Most Important Python Functions [With Examples] | Types of Functions

Only a few years ago, Java was the leading programming language, with a user base of over 7.6 million people.

However, today, Python has surpassed this number and is the preferred choice of 8.2 million developers!

The ease of programming and the time-saving capabilities of Python has made most companies use it for various purposes and python developer salary in India is a proof for that.

Because of the increase in demand for Python developers, people are now looking to learn how to code in Python and the different functions in Python.

In this article, we will be focusing on various Python functions and how to code using these functions.

But first, let’s understand…

What are the Functions in Python?

A series of statements that take inputs and perform specific computations to give output is called a function.

This helps in eliminating the need to write the same code over and over again since you can simply call a function to get output for varying inputs.

What does that tell you?

Python helps control the size of a program and makes it more manageable, thus avoiding repetition.

Python already has a list of built-in functions, including print().

Syntax of a Python Function

Here’s what a general syntax of a Python function looks like:

def function_name(parameter list):

    statements, i.e. the function body

What does this jargon even mean?

• def means the start of the function header.
• Function name is a name given to the function to identify it.
• Parameter list is meant to pass values to a function.
• The colon indicates the end of the function header.
• Statements (one or more) define the body of the function.

Calling a Python Function

It’s quite easy to call a function in Python.

Just use the function name after parentheses.

Example:

ef my_function():
  print(“Hello from upGrad!”)

my_function()

Output:

Hello from upGrad!

In this, when you called the function, you got the statement that you had entered in the print function.

Pretty easy, wasn’t it?

Arguments in Python

All information that is passed into functions is done via arguments.

You define an argument inside the parentheses after the name of the function.

As long as you separate all arguments with a comma, you can create as many as you want.

Here is an example containing a function with one argument.

In this, you ask the user to enter the city name and it is printed with the country name.

Example:

def my_function(cityname):
  print(cityname + “, India”)

my_function(“Delhi”)
my_function(“Mumbai”)
my_function(“Chennai”)

Output:

Delhi, India
Mumbai, India
Chennai, India

Now let’s see what happens when you use two arguments and separate them by a comma.

Example:

def my_function(cityname, countryname):
  print(cityname + “, ” + countryname)

my_function(“Lucknow”, “India”)

Output:

Lucknow,India

Note that if you define two arguments in the function, you must call it with two arguments. Otherwise, it will result in an error:

Traceback (most recent call last):
File “./prog.py”, line 4, in <module>
TypeError: my_function() missing 1 required positional argument: ‘countryname’

Return Values in Python

In order to make a function return a value, use the return statement.

Example:

def my_function(x):
  return 7 + x

print(my_function(3))
print(my_function(8))
print(my_function(10))

Output:

10
15
17

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Arbitrary Arguments in Python

These are most useful when you do not know how many numbers of arguments are to be passed into a function.

In such cases, it is mandatory to use an asterisk (*) right before the name of the parameter.

Example:

def greet(*names):

   # names is a tuple with arguments

   for name in names:

       print(“Hello”,name)

greet(“Tom”,”Ed”,”Harry”)

Output:

Hello Tom
Hello Ed
Hello Harry

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Keyword Arguments in Python

Keyword arguments are made when there is no preferred order.

Example:

def my_function(song3, song1, song2):
  print(“My favorite song is ” + song2)

my_function(song1 = “Bohemian Rhapsody”, song2 = “Supersonic”, song3 = “Imitosis”)

Output:

My favourite song is Supersonic

Default Arguments in Python

These arguments are the ones that assume a default value in the function when there is no provided value.

Example:

def my_function(disease = “COVID-19”):
  print(disease + ” is a communicable disease”)

my_function(“Ebola”)
my_function(“Flu”)
my_function()
my_function(“Measles”)

Output:

Ebola is a communicable disease
Flu is a communicable disease
COVID 19 is a communicable disease
Measles is a communicable disease

Anonymous Functions in Python

The functions that are not declared in a decided manner without the def keyword are called anonymous functions.

To create anonymous functions, use the keyword Lamba.

• There is no restriction on the number of arguments lambda can take. However, it will just return one value.
• Anonymous functions can’t be directly called to be printed.
• Lambda has a different namespace and cannot accept variables that are not in the parameter list.

Syntax of lambda Functions

It is only a single-line statement:

lambda [arg1 [,arg2,…..argn]]:expression

Example:

square = lambda x: x*x

print(square(3))

Output:

9

Recursion in Python

Recursion is one of the most important functions in Python.

A recursion means a defined function can call itself. It helps loop through data over and over again to get a result.

One of the most common errors in recursion is when you write a function that keeps calling itself and do not terminate, thus resulting in the usage of excessive power.

Check out the following program.

Example:

def recursive(k):
  if(k > 0):
    result = k + recursive(k – 1)
    print(result)
  else:
    result = 0
  return result

print(“\n\nRecursion Results”)
recursive(3)

Output:

Recursion Results
1
3
6

In this, recursive(k) is the name of the function that will be calling itself, i.e. recurse.

k is the variable, which is decremented by 1 {(k – 1)} each time it is called back.

The moment the condition k > 0 is not fulfilled, the recursion breaks.

Read more: Python Recursive Function Concept

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Advantages of Recursion

Here are the most important advantages of recursion:

• The code or program looks clean and easy-to-understand.
• With recursion, complex functions can be broken down into easier problems.
• The generation of a sequence is way easier with recursion that it is with nested iteration.

Limitations of Recursion

Here are some of the limitations of recursion:

• It is sometimes difficult to understand the logic behind a recursive function.
• Because the function calls itself many times, a recursive function takes up a lot of memory and time, thus being inefficient.
• It is quite complicated to debug a recursive function.

Read: Top 12 Fascinating Python Applications in Real-World

Fibonacci in Python

As you know, sunflowers, the Da Vinci Code, and the song “Lateralus” by Tool, all are based on one thing – Fibonacci numbers.

Fibonacci numbers are those that follow the following sequence of integer values:

0,1,1,2,3,5,8,13,21,34,55,89,….

This sequence is defined by:

Fn = Fn-1 + Fn-2

Where,

F0 = 0

And

F1 = 1

In Python, the code to obtain the nth number of the Fibonacci sequence is written using recursion:

def Fibonacci(n): 

    if n<0: 

        print(“Incorrect input”) 

    elif n==1: 

        return 0

    elif n==2: 

        return 1

    else: 

        return Fibonacci(n-1)+Fibonacci(n-2) 

print(Fibonacci(13))

Output:

144

This means that the 13th number in the Fibonacci series is 144.

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Conclusion

In this post, you learned about the different types of Python functions and how to use them to obtain desired outputs.

However, it is important to be very careful while using each function as the syntax varies.

Even one colon can make a difference!

Similarly, using recursion can help break various complicated mathematical problems. But, at the same time, they have to be used carefully. Otherwise, it can be difficult to debug your recursive function.

This tutorial should surely help you get better at coding in Python.

If you are curious to learn about data science, check out upGrad’s Data Science Programs which are created for working professionals and offers 10+ case studies & projects, practical hands-on workshops, mentorship with industry experts, 1-on-1 with industry mentors, 400+ hours of learning, and job assistance with top firms.