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
'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!') <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
They look like numbers, but they are in quotation marks like
>>> 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:
>>> 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 3.14159265359
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 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
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 >>> [email protected] = 1000000 SyntaxError: invalid syntax >>> class = 'Advanced Theoretical Zymurgy' SyntaxError: invalid syntax
76trombones is illegal because it begins with a number. [email protected] 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 31 keywords1 for its use:
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
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 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
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)
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 division2.
When both of the operands are integers, the result is also an integer; floor division chops off the fractional part, so in this example it truncates the answer 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
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.
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:
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 output of this program is 100150.
Sometimes we would like to take the value for a variable from the user
via their keyboard.
Python provides a built-in function called
raw_input that gets
input from the keyboard3. 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
returns what the user typed as a string.
>>> input = raw_input() Some silly stuff >>> print input 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
raw_input to be displayed to the user before pausing
>>> name = raw_input('What is your name?\n') What is your name? Chuck >>> print name Chuck
\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 = raw_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 = raw_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()
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
# 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 mnemonic4 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 31 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:
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
US$, which contain
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
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 1/2 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.
raw_inputto prompt a user for their name and then welcomes them.
Enter your name: Chuck Hello Chuck
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.
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).
Use the Python interpreter to check your answers.