The ternary operator is used for inline conditional expressions. It is best used in simple, concise operations that are easily read.

• The order of the arguments is different from many other languages (such as C, Ruby, Java, etc.), which may lead to bugs when people unfamiliar with Python's "surprising" behaviour use it (they may reverse the order).
• Some find it "unwieldy", since it goes contrary to the normal flow of thought (thinking of the condition first and then the effects).

n = 5

"Greater than 2" if n > 2 else "Smaller than or equal to 2"
# Out: 'Greater than 2'

The result of this expression will be as it is read in English - if the conditional expression is True, then it will evaluate to the expression on the left side, otherwise, the right side.

Tenary operations can also be nested, as here:

n = 5
"Hello" if n > 10 else "Goodbye" if n > 5 else "Good day"

They also provide a method of including conditionals in lambda functions (opens new window).

In Python you can define a series of conditionals using if for the first one, elif for the rest, up until the final (optional) else for anything not caught by the other conditionals.

number = 5

if number > 2:
    print("Number is bigger than 2.")
elif number < 2:  # Optional clause (you can have multiple elifs)
    print("Number is smaller than 2.")
else:  # Optional clause (you can only have one else)
    print("Number is 2.")

Outputs Number is bigger than 2

Using else if instead of elif will trigger a syntax error and is not allowed.

The following values are considered falsey, in that they evaluate to False when applied to a boolean operator.

• None
• False
• 0, or any numerical value equivalent to zero, for example 0L, 0.0, 0j
• Empty sequences: '', "", (), []
• Empty mappings: {}
• User-defined types where the __bool__ or __len__ methods return 0 or False

All other values in Python evaluate to True.

Note: A common mistake is to simply check for the Falseness of an operation which returns different Falsey values where the difference matters. For example, using if foo() rather than the more explicit if foo() is None

Boolean logic expressions, in addition to evaluating to True or False, return the value that was interpreted as True or False. It is Pythonic way to represent logic that might otherwise require an if-else test.

And operator

The and operator evaluates all expressions and returns the last expression if all expressions evaluate to True. Otherwise it returns the first value that evaluates to False:

>>> 1 and 2
2

>>> 1 and 0
0

>>> 1 and "Hello World"
"Hello World"

>>> "" and "Pancakes"
""

Or operator

The or operator evaluates the expressions left to right and returns the first value that evaluates to True or the last value (if none are True).

>>> 1 or 2
1

>>> None or 1
1

>>> 0 or []
[]

Lazy evaluation

When you use this approach, remember that the evaluation is lazy. Expressions that are not required to be evaluated to determine the result are not evaluated. For example:

>>> def print_me():
        print('I am here!')
>>> 0 and print_me()
0

In the above example, print_me is never executed because Python can determine the entire expression is False when it encounters the 0 (False). Keep this in mind if print_me needs to execute to serve your program logic.

Testing for multiple conditions

A common mistake when checking for multiple conditions is to apply the logic incorrectly.

This example is trying to check if two variables are each greater than 2. The statement is evaluated as - if (a) and (b > 2). This produces an unexpected result because bool(a) evaluates as True when a is not zero.

>>> a = 1
>>> b = 6
>>> if a and b > 2:
...     print('yes')
... else:
...     print('no')
    
yes

Each variable needs to be compared separately.

>>> if a > 2 and b > 2:
...     print('yes')
... else:
...     print('no')
        
no

Another, similar, mistake is made when checking if a variable is one of multiple values. The statement in this example is evaluated as - if (a == 3) or (4) or (6). This produces an unexpected result because bool(4) and bool(6) each evaluate to True

>>> a = 1
>>> if a == 3 or 4 or 6:
...     print('yes')
... else:
...     print('no')
       
yes

Again each comparison must be made separately

>>> if a == 3 or a == 4 or a == 6:
...     print('yes')
... else:
...     print('no')
        
no

Using the in operator is the canonical way to write this.

>>> if a in (3, 4, 6):
...     print('yes')
... else:
...     print('no')
    
no

if condition:
    body
else:
    body

The else statement will execute it's body only if preceding conditional statements all evaluate to False.

if True:
    print "It is true!"
else:
    print "This won't get printed.."

# Output: It is true!

if False:
    print "This won't get printed.."
else:
    print "It is false!"

# Output: It is false!

Python 2 includes a cmp function which allows you to determine if one object is less than, equal to, or greater than another object. This function can be used to pick a choice out of a list based on one of those three options.

Suppose you need to print 'greater than' if x > y, 'less than' if x < y and 'equal' if x == y.

['equal', 'greater than', 'less than', ][cmp(x,y)]

# x,y = 1,1 output: 'equal'
# x,y = 1,2 output: 'less than'
# x,y = 2,1 output: 'greater than'

cmp(x,y) returns the following values

This function is removed on Python 3. You can use the cmp_to_key(func) (opens new window) helper function located in functools (opens new window) in Python 3 to convert old comparison functions to key functions.

if condition:
    body

The if statements checks the condition. If it evaluates to True, it executes the body of the if statement. If it evaluates to False, it skips the body.

if True:
    print "It is true!"
>> It is true!

if False:
    print "This won't get printed.."

The condition can be any valid expression:

if 2 + 2 == 4:
    print "I know math!"
>> I know math!

Python allows you to hack list comprehensions to evaluate conditional expressions.

For instance,

[value_false, value_true][<conditional-test>]

Example:

>> n = 16
>> print [10, 20][n <= 15]
10

Here n<=15 returns False (which equates to 0 in Python). So what Python is evaluating is:

[10, 20][n <= 15]
==> [10, 20][False] 
==> [10, 20][0]     #False==0, True==1 (Check Boolean Equivalencies in Python)
==> 10

The inbuilt __cmp__ method returned 3 possible values: 0, 1, -1, where cmp(x,y) returned 0: if both objecs were the same 1: x > y -1: x < y

This could be used with list comprehensions to return the first(ie. index 0), second(ie. index 1) and last(ie. index -1) element of the list. Giving us a conditional of this type:

[value_equals, value_greater, value_less][<conditional-test>]

Finally, in all the examples above Python evaluates both branches before choosing one. To only evaluate the chosen branch:

[lambda: value_false, lambda: value_true][<test>]()

where adding the () at the end ensures that the lambda functions are only called/evaluated at the end. Thus, we only evaluate the chosen branch.

Example:

count = [lambda:0, lambda:N+1][count==N]()

Syntax

• if else # Ternary Operator

You'll often want to assign something to an object if it is None, indicating it has not been assigned. We'll use aDate.

The simplest way to do this is to use the is None test.

if aDate is None:
    aDate=datetime.date.today()

(Note that it is more Pythonic to say is None instead of == None.)

But this can be optimized slightly by exploiting the notion that not None will evaluate to True in a boolean expression. The following code is equivalent:

if not aDate:
    aDate=datetime.date.today()

But there is a more Pythonic way. The following code is also equivalent:

aDate=aDate or datetime.date.today()

This does a Short Circuit evaluation (opens new window). If aDate is initialized and is not None, then it gets assigned to itself with no net effect. If it is None, then the datetime.date.today() gets assigned to aDate.