Values, Types, Variable Names, and Keywords

A value is one of the basic things a program works with, like a letter or a number.

These values belong to different types: 2 is an integer, and 'Hello, World!' is a string, so-called because it contains a "string" of letters. You (and the interpreter) can identify strings because they are enclosed in quotation marks.

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'>

What about values like '17' and '3.2'? They look like numbers, but they are in quotation marks like strings.

>>> type('17')
<type 'str'>
>>> type('3.2')
<type 'str'>

They're strings.

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.

Source: Allen B. Downey, http://www.greenteapress.com/thinkpython/html/thinkpython003.html
This work is licensed under a Creative Commons Attribution 4.0 License.

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

This example makes three assignments. The first assigns a string to a new variable named message; the second gives the integer 17 to n; the third assigns the (approximate) value of π to pi.

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'>

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).

The underscore character, _, can appear in a name. It is often used in names with multiple words, such asmy_name or airspeed_of_unladen_swallow.

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?

It turns out that class is one of Python's keywords. The interpreter uses keywords to recognize the structure of the program, and they cannot be used as variable names.

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.

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, ^ is used for exponentiation, but in Python it is a bitwise operator called XOR. I won't cover bitwise operators in this book, but you can read about them at http://wiki.python.org/moin/BitwiseOperators.

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.

In Python 3, the result of this division is a float. The new operator // performs floor division.

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

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 statements: 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.

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

1
2

The assignment statement produces no output.

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:

• Parentheses have the highest precedence and can be used to force an expression to evaluate in the order you want. Since expressions in parentheses are evaluated first, 2 * (3-1) is 4, and (1+1)**(5-2) is 8. You can also use parentheses to make an expression easier to read, as in (minute * 100) / 60, even if it doesn't change the result.
• Exponentiation has the next highest precedence, so 2**1+1 is 3, not 4, and 3*1**3 is 3, not 27.
• Multiplication and Division have the same precedence, which is higher than Addition and Subtraction, which also have the same precedence. So 2*3-1 is 5, not 4, and 6+4/2 is 8, not 5.
• Operators with the same precedence are evaluated from left to right (except exponentiation). So in the expression degrees / 2 * pi, the division happens first and the result is multiplied by pi. To divide by 2 π, you can use parentheses or write degrees / 2 / pi.

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.

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'

The + operator works with strings, but it might not do what you expect: it performs concatenation, which means joining the strings by linking them end-to-end. For example:

first = 'throat'
second = 'warbler'
print first + second

The output of this program is throatwarbler.

The * operator also works on strings; it performs repetition. For example, 'Spam'*3 is 'SpamSpamSpam'. If one of the operands is a string, the other has to be an integer.

This use of + and * makes sense by analogy with addition and multiplication. Just as 4*3 is equivalent to 4+4+4, we expect 'Spam'*3 to be the same as 'Spam'+'Spam'+'Spam', and it is. On the other hand, there is a significant way in which string concatenation and repetition are different from integer addition and multiplication. Can you think of a property that addition has that string concatenation does not?

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 # symbol:

# 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.

At this point the syntax error you are most likely to make is an illegal variable name, like class and yield, which are keywords, or odd~job  and US$, which contain illegal characters.

If you put a space in a variable name, Python thinks it is two operands without an operator:

>>> bad name = 5
SyntaxError: invalid syntax

For syntax errors, the error messages don't help much. The most common messages are SyntaxError: invalid syntax and SyntaxError: invalid token, neither of which is very informative.

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

Variable names are case sensitive, so LaTeX is not the same as latex.

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.

variable:

A name that refers to a value.

assignment:

A statement that assigns a value to a variable.

state diagram:

A graphical representation of a set of variables and the values they refer to.

keyword:

A reserved word that is used to parse a program; you cannot use keywords like if, def, and while as variable names.

operand:

One of the values on which an operator operates.

expression:

A combination of variables, operators, and values that represents a single result.

evaluate:

To simplify an expression by performing the operations in order to yield a single value.

statement:

A section of code that represents a command or action. So far, the statements we have seen are assignments and print statements.

execute:

To run a statement and do what it says.

interactive mode:

A way of using the Python interpreter by typing code at the prompt.

script mode:

A way of using the Python interpreter to read code from a script and run it.

script:

A program stored in a file.

order of operations:

Rules governing the order in which expressions involving multiple operators and operands are evaluated.

concatenate:

To join two operands end-to-end.

comment:

Information in a program that is meant for other programmers (or anyone reading the source code) and has no effect on the execution of the program.

syntax error:

An error in a program that makes it impossible to parse (and therefore impossible to interpret).

exception:

An error that is detected while the program is running.

semantics:

The meaning of a program.

semantic error:

An error in a program that makes it do something other than what the programmer intended.