Chapter 1 The way of the program
The goal of this book is to teach you to think like a computer scientist. This way of thinking combines some of the best features of mathematics, engineering, and natural science. Like mathematicians, computer scientists use formal languages to denote ideas (specifically computations). Like engineers, they design things, assembling components into systems and evaluating tradeoffs among alternatives. Like scientists, they observe the behavior of complex systems, form hypotheses, and test predictions.
The single most important skill for a computer scientist is problem solving. Problem solving means the ability to formulate problems, think creatively about solutions, and express a solution clearly and accurately. As it turns out, the process of learning to program is an excellent opportunity to practice problem-solving skills. That’s why this chapter is called, “The way of the program”.
On one level, you will be learning to program, a useful skill by itself. On another level, you will use programming as a means to an end. As we go along, that end will become clearer.
1.1 What is a program?
A program is a sequence of instructions that specifies how to perform a computation. The computation might be something mathematical, such as solving a system of equations or finding the roots of a polynomial, but it can also be a symbolic computation, such as searching and replacing text in a document or something graphical, like processing an image or playing a video.
The details look different in different languages, but a few basic instructions appear in just about every language:
Believe it or not, that’s pretty much all there is to it. Every program you’ve ever used, no matter how complicated, is made up of instructions that look pretty much like these. So you can think of programming as the process of breaking a large, complex task into smaller and smaller subtasks until the subtasks are simple enough to be performed with one of these basic instructions.
1.2 Running Python
One of the challenges of getting started with Python is that you might have to install Python and related software on your computer. If you are familiar with your operating system, and especially if you are comfortable with the command-line interface, you will have no trouble installing Python. But for beginners, it can be painful to learn about system administration and programming at the same time.
There are a number of web pages you can use to run Python. If you already have a favorite, go ahead and use it. Otherwise I recommend PythonAnywhere. I provide detailed instructions for getting started at http://tinyurl.com/thinkpython2e.
There are two versions of Python, called Python 2 and Python 3. They are very similar, so if you learn one, it is easy to switch to the other. In fact, there are only a few differences you will encounter as a beginner. This book is written for Python 3, but I include some notes about Python 2.
The Python interpreter is a program that reads and executes Python code. Depending on your environment, you might start the interpreter by clicking on an icon, or by typing python on a command line. When it starts, you should see output like this:
Python 3.4.0 (default, Jun 19 2015, 14:20:21) [GCC 4.8.2] on linux Type "help", "copyright", "credits" or "license" for more information. >>>
The first three lines contain information about the interpreter and the operating system it’s running on, so it might be different for you. But you should check that the version number, which is 3.4.0 in this example, begins with 3, which indicates that you are running Python 3. If it begins with 2, you are running (you guessed it) Python 2.
>>> 1 + 1 2
Now you’re ready to get started. From here on, I assume that you know how to start the Python interpreter and run code.
1.3 The first program
Traditionally, the first program you write in a new language is called “Hello, World!” because all it does is display the words “Hello, World!”. In Python, it looks like this:
>>> print('Hello, World!')
This is an example of a print statement, although it doesn’t actually print anything on paper. It displays a result on the screen. In this case, the result is the words
The parentheses indicate that print is a function. We’ll get to functions in Chapter 3.
>>> print 'Hello, World!'
This distinction will make more sense soon, but that’s enough to get started.
1.4 Arithmetic operators
After “Hello, World”, the next step is arithmetic. Python provides operators, which are special symbols that represent computations like addition and multiplication.
The operators +, -, and * perform addition, subtraction, and multiplication, as in the following examples:
>>> 40 + 2 42 >>> 43 - 1 42 >>> 6 * 7 42
The operator / performs division:
>>> 84 / 2 42.0
You might wonder why the result is 42.0 instead of 42. I’ll explain in the next section.
Finally, the operator ** performs exponentiation; that is, it raises a number to a power:
>>> 6**2 + 6 42
In some other languages,
>>> 6 ^ 2 4
I won’t cover bitwise operators in this book, but you can read about them at http://wiki.python.org/moin/BitwiseOperators.
