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 “Hello, World!”
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.
The print
statement also works for integers. We use the
python
command to start the interpreter.
python
>>> print(4)
4
If you are not sure what type a value has, the interpreter can tell you.
>>> type('Hello, World!')
<class 'str'>
>>> type(17)
<class '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)
<class 'float'>
What about values like “17” and “3.2”? They look like numbers, but they are in quotation marks like strings.
>>> type('17')
<class 'str'>
>>> type('3.2')
<class '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:
>>> print(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, which it prints with spaces between.
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 = 3.1415926535897931
This example makes three assignments. The first assigns a string to a
new variable named message
; the second assigns the integer
17 to n
; the third assigns the (approximate) value of π to pi
.
To display the value of a variable, you can use a print statement:
>>> print(n)
17
>>> print(pi)
3.141592653589793
The type of a variable is the type of the value it refers to.
>>> type(message)
<class 'str'>
>>> type(n)
<class 'int'>
>>> type(pi)
<class 'float'>
Programmers generally choose names for their variables that are meaningful and document what the variable is used for.
Variable names can be arbitrarily long. They can contain both letters and numbers, but they cannot start with a number. 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 as my_name
or
airspeed_of_unladen_swallow
. Variable names can start with
an underscore character, but we generally avoid doing this unless we are
writing library code for others to use.
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 begins with a number.
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 reserves 35 keywords:
False await else import pass
None break except in raise
True class finally is return
and continue for lambda try
as def from nonlocal while
assert del global not with
async elif if or yield
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.
A statement is a unit of code that the Python interpreter can execute. We have seen two kinds of statements: print being an expression statement and assignment.
When you type a statement in interactive mode, the interpreter executes it and displays the result, if there is one.
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.
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)
There has been a change in the division operator between Python 2 and Python 3. In Python 3, the result of this division is a floating point result:
>>> minute = 59
>>> minute/60
0.9833333333333333
The division operator in Python 2 would divide two integers and truncate the result to an integer:
>>> minute = 59
>>> minute/60
0
To obtain the same answer in Python 3 use floored ( //
integer) division.
>>> minute = 59
>>> minute//60
0
In Python 3 integer division functions much more as you would expect if you entered the expression on a calculator.
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
If you type an expression in interactive mode, the interpreter evaluates it and displays the result:
>>> 1 + 1
2
But in a script, an expression all by itself doesn’t do anything! This is a common source of confusion for beginners.
Exercise 1: Type the following statements in the Python interpreter to see what they do:
5
x = 5
x + 1
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. So the expression 5-3-1
is 1, not 3, because the
5-3
happens first and then 1
is subtracted
from 2.
When in doubt, always put parentheses in your expressions to make sure the computations are performed in the order you intend.
The modulus operator works on integers and yields the
remainder when the first operand is divided by the second. In Python,
the modulus operator is a percent sign (%
). The syntax is
the same as for other operators:
>>> quotient = 7 // 3
>>> print(quotient)
2
>>> remainder = 7 % 3
>>> print(remainder)
1
So 7 divided by 3 is 2 with 1 left over.
The modulus operator turns out to be surprisingly useful. For
example, you can check whether one number is divisible by another: if
x % y
is zero, then x
is divisible by
y
.
You can also extract the right-most digit or digits from a number.
For example, x % 10
yields the right-most digit of
x
(in base 10). Similarly, x % 100
yields the
last two digits.
The +
operator works with strings, but it is not
addition in the mathematical sense. Instead it performs
concatenation, which means joining the strings by linking them
end to end. For example:
>>> first = 10
>>> second = 15
>>> print(first+second)
25
>>> first = '100'
>>> second = '150'
>>> print(first + second)
100150
The *
operator also works with strings by multiplying
the content of a string by an integer. For example:
>>> first = 'Test '
>>> second = 3
>>> print(first * second)
Test Test Test
Sometimes we would like to take the value for a variable from the
user via their keyboard. Python provides a built-in function called
input
that gets input from the keyboard1.
When this function is called, the program stops and waits for the user
to type something. When the user presses Return
or
Enter
, the program resumes and input
returns
what the user typed as a string.
>>> inp = input()
Some silly stuff
>>> print(inp)
Some silly stuff
Before getting input from the user, it is a good idea to print a
prompt telling the user what to input. You can pass a string to
input
to be displayed to the user before pausing for
input:
>>> name = input('What is your name?\n')
What is your name?
Chuck
>>> print(name)
Chuck
The sequence \n
at the end of the prompt represents a
newline, which is a special character that causes a line break.
That’s why the user’s input appears below the prompt.
If you expect the user to type an integer, you can try to convert the
return value to int
using the int()
function:
>>> prompt = 'What...is the airspeed velocity of an unladen swallow?\n'
>>> speed = input(prompt)
What...is the airspeed velocity of an unladen swallow?
17
>>> int(speed)
17
>>> int(speed) + 5
22
But if the user types something other than a string of digits, you get an error:
>>> speed = input(prompt)
What...is the airspeed velocity of an unladen swallow?
What do you mean, an African or a European swallow?
>>> int(speed)
ValueError: invalid literal for int() with
base 10: 'What do you mean, an African or a European swallow?'
We will see how to handle this kind of error later.
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 in Python 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 trade-off.
As long as you follow the simple rules of variable naming, and avoid reserved words, you have a lot of choice when you name your variables. In the beginning, this choice can be confusing both when you read a program and when you write your own programs. For example, the following three programs are identical in terms of what they accomplish, but very different when you read them and try to understand them.
a = 35.0
b = 12.50
c = a * b
print(c)
hours = 35.0
rate = 12.50
pay = hours * rate
print(pay)
x1q3z9ahd = 35.0
x1q3z9afd = 12.50
x1q3p9afd = x1q3z9ahd * x1q3z9afd
print(x1q3p9afd)
The Python interpreter sees all three of these programs as exactly the same but humans see and understand these programs quite differently. Humans will most quickly understand the intent of the second program because the programmer has chosen variable names that reflect their intent regarding what data will be stored in each variable.
We call these wisely chosen variable names “mnemonic variable names”. The word mnemonic2 means “memory aid”. We choose mnemonic variable names to help us remember why we created the variable in the first place.
While this all sounds great, and it is a very good idea to use mnemonic variable names, mnemonic variable names can get in the way of a beginning programmer’s ability to parse and understand code. This is because beginning programmers have not yet memorized the reserved words (there are only 35 of them) and sometimes variables with names that are too descriptive start to look like part of the language and not just well-chosen variable names.
Take a quick look at the following Python sample code which loops through some data. We will cover loops soon, but for now try to just puzzle through what this means:
for word in words:
print(word)
What is happening here? Which of the tokens (for, word, in, etc.) are reserved words and which are just variable names? Does Python understand at a fundamental level the notion of words? Beginning programmers have trouble separating what parts of the code must be the same as this example and what parts of the code are simply choices made by the programmer.
The following code is equivalent to the above code:
for slice in pizza:
print(slice)
It is easier for the beginning programmer to look at this code and know which parts are reserved words defined by Python and which parts are simply variable names chosen by the programmer. It is pretty clear that Python has no fundamental understanding of pizza and slices and the fact that a pizza consists of a set of one or more slices.
But if our program is truly about reading data and looking for words
in the data, pizza
and slice
are very
un-mnemonic variable names. Choosing them as variable names distracts
from the meaning of the program.
After a pretty short period of time, you will know the most common reserved words and you will start to see the reserved words jumping out at you:
for word in words: print(word)
The parts of the code that are defined by Python (for
,
in
, print
, and :
) are in bold and
the programmer-chosen variables (word
and
words
) are not in bold. Many text editors are aware of
Python syntax and will color reserved words differently to give you
clues to keep your variables and reserved words separate. After a while
you will begin to read Python and quickly determine what is a variable
and what is a reserved word.
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
which is
not 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
Variables 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 1/2π, 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.
if
, def
, and
while
as variable names.
%
), that works on
integers and yields the remainder when one number is divided by another.
int
), floating-point numbers (type float
), and
strings (type str
).
Exercise 2: Write a program that uses
input
to prompt a user for their name and then welcomes
them.
Enter your name: Chuck
Hello Chuck
Exercise 3: Write a program to prompt the user for hours and rate per hour to compute gross pay.
Enter Hours: 35
Enter Rate: 2.75
Pay: 96.25
We won’t worry about making sure our pay has exactly two digits after
the decimal place for now. If you want, you can play with the built-in
Python round
function to properly round the resulting pay
to two decimal places.
Exercise 4: Assume that we execute the following assignment statements:
width = 17
height = 12.0
For each of the following expressions, write the value of the expression and the type (of the value of the expression).
width//2
width/2.0
height/3
1 + 2 * 5
Use the Python interpreter to check your answers.
Exercise 5: Write a program which prompts the user for a Celsius temperature, convert the temperature to Fahrenheit, and print out the converted temperature.
In Python 2, this function was named
raw_input
.↩︎
See https://en.wikipedia.org/wiki/Mnemonic for an extended description of the word “mnemonic”.↩︎
If you find a mistake in this book, feel free to send me a fix using Github.