_string = string1 + string2 >>> magic_string 'abracadabra' In this example, the string concatenation occurs on the third line. You concatenate string1 and string2 using +, and then you assign the re- sult to the variable magic_string. Notice that the two strings are joined without any whitespace between them. You can use string concatenation to join two related strings, such as joining a ﬁrst name and a last name into a full name: >>> first_name = "Arthur" >>> last_name = "Dent" >>> full_name = first_name + " " + last_name >>> full_name 'Arthur Dent' Here, you use string concatenation twice on the same line. First, you concatenate first_name with " " to ensure a space appears after the ﬁrst name in the ﬁnal string. This produces the string "Arthur ", which you then concatenate with last_name to produce the full name "Arthur Dent". 70 4.2. Concatenation, Indexing, and Slicing String Indexing Each character in a string has a numbered position called an index. You can access the character at the nth position by putting the number n between two square brackets ([]) immediately after the string: >>> flavor = "fig pie" >>> flavor 'i' flavor returns the character at position 1 in "fig pie", which is i. Wait. Isn’t f the ﬁrst character of "fig pie"? In Python—and in most other programming languages—counting al- ways starts at zero. To get the character at the beginning of a string, you need to access the character at position 0: >>> flavor 'f' Important Forgetting that counting starts with zero and trying to access the ﬁrst character in a string with the index 1 results in an o - by-one error. Oﬀ-by-one errors are a common source of frustration for begin- ning and experienced programmers alike! The following ﬁgure shows the index for each character of the string "fig pie": | f | i | g | | p | i | e | 0 1 2 3 4 5 6 71 4.2. Concatenation, Indexing, and Slicing If you try to access an index beyond the end of a string, then Python raises an IndexError: >>> flavor Traceback (most recent call last): File "", line 1, in flavor IndexError: string index out of range The largest index in a string is always one less than the string’s length. Since "fig pie" has a length of seven, the largest index allowed is 6. Strings also support negative indices: >>> flavor[-1] 'e' The last character in a string has index -1, which for "fig pie" is the letter e. The second to last character i has index -2, and so on. The following ﬁgure shows the negative index for each character in the string "fig pie": | f | i | g | | p | i | e | -7 -6 -5 -4 -3 -2 -1 Just like with positive indices, Python raises an IndexError if you try to access a negative index less than the index of the ﬁrst character in the string: >>> flavor[-10] Traceback (most recent call last): File "", line 1, in flavor[-10] IndexError: string index out of range Negative indices may not seem useful at ﬁrst, but sometimes they’re a better choice than a positive index. 72 4.2. Concatenation, Indexing, and Slicing For example, suppose a string input by a user is assigned to the vari- able user_input. If you need to get the last character of the string, how do you know what index to use? One way to get the last character of a string is to calculate the ﬁnal index using len(): final_index = len(user_input) - 1 last_character = user_input[final_index] Getting the ﬁnal character with the index -1 takes less typing and doesn’t require an intermediate step to calculate the ﬁnal index: last_character = user_input[-1] String Slicing Suppose you need a string containing just the ﬁrst three letters of the string "fig pie". You could access each character by index and con- catenate them like this: >>> first_three_letters = flavor + flavor + flavor >>> first_three_letters 'fig' If you need more than just the ﬁrst few letters of a string, then get- ting each character individually and concatenating them together is clumsy and long-winded. Fortunately, Python provides a way to do this with much less typing. You can extract a portion of a string, called a substring, by inserting a colon between two index numbers set inside square brackets like this: >>> flavor = "fig pie" >>> flavor[0:3] 'fig' 73 4.2. Concatenation, Indexing, and Slicing returns the ﬁrst three characters of the string assigned to flavor, starting with the character at index 0 and going up to but not in- flavor[0:3] cluding the character at index 3. The [0:3] part of flavor[0:3] is called a slice. In this case, it returns a slice of "fig pie". Yum! String slices can be confusing because the substring returned by the slice includes the character whose index is the ﬁrst number but doesn’t include the character whose index is the second number. To remember how slicing works, you can think of a string as a se- quence of square slots. The left and right boundaries of each slot are numbered sequentially from zero up to the length of the string, and each slot is ﬁlled with a character in the string. Here’s what this looks like for the string "fig pie": | f | i | g | | p | i | e | 0 1 2 3 4 5 6 7 So, for "fig pie", the slice [0:3] returns the string "fig", and the slice [3:7] returns the string " pie". If you omit the ﬁrst index in a slice, then Python assumes you want to start at index 0: >>> flavor[:3] 'fig' The slice [:3] is equivalent to the slice [0:3], so flavor[:3] returns the ﬁrst three characters in the string "fig pie". Similarly, if you omit the second index in the slice, then Python as- sumes you want to return the substring that begins with the character 74 4.2. Concatenation, Indexing, and Slicing whose index is the ﬁrst number in the slice and ends with the last char- acter in the string: >>> flavor[3:] ' pie' For "fig pie", the slice [3:] is equivalent to the slice [3:7]. Since the character at index 3 is a space, flavor[3:9] returns the substring that starts with the space and ends with the last letter: " pie". If you omit both the ﬁrst and second numbers in a slice, you get a string that starts with the character at index 0 and ends with the last character. In other words, omitting both numbers in a slice returns the entire string: >>> flavor[:] 'fig pie' It’s important to note that, unlike with string indexing, Python won’t raise an IndexError when you try to slice between boundaries that fall outside the beginning or ending boundaries of a string: >>> flavor[:14] 'f

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