1.5 Values and types
A value is one of the basic things a program works with, like a
letter or a number. Some values we have seen so far are 2,
If you are not sure what type a value has, the interpreter can tell you:
>>> type(2) <class 'int'> >>> type(42.0) <class 'float'> >>> type('Hello, World!') <class 'str'>
>>> type('2') <class 'str'> >>> type('42.0') <class 'str'>
When you type a large integer, you might be tempted to use commas between groups of digits, as in 1,000,000. This is not a legal integer in Python, but it is legal:
>>> 1,000,000 (1, 0, 0)
1.6 Formal and natural languages
Natural languages are the languages people speak, such as English, Spanish, and French. They were not designed by people (although people try to impose some order on them); they evolved naturally.
Formal languages are languages that are designed by people for specific applications. For example, the notation that mathematicians use is a formal language that is particularly good at denoting relationships among numbers and symbols. Chemists use a formal language to represent the chemical structure of molecules. And most importantly:
Programming languages are formal languages that have been designed to express computations.
Formal languages tend to have strict syntax rules that govern the structure of statements. For example, in mathematics the statement 3 + 3 = 6 has correct syntax, but 3 + = 3 $ 6 does not. In chemistry H2O is a syntactically correct formula, but 2Zz is not.
Syntax rules come in two flavors, pertaining to tokens and structure. Tokens are the basic elements of the language, such as words, numbers, and chemical elements. One of the problems with 3 += 3 $ 6 is that $ is not a legal token in mathematics (at least as far as I know). Similarly, 2Zz is not legal because there is no element with the abbreviation Zz.
The second type of syntax rule pertains to the way tokens are combined. The equation 3 +/ 3 is illegal because even though + and / are legal tokens, you can’t have one right after the other. Similarly, in a chemical formula the subscript comes after the element name, not before.
This is @ well-structured Engli$h sentence with invalid t*kens in it. This sentence all valid tokens has, but invalid structure with.
When you read a sentence in English or a statement in a formal language, you have to figure out the structure (although in a natural language you do this subconsciously). This process is called parsing.
Because we all grow up speaking natural languages, it is sometimes hard to adjust to formal languages. The difference between formal and natural language is like the difference between poetry and prose, but more so:
Formal languages are more dense than natural languages, so it takes longer to read them. Also, the structure is important, so it is not always best to read from top to bottom, left to right. Instead, learn to parse the program in your head, identifying the tokens and interpreting the structure. Finally, the details matter. Small errors in spelling and punctuation, which you can get away with in natural languages, can make a big difference in a formal language.
Programming, and especially debugging, sometimes brings out strong emotions. If you are struggling with a difficult bug, you might feel angry, despondent, or embarrassed.
There is evidence that people naturally respond to computers as if they were people. When they work well, we think of them as teammates, and when they are obstinate or rude, we respond to them the same way we respond to rude, obstinate people (Reeves and Nass, The Media Equation: How People Treat Computers, Television, and New Media Like Real People and Places).
Preparing for these reactions might help you deal with them. One approach is to think of the computer as an employee with certain strengths, like speed and precision, and particular weaknesses, like lack of empathy and inability to grasp the big picture.
Your job is to be a good manager: find ways to take advantage of the strengths and mitigate the weaknesses. And find ways to use your emotions to engage with the problem, without letting your reactions interfere with your ability to work effectively.
Learning to debug can be frustrating, but it is a valuable skill that is useful for many activities beyond programming. At the end of each chapter there is a section, like this one, with my suggestions for debugging. I hope they help!
It is a good idea to read this book in front of a computer so you can try out the examples as you go.
Whenever you are experimenting with a new feature, you should try to make mistakes. For example, in the “Hello, world!” program, what happens if you leave out one of the quotation marks? What if you leave out both? What if you spell print wrong?
This kind of experiment helps you remember what you read; it also helps when you are programming, because you get to know what the error messages mean. It is better to make mistakes now and on purpose than later and accidentally.
Start the Python interpreter and use it as a calculator.
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