Reusing the same code is required many times within a same program. Functions help us to do so. We write the things we have to do repeatedly in a function then call it where ever required. We already saw build in functions like len(), divmod().

Defining a function

We use def keyword to define a function. General syntax is like

def functionname(params):

Let us write a function which will take two integers as input and then return the sum.

>>> def sum(a, b):
...     return a + b

In the second line with the return keyword, we are sending back the value of a + b to the caller. You must call it like

>>> res = sum(234234, 34453546464)
>>> res

Remember the palindrome program we wrote in the last chapter. Let us write a function which will check if a given string is palindrome or not, then return True or False.

#!/usr/bin/env python3
def palindrome(s):
    return s == s[::-1]
if __name__ == '__main__':
    s = input("Enter a string: ")
    if palindrome(s):
        print("Yay a palindrome")
        print("Oh no, not a palindrome")

Now run the code :)

Local and global variables

To understand local and global variables we will go through two examples.

#!/usr/bin/env python3
def change(b):
    a = 90
a = 9
print("Before the function call ", a)
print("inside change function", end=' ')
print("After the function call ", a)

The output

$ ./
Before the function call  9
inside change function 90
After the function call  9

First we are assigning 9 to a, then calling change function, inside of that we are assigning 90 to a and printing a. After the function call we are again printing the value of a. When we are writing a = 90 inside the function, it is actually creating a new variable called a, which is only available inside the function and will be destroyed after the function finished. So though the name is same for the variable a but they are different in and out side of the function.

#!/usr/bin/env python3
def change(b):
    global a
    a = 90
a = 9
print("Before the function call ", a)
print("inside change function", end=' ')
print("After the function call ", a)

Here by using global keyword we are telling that a is globally defined, so when we are changing a’s value inside the function it is actually changing for the a outside of the function also.

Default argument value

In a function variables may have default argument values, that means if we don’t give any value for that particular variable it will assigned automatically.

>>> def test(a , b=-99):
...     if a > b:
...         return True
...     else:
...         return False

In the above example we have written b = -99 in the function parameter list. That means of no value for b is given then b’s value is -99. This is a very simple example of default arguments. You can test the code by

>>> test(12, 23)
>>> test(12)



Remember that you can not have an argument without default argument if you already have one argument with default values before it. Like f(a, b=90, c) is illegal as b is having a default value but after that c is not having any default value.

Also remember that default value is evaluated only once, so if you have any mutable object like list it will make a difference. See the next example

>>> def f(a, data=[]):
...     data.append(a)
...     return data
>>> print f(1)
>>> print f(2)
[1, 2]
>>> print f(3)
[1, 2, 3]

To avoid this you can write more idiomatic Python, like the following

>>> def f(a, data=None):
...     if data is None:
...         data = []
...     data.append(a)
...     return data
>>> print f(1)
>>> print f(2)


To understand more read this link.

Keyword arguments

>>> def func(a, b=5, c=10):
...     print('a is', a, 'and b is', b, 'and c is', c)
>>> func(12, 24)
a is 12 and b is 24 and c is 10
>>> func(12, c = 24)
a is 12 and b is 5 and c is 24
>>> func(b=12, c = 24, a = -1)
a is -1 and b is 12 and c is 24

In the above example you can see we are calling the function with variable names, like func(12, c = 24), by that we are assigning 24 to c and b is getting its default value. Also remember that you can not have without keyword based argument after a keyword based argument. like

>>> def func(a, b=13, v):
...     print(a, b, v)
File "<stdin>", line 1
SyntaxError: non-default argument follows default argument

Keyword only argument

We can also mark the arguments of function as keyword only. That way while calling the function, the user will be forced to use correct keyword for each parameter.

>>> def hello(*, name='User'):
...     print("Hello %s" % name)
>>> hello('Kushal')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: hello() takes 0 positional arguments but 1 was given
>>> hello(name='Kushal')
Hello Kushal


To learn more please read PEP-3102.


In Python we use docstrings to explain how to use the code, it will be useful in interactive mode and to create auto-documentation. Below we see an example of the docstring for a function called longest_side.

#!/usr/bin/env python3
import math

def longest_side(a, b):
    Function to find the length of the longest side of a right triangle.

    :arg a: Side a of the triangle
    :arg b: Side b of the triangle

    :return: Length of the longest side c as float
    return math.sqrt(a*a + b*b)

if __name__ == '__main__':
    print(longest_side(4, 5))

We will learn more on docstrings in reStructuredText chapter.

Higher-order function

Higher-order function or a functor is a function which does at least one of the following step inside:

  • Takes one or more functions as argument.
  • Returns another function as output.

In Python any function can act as higher order function.

>>> def high(func, value):
...     return func(value)
>>> lst = high(dir, int)
>>> print(lst[-3:])
['imag', 'numerator', 'real']
>>> print(lst)


To know more read this link.

map function

map is a very useful higher order function in Python. It takes one function and an iterator as input and then applies the function on each value of the iterator and returns a list of results.


>>> lst = [1, 2, 3, 4, 5]
>>> def square(num):
...     "Returns the square of a given number."
...     return num * num
>>> print(map(square, lst))
[1, 4, 9, 16, 25]