hackerrank python test with code examples

HackerRank is an online platform that allows software developers to sharpen their programming skills. It provides a large collection of coding challenges across different domains like algorithms, data science, databases, and many more. The HackerRank Python test provides an opportunity for programmers to test their coding knowledge of the Python programming language. This article will explore what the HackerRank Python test entails, examples of commonly asked questions, and tips on how to prepare for the test.

What is the HackerRank Python Test?

The HackerRank Python test is an online coding challenge that tests your knowledge of the Python programming language. The test is timed and typically takes one hour to complete. During the test, you will be asked to solve algorithmic problems in Python. You will also be expected to understand fundamental programming concepts such as loops, conditionals, and recursion. The test is divided into different sections that test your knowledge of different aspects of Python programming.

Examples of Commonly Asked Questions

The questions in the HackerRank Python test are algorithmic problems that require you to write efficient and optimized code in Python. Here are some examples of the type of questions you can expect to encounter during the test:

  1. Write a Python function that takes in an array of integers and returns the sum of the odd numbers in the array.
def sum_odd_numbers(arr):
     return sum(num for num in arr if num%2!=0)
  1. Given a list of integers, write a Python function to find the second-highest number in the list.
def second_highest_num(arr):
    return sorted(set(arr))[-2]
  1. Write a Python function that checks if a given string is a palindrome.
def is_palindrome(s):
    return s == s[::-1]
  1. Write a Python function that takes in a string and checks if it contains only unique characters.
def has_unique_chars(s):
    return len(set(s)) == len(s)

Tips on How to Prepare for the HackerRank Python Test

Preparing for the HackerRank Python test requires thorough knowledge of the Python programming language and problem-solving skills. Here are some tips to help you prepare for the test:

  1. Study the Python language: Make sure you have a solid understanding of Python programming concepts like loops, conditionals, functions, and classes.

  2. Practice coding exercises: Use websites like HackerRank to practice coding problems in Python. This will help you develop problem-solving skills and prepare you for the types of questions you will encounter during the test.

  3. Learn common algorithms and data structures: You should be familiar with commonly used algorithms like sorting and searching, as well as data structures like arrays and linked lists.

  4. Familiarize yourself with the test format: Take some time to understand how the HackerRank Python test is structured and the types of questions that may be asked. This will help you manage your time effectively during the test.

  5. Manage your time: The HackerRank Python test is timed, so you must be able to manage your time effectively. Make sure you allocate enough time to solve each question and move on if you get stuck.


The HackerRank Python test is a great way to test your coding skills in Python. It provides an opportunity for programmers to hone their problem-solving skills and improve their understanding of the Python programming language. As with any test, preparation is key to success. By studying and practicing Python programming concepts and solving coding challenges, you can improve your chances of performing well on the HackerRank Python test.

let me elaborate more on the topics mentioned in the article.

  1. Python Programming Language

Python is a high-level interpreted programming language that is known for its simplicity and ease of use. It was first created by Guido van Rossum in the late 1980s and has since become one of the most popular programming languages in the world. Python is used in a wide range of applications, including web development, data science, machine learning, and more.

Python syntax is easy to read and write, making it ideal for beginners learning to code. Python code is designed to be readable and concise, with minimal use of symbols and keywords. Python also has a large standard library that provides a wide range of modules and functions for various tasks.

  1. Algorithmic Problems

Algorithmic problems involve the use of algorithms to solve problems. An algorithm is a set of instructions that defines a sequence of steps to be followed to solve a specific problem. Algorithmic problems are common in programming tests like the HackerRank Python test and require a good understanding of programming concepts and problem-solving skills.

To solve algorithmic problems, you must first understand the problem statement and identify the inputs and outputs. You then need to develop an algorithm to solve the problem and write code to implement the algorithm. The code should optimize performance and meet the constraints of the problem statement.

  1. Data Structures

Data structures are essential objects used in computer science to store and manipulate data. Some common data structures include arrays, linked lists, stacks, queues, trees, and graphs. Data structures are used in algorithmic problems to organize, sort, and search data.

To solve an algorithmic problem that involves data structures, you must first identify the appropriate data structure to use. You then need to develop an algorithm to manipulate the data structure to solve the problem. The code should be optimized for performance and meet the constraints of the problem statement.

  1. Problem-Solving Skills

Problem-solving skills are essential for software developers. A good software developer must be able to analyze a problem, develop solutions, and implement them. Problem-solving skills require critical thinking, analytical skills, logical reasoning, and creativity.

To develop problem-solving skills, you need to practice solving problems regularly. You can use websites like HackerRank or Leetcode to practice solving algorithmic problems. It is also important to learn from your mistakes and seek feedback from others to improve your problem-solving skills. Developing good problem-solving skills requires patience, persistence, and dedication.

In conclusion, mastering the Python programming language, algorithmic problem-solving, data structures, and problem-solving skills are essential for software developers. By practicing regularly, seeking feedback, and continuously learning, you can improve your skills and perform well in exams and job interviews.

Popular questions

Sure, here are five questions with answers:

Question 1:

Write a Python function that takes in a list of words and returns the count of words that start with the letter 'a'.


def count_a_words(words):
    count = 0
    for word in words:
        if word.startswith('a'):
            count += 1
    return count

Question 2:

Write a Python function that takes in a string and returns a new string with all vowels removed.


def remove_vowels(s):
    vowels = "aeiouAEIOU"
    return "".join([char for char in s if char not in vowels])

Question 3:

Write a Python function that takes in a list of integers and returns the second smallest integer in the list.


def second_smallest(lst):
    smallest = min(lst)
    second_smallest = min(lst)
    return second_smallest

Question 4:

Write a Python function to check if a string is a valid IPv4 address.


def is_valid_ipv4_address(address):
        octets = address.split('.')
        if len(octets) != 4:
            return False
        for octet in octets:
            if not octet.isdigit() or not 0 <= int(octet) <= 255:
                return False
        return True
        return False

Question 5:

Write a Python function that takes in a list of integers and returns the sum of all the numbers in the list.


def sum_numbers(numbers):
    return sum(numbers)



Throughout my career, I have held positions ranging from Associate Software Engineer to Principal Engineer and have excelled in high-pressure environments. My passion and enthusiasm for my work drive me to get things done efficiently and effectively. I have a balanced mindset towards software development and testing, with a focus on design and underlying technologies. My experience in software development spans all aspects, including requirements gathering, design, coding, testing, and infrastructure. I specialize in developing distributed systems, web services, high-volume web applications, and ensuring scalability and availability using Amazon Web Services (EC2, ELBs, autoscaling, SimpleDB, SNS, SQS). Currently, I am focused on honing my skills in algorithms, data structures, and fast prototyping to develop and implement proof of concepts. Additionally, I possess good knowledge of analytics and have experience in implementing SiteCatalyst. As an open-source contributor, I am dedicated to contributing to the community and staying up-to-date with the latest technologies and industry trends.
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