Top 70 Python Interview Questions and Answers

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Are you preparing for a Python interview and wondering what questions to expect? Python is one of the most in-demand programming languages today, used by over 8.2 million developers worldwide. Statistics also show that Python-related jobs are on the rise. Right now, Hirist has more than a thousand job listings for Python roles! Whether you’re aiming for a junior or senior role – it’s essential to be ready for common interview questions. This blog covers the top 70 Python interview questions and answers to help you stand out. From basic syntax to more advanced topics, we’ve got you covered with clear explanations. 

So, let’s begin!

Python Interview Questions for Freshers

Here are some commonly asked Python basic interview questions and their answers. 

1. What is Python?

Python is an interpreted, high-level, general-purpose programming language. It emphasizes code readability and has a simple syntax, making it great for both beginners and experts. Python supports object-oriented, procedural, and functional programming.

2. What are Python data types?

The main data types in Python are:

• int (integer)
• float (floating-point numbers)
• str (string)
• bool (boolean)
• list, tuple, set, and dict (for collections)

3. What is a Python function?

This is one of the most common Python language interview questions. 

A function in Python is a block of reusable code designed to perform a specific task. It’s defined using the def keyword and can take input parameters and return output.

4. What is a lambda function?

A lambda function is an anonymous, small function in Python that can have any number of arguments but only one expression. It’s written as lambda arguments: expression and is often used for short, simple tasks.

5. Explain what Flask is and its uses. 

You may also come across Python Flask interview questions like this one. 

Flask is a lightweight web framework for Python. It’s used to create web applications quickly with fewer dependencies, making it flexible and easy to scale. Flask is often preferred for smaller applications or when developers want more control over components.

6. What is Selenium and how is it used in Python?

It is one of the most important Python Selenium interview questions. 

Selenium is an open-source tool used for automating web browsers. In Python, Selenium is used for writing test scripts that can interact with web elements (like clicking buttons or filling forms) to test websites. It helps automate repetitive web-based tasks efficiently.

Also Read - Top 25+ Java Questions for Selenium Interview

7. What is Python used for in automation?

This is how you should answer Python automation interview questions like this one. 

Python is commonly used in automation to simplify repetitive tasks such as web scraping, file handling, and task scheduling. Libraries like Selenium, PyAutoGUI, and subprocess make Python an ideal choice for automating workflows.

8. What is PEP 8?

PEP 8 is Python’s style guide for writing clean, readable code. It includes best practices for formatting code, such as indentation, line length, naming conventions, and more, ensuring that Python code is easy to read and maintain.

Python Interview Questions for Experienced

Here are some important Python interview questions for experienced developers, along with their answers. 

Python Interview Questions for 2 Years Experienced Candidates

9. What is Python scripting, and how is it different from programming in Python?

This is one of the most common Python scripting interview questions.

Python scripting refers to writing small, executable programs (or scripts) for automating tasks. These scripts are often written for system administration, web scraping, or automating repetitive tasks. In contrast, Python programming usually involves building larger, more complