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Python Functions - GeeksforGeeks

Python Functions is a block of statements that does a specific task. The idea is to put some commonly or repeatedly done task together and make a function so that instead of writing the same code again and again for different inputs, we can do the function calls to reuse code contained in it over and over again.

Benefits of Using Functions Python Function Declaration

The syntax to declare a function is:

Syntax of Python Function Declaration Types of Functions in Python

Below are the different types of functions in Python:

Creating a Function in Python

We can define a function in Python, using the def keyword. We can add any type of functionalities and properties to it as we require. By the following example, we can understand how to write a function in Python. In this way we can create Python function definition by using def keyword.

Python
def fun():
    print("Welcome to GFG")
Calling a Function in Python

After creating a function in Python we can call it by using the name of the functions Python followed by parenthesis containing parameters of that particular function. Below is the example for calling def function Python.

Python
def fun():
    print("Welcome to GFG")

# Driver code to call a function
fun()
Python Function Arguments

Arguments are the values passed inside the parenthesis of the function. A function can have any number of arguments separated by a comma.

Syntax for functions with arguments:

def function_name(parameter: data_type) -> return_type:
"""Docstring"""
# body of the function
return expression

data_type and return_type are optional in function declaration, meaning the same function can also be written as:

def function_name(parameter) :
"""Docstring"""
# body of the function
return expression

Let's understand this with an example, we will create a simple function in Python to check whether the number passed as an argument to the function is even or odd.

Python
def evenOdd(x: int) ->str:
    if (x % 2 == 0):
        return "Even"
    else:
        return "Odd"

print(evenOdd(16))
print(evenOdd(7))

The above function can also be declared without type_hints, like this:

Python
def evenOdd(x):
    if (x % 2 == 0):
        return "Even"
    else:
        return "Odd"

print(evenOdd(16))
print(evenOdd(7))
Types of Python Function Arguments

Python supports various types of arguments that can be passed at the time of the function call. In Python, we have the following function argument types in Python:

Let's discuss each type in detail. 

Default Arguments

A default argument is a parameter that assumes a default value if a value is not provided in the function call for that argument. The following example illustrates Default arguments to write functions in Python.

Python
def myFun(x, y=50):
    print("x: ", x)
    print("y: ", y)


myFun(10)

Like C++ default arguments, any number of arguments in a function can have a default value. But once we have a default argument, all the arguments to its right must also have default values.

Keyword Arguments

The idea is to allow the caller to specify the argument name with values so that the caller does not need to remember the order of parameters.

Python
def student(fname, lname):
    print(fname, lname)

student(fname='Geeks', lname='Practice')
student(lname='Practice', fname='Geeks')

Output
Geeks Practice
Geeks Practice
Positional Arguments

We used the Position argument during the function call so that the first argument (or value) is assigned to name and the second argument (or value) is assigned to age. By changing the position, or if you forget the order of the positions, the values can be used in the wrong places, as shown in the Case-2 example below, where 27 is assigned to the name and Suraj is assigned to the age.

Python
def nameAge(name, age):
    print("Hi, I am", name)
    print("My age is ", age)


print("Case-1:")
nameAge("Suraj", 27)

print("\nCase-2:")
nameAge(27, "Suraj")

Output
Case-1:
Hi, I am Suraj
My age is  27

Case-2:
Hi, I am 27
My age is  Suraj
Arbitrary Keyword  Arguments

In Python Arbitrary Keyword Arguments, *args, and **kwargs can pass a variable number of arguments to a function using special symbols. There are two special symbols:

Example 1: Variable length non-keywords argument

Python
def myFun(*argv):
    for arg in argv:
        print(arg)


myFun('Hello', 'Welcome', 'to', 'GeeksforGeeks')

Output
Hello
Welcome
to
GeeksforGeeks

Example 2: Variable length keyword arguments

Python
def myFun(**kwargs):
    for key, value in kwargs.items():
        print("%s == %s" % (key, value))


myFun(first='Geeks', mid='for', last='Geeks')

Output
first == Geeks
mid == for
last == Geeks
Docstring

The first string after the function is called the Document string or Docstring in short. This is used to describe the functionality of the function. The use of docstring in functions is optional but it is considered a good practice.

The below syntax can be used to print out the docstring of a function.

Syntax: print(function_name.__doc__)

Example: Adding Docstring to the function

Python
def evenOdd(x):
    """Function to check if the number is even or odd"""
    
    if (x % 2 == 0):
        print("even")
    else:
        print("odd")


print(evenOdd.__doc__)

Output
Function to check if the number is even or odd
Python Function within Functions

A function that is defined inside another function is known as the inner function or nested function. Nested functions can access variables of the enclosing scope. Inner functions are used so that they can be protected from everything happening outside the function.

Python
def f1():
    s = 'I love GeeksforGeeks'
    
    def f2():
        print(s)
        
    f2()

f1()

Output
I love GeeksforGeeks
Anonymous Functions in Python

In Python, an anonymous function means that a function is without a name. As we already know the def keyword is used to define the normal functions and the lambda keyword is used to create anonymous functions.

Python
def cube(x): return x*x*x   # without lambda

cube_l = lambda x : x*x*x  # with lambda

print(cube(7))
print(cube_l(7))
Recursive Functions in Python

Recursion in Python refers to when a function calls itself. There are many instances when you have to build a recursive function to solve Mathematical and Recursive Problems.

Using a recursive function should be done with caution, as a recursive function can become like a non-terminating loop. It is better to check your exit statement while creating a recursive function.

Python
def factorial(n):
    if n == 0:  
        return 1
    else:
        return n * factorial(n - 1) 
      
print(factorial(4))

Here we have created a recursive function to calculate the factorial of the number. It calls itself until a base case (n==0) is met.

Return Statement in Python Function

The function return statement is used to exit from a function and go back to the function caller and return the specified value or data item to the caller. The syntax for the return statement is:

return [expression_list]

The return statement can consist of a variable, an expression, or a constant which is returned at the end of the function execution. If none of the above is present with the return statement a None object is returned.

Example: Python Function Return Statement

Python
def square_value(num):
    """This function returns the square
    value of the entered number"""
    return num**2

print(square_value(2))
print(square_value(-4))
Pass by Reference and Pass by Value

One important thing to note is, in Python every variable name is a reference. When we pass a variable to a function Python, a new reference to the object is created. Parameter passing in Python is the same as reference passing in Java.

Python
# Here x is a new reference to same list lst
def myFun(x):
    x[0] = 20

# Driver Code (Note that lst is modified
# after function call.
lst = [10, 11, 12, 13, 14, 15]
myFun(lst)
print(lst)

Output
[20, 11, 12, 13, 14, 15]

When we pass a reference and change the received reference to something else, the connection between the passed and received parameters is broken. For example, consider the below program as follows:

Python
def myFun(x):
    x = [20, 30, 40]


lst = [10, 11, 12, 13, 14, 15]
myFun(lst)
print(lst)

Output
[10, 11, 12, 13, 14, 15]

Another example demonstrates that the reference link is broken if we assign a new value (inside the function). 

Python
def myFun(x):
    x = 20

x = 10
myFun(x)
print(x)

Exercise: Try to guess the output of the following code. 

Python
def swap(x, y):
    temp = x
    x = y
    y = temp

x = 2
y = 3
swap(x, y)
print(x)
print(y)
Quiz: Recommended Problems: Quick Links
How Functions Work in Python

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