Chapter 2 Variables, expressions and statements
2.1 Values and types
A value is one of the basic things a program works with,
like a letter or a
number. The values we have seen so far
are 1, 2, and
These values belong to different types:
2 is an integer, and
If you are not sure what type a value has, the interpreter can tell you.
>>> type('Hello, World!') <type 'str'> >>> type(17) <type 'int'>
Not surprisingly, strings belong to the type str and integers belong to the type int. Less obviously, numbers with a decimal point belong to a type called float, because these numbers are represented in a format called floating-point.
>>> type(3.2) <type 'float'>
>>> type('17') <type 'str'> >>> type('3.2') <type 'str'>
When you type a large integer, you might be tempted to use commas between groups of three digits, as in 1,000,000. This is not a legal integer in Python, but it is legal:
>>> 1,000,000 (1, 0, 0)
Well, that’s not what we expected at all! Python interprets 1,000,000 as a comma-separated sequence of integers. This is the first example we have seen of a semantic error: the code runs without producing an error message, but it doesn’t do the “right” thing.
One of the most powerful features of a programming language is the ability to manipulate variables. A variable is a name that refers to a value.
An assignment statement creates new variables and gives them values:
>>> message = 'And now for something completely different' >>> n = 17 >>> pi = 3.1415926535897932
A common way to represent variables on paper is to write the name with an arrow pointing to the variable’s value. This kind of figure is called a state diagram because it shows what state each of the variables is in (think of it as the variable’s state of mind). Figure 2.1 shows the result of the previous example.
The type of a variable is the type of the value it refers to.
>>> type(message) <type 'str'> >>> type(n) <type 'int'> >>> type(pi) <type 'float'>
2.3 Variable names and keywords
Programmers generally choose names for their variables that are meaningful—they document what the variable is used for.
Variable names can be arbitrarily long. They can contain both letters and numbers, but they have to begin with a letter. It is legal to use uppercase letters, but it is a good idea to begin variable names with a lowercase letter (you’ll see why later).
If you give a variable an illegal name, you get a syntax error:
>>> 76trombones = 'big parade' SyntaxError: invalid syntax >>> more@ = 1000000 SyntaxError: invalid syntax >>> class = 'Advanced Theoretical Zymurgy' SyntaxError: invalid syntax
76trombones is illegal because it does not begin with a letter. more@ is illegal because it contains an illegal character, @. But what’s wrong with class?
Python 2 has 31 keywords:
and del from not while as elif global or with assert else if pass yield break except import print class exec in raise continue finally is return def for lambda try
In Python 3, exec is no longer a keyword, but nonlocal is.
You might want to keep this list handy. If the interpreter complains about one of your variable names and you don’t know why, see if it is on this list.
2.4 Operators and operands
Operators are special symbols that represent computations like addition and multiplication. The values the operator is applied to are called operands.
The operators +, -, *, / and ** perform addition, subtraction, multiplication, division and exponentiation, as in the following examples:
20+32 hour-1 hour*60+minute minute/60 5**2 (5+9)*(15-7)
In some other languages,
In Python 2, the division operator might not do what you expect:
>>> minute = 59 >>> minute/60 0
The value of minute is 59, and in conventional arithmetic 59 divided by 60 is 0.98333, not 0. The reason for the discrepancy is that Python is performing floor division. When both of the operands are integers, the result is also an integer; floor division chops off the fraction part, so in this example it rounds down to zero.
If either of the operands is a floating-point number, Python performs floating-point division, and the result is a float:
>>> minute/60.0 0.98333333333333328
2.5 Expressions and statements
An expression is a combination of values, variables, and operators. A value all by itself is considered an expression, and so is a variable, so the following are all legal expressions (assuming that the variable x has been assigned a value):
17 x x + 17
A statement is a unit of code that the Python interpreter can execute. We have seen two kinds of statement: print and assignment.
Technically an expression is also a statement, but it is probably simpler to think of them as different things. The important difference is that an expression has a value; a statement does not.
2.6 Interactive mode and script mode
One of the benefits of working with an interpreted language is that you can test bits of code in interactive mode before you put them in a script. But there are differences between interactive mode and script mode that can be confusing.
For example, if you are using Python as a calculator, you might type
>>> miles = 26.2 >>> miles * 1.61 42.182
The first line assigns a value to miles, but it has no visible effect. The second line is an expression, so the interpreter evaluates it and displays the result. So we learn that a marathon is about 42 kilometers.
But if you type the same code into a script and run it, you get no output at all. In script mode an expression, all by itself, has no visible effect. Python actually evaluates the expression, but it doesn’t display the value unless you tell it to:
miles = 26.2 print miles * 1.61
This behavior can be confusing at first.
A script usually contains a sequence of statements. If there is more than one statement, the results appear one at a time as the statements execute.
For example, the script
print 1 x = 2 print x
produces the output
The assignment statement produces no output.
Type the following statements in the Python interpreter to see what they do:
5 x = 5 x + 1
Now put the same statements into a script and run it. What is the output? Modify the script by transforming each expression into a print statement and then run it again.
2.7 Order of operations
When more than one operator appears in an expression, the order of evaluation depends on the rules of precedence. For mathematical operators, Python follows mathematical convention. The acronym PEMDAS is a useful way to remember the rules:
I don’t work very hard to remember rules of precedence for other operators. If I can’t tell by looking at the expression, I use parentheses to make it obvious.
2.8 String operations
In general, you can’t perform mathematical operations on strings, even if the strings look like numbers, so the following are illegal:
'2'-'1' 'eggs'/'easy' 'third'*'a charm'
first = 'throat' second = 'warbler' print first + second
The output of this program is throatwarbler.
The * operator also works on strings; it performs repetition.
This use of + and * makes sense by
analogy with addition and multiplication. Just as 4*3 is
equivalent to 4+4+4, we expect
As programs get bigger and more complicated, they get more difficult to read. Formal languages are dense, and it is often difficult to look at a piece of code and figure out what it is doing, or why.
For this reason, it is a good idea to add notes to your programs to explain
in natural language what the program is doing. These notes are called
comments, and they start with the
# compute the percentage of the hour that has elapsed percentage = (minute * 100) / 60
In this case, the comment appears on a line by itself. You can also put comments at the end of a line:
percentage = (minute * 100) / 60 # percentage of an hour
Everything from the # to the end of the line is ignored—it has no effect on the program.
Comments are most useful when they document non-obvious features of the code. It is reasonable to assume that the reader can figure out what the code does; it is much more useful to explain why.
This comment is redundant with the code and useless:
v = 5 # assign 5 to v
This comment contains useful information that is not in the code:
v = 5 # velocity in meters/second.
Good variable names can reduce the need for comments, but long names can make complex expressions hard to read, so there is a tradeoff.
If you put a space in a variable name, Python thinks it is two operands without an operator:
>>> bad name = 5 SyntaxError: invalid syntax
The runtime error you are most likely to make is a “use before def;” that is, trying to use a variable before you have assigned a value. This can happen if you spell a variable name wrong:
>>> principal = 327.68 >>> interest = principle * rate NameError: name 'principle' is not defined
At this point the most likely cause of a semantic error is the order of operations. For example, to evaluate 1/2 π, you might be tempted to write
>>> 1.0 / 2.0 * pi
But the division happens first, so you would get π / 2, which is not the same thing! There is no way for Python to know what you meant to write, so in this case you don’t get an error message; you just get the wrong answer.
Assume that we execute the following assignment statements:
width = 17 height = 12.0 delimiter = '.'
For each of the following expressions, write the value of the expression and the type (of the value of the expression).
Use the Python interpreter to check your answers.
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