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Also by Mark Myers

A Smarter Way

to Learn Python

Mark Myers

Copyright © 2017 Mark Myers

All rights reserved, including the right to reproduce this book, or any portions of it, in any form.

http://www.ASmarterWayToLearn.com

Digital book(s) (epub and mobi) produced by Booknook.biz.

23: Getting information from the user and converting strings and numbers

24: Changing case

25: Dictionaries: What they are

26: Dictionaries: How to code one

27: Dictionaries: How to pick information out of them

28: Dictionaries: The versatility of keys and values

29: Dictionaries: Adding items

30: Dictionaries: Removing and changing items

31: Dictionaries: Looping through values

32: Dictionaries: Looping through keys

33: Dictionaries: Looping through key-value pairs

34: Creating a list of dictionaries

35: How to pick information out of a list of dictionaries

36: How to append a new dictionary to a list of dictionaries

37: Creating a dictionary that contains lists

38: How to get information out of a list within a dictionary

39: Creating a dictionary that contains a dictionary

40: How to get information out of a dictionary within another dictionary

41: Functions

42: Functions: Passing them information

43: Functions: Passing information to them a different way

44: Functions: Assigning a default value to a parameter

45: Functions: Mixing positional and keyword arguments

46: Functions: Dealing with an unknown number of arguments

47: Functions: Passing information back from them

48: Using functions as variables (which is what they really are)

49: Functions: Local vs. global variables

50: Functions within functions

51: While loops

52: While loops: Setting a flag

53: Classes

54: Classes: Starting to build the structure

55: Classes: A bit of housekeeping

56: Classes: Creating an instance

57: Classes: A little more complexity

58: Classes: Getting info out of instances

59: Classes: Building functions into them

60: Classes: Coding a method

61: Classes: Changing an attribute's value

62: Data files

63: Data files: Storing data

64: Data files: Retrieving data

65: Data files: Appending data

66: Modules

67: CSV files

68: CSV files: Reading them

69: CSV files: Picking information out of them

70: CSV files: Loading information into them. Part 1

71: CSV files: Loading information into them. Part 2

72: CSV files: Loading information into them. Part 3

73: CSV files: Appending rows to them.

74: How to save a Python list or dictionary in a file: JSON

75: How to retrieve a Python list or dictionary from a JSON file

76: Planning for things to go wrong

77: A more practical example of exception handling

Guide to the appendices Appendix A: An easy way to run Python Appendix B: How to install Python on your computer Appendix C: How to run Python in the terminal Appendix D: How to create a Python program that you can save Appendix E: How to run a saved Python program in the terminal

Learn it faster.

Remember it longer.

If you embrace this method of learning, you’ll get the hang of Python in less time than you might expect. And the knowledge will stick. You’ll catch onto concepts quickly. You’ll be less bored, and might even be excited. You’ll certainly be motivated. You’ll feel confident instead of frustrated. You’ll remember the lessons long after you close the book. Is all this too much for a book to promise? Yes, it is. Yet I can make these promises and keep them, because this isn’t just a book. It’s a book plus almost a thousand interactive online exercises. You’re going to learn by doing. You'll read a chapter, then practice with the exercises. That way, the knowledge gets embedded in your memory so you don't forget it. Instant feedback corrects your mistakes like a one-on-one teacher. I’ve done my best to write each chapter so it’s easy for anyone to understand, but it’s the exercises that are going to turn you into a real Python coder. Cognitive research shows that reading alone doesn’t buy you much long- term retention. Even if you read a book a second or even a third time, things won’t improve much, according to research. And forget highlighting or underlining. Marking up a book gives us the illusion that we’re engaging with the material, but studies show that it’s an exercise in self-deception. It doesn’t matter how much yellow you paint on the pages, or how many times you review the highlighted material. By the time you get to Chapter 50, you’ll have forgotten most of what you highlighted in Chapter 1. This all changes if you read less and do more—if you read a short passage and then immediately put it into practice. Washington University researchers say that being asked to retrieve information increases long-term retention by four

hundred percent. That may seem implausible, but by the time you finish this book, I think you’ll believe it. Practice also makes learning more interesting. Trying to absorb long passages of technical material puts you to sleep and kills your motivation. Ten minutes of reading followed by fifteen minutes of challenging practice keeps you awake and spurs you on. And it keeps you honest. If you only read, it’s easy to kid yourself that you’re learning more than you are. But when you’re challenged to produce the goods, there’s a moment of truth. You know that you know—or that you don’t. When you find out that you’re a little shaky on this point or that, you can review the material, then re-do the exercise. That’s all it takes to master this book from beginning to end—and to build a solid foundation of Python knowledge. I’ve talked with many readers who say they thought they had a problem understanding technical concepts. But what looked like a comprehension problem was really a retention problem. If you get to Chapter 50 and everything you studied in Chapter 1 has faded from memory, how can you understand Chapter 50, which depends on your knowing Chapter 1 cold? The read-then- practice approach embeds the concepts of each chapter in your long-term memory, so you’re prepared to tackle material in later chapters that builds on top of those concepts. When you’re able to remember what you read, you’ll find that you learn Python quite readily. I hope you enjoy this learning approach. And I hope you build on it to become a terrific coder.

details, a fundamental requirement for coding in any language.

Subscribe, temporarily, to my formatting biases. Current code formatting is like seventeenth-century spelling. Everyone does it his own way. There are no universally accepted standards. But the algorithms that check your work when you do the interactive exercises need standards. They can't grant you the latitude that a human teacher could, because, let's face it, algorithms aren't that bright. So I've had to settle on certain conventions. All of the conventions I teach are embraced by a large segment of the coding community, so you'll be in good company. But that doesn't mean you'll be married to my formatting biases forever. When you start coding projects, you'll soon develop your own opinions or join an organization that has a stylebook. Until then, I'll ask you to make your code look like my code.

The language you're learning here

Python is a popular, 30-year-old general purpose programming language created by Guido van Rossum. Compared with some other languages, it's reasonably easy to learn, and it's relatively easy to read. Python is often used to teach beginners the fundamentals of programming.

2

Variables for Strings

Please memorize the following facts.

My name is Mark.

My nationality is U.S.

Now that you've memorized my name and nationality, I won't have to repeat them again. If I say to you, "You probably know other people who have my name," you'll know I'm referring to "Mark." If I ask you whether my nationality is the same as yours, I won't have to ask, "Is your nationality the same as U.S.?" I'll ask, "Is your nationality the same as my nationality?" You'll remember that when I say "my nationality," I'm referring to "U.S.", and you'll compare your nationality with "U.S.", even though I haven't said "U.S." explicitly. In these examples, the terms my name and my nationality work the same way Python variables do. my name refers to a particular value, "Mark." In the same way, a variable refers to a particular value. You could say that my name is a variable that refers to the string "Mark." A variable is created this way:

name = "Mark"

Now the variable name refers to the text string "Mark". Note that it was my choice to call it name. I could have called it my_name , xyz , lol , or something else. It's up to me how to name my variables, within limits. More on those limits later. With the string "Mark" assigned to the variable name , my Python code doesn't have to specify "Mark" again. Whenever Python encounters name ,

But that was then. Now if, having written…

name = "Ace"

…if I write…

print(name)

…Python displays...

Ace

A variable can have any number of values, but only one at a time. Python variable names have no inherent meaning to Python. In English, words have meaning. You can't use just any word to communicate. I can say, "My name is Mark," but, if I want to be understood, I can't say, "My floogle is Mark." That's nonsense. But with variables, Python is blind to semantics. You can use just any word (as long as it doesn't break the rules of variable-naming, which I'll cover later). From Python's point of view...

floogle = "Mark"

...is just as good as...

name = "Mark"

If you write...

floogle = "Mark"

...then write…

print(floogle)

…Python displays...

Mark

Within limits, you can name variables anything you want, and Python won't care.

lesson_author = "Mark" guy_who_keeps_saying_his_own_name = "Mark" x = "Mark"

Python's blindness to meaning notwithstanding, when it comes to variable names, you'll want to give your variables meaningful names, because it'll help you and other coders understand your code. Again, the syntactic difference between variables and text strings is that variables are never enclosed in quotes, and text strings are always enclosed in quotes. It's always...

last_name = "Smith" city_of_origin = "New Orleans" aussie_greeting = "g'Day"

If it's an alphabet letter or word, and it isn't enclosed in quotes, and it isn't a keyword that has special meaning for Python, like print , it's a variable. If it's some characters enclosed in quotes, it's a text string. If you haven't noticed, let me point out the spaces between the variable and the equal sign, and between the equal sign and the value.

nickname = "Bub"

These spaces are a style choice rather than a legal requirement. But I'll ask you to include them in your code throughout the practice exercises. In the last chapter you learned to write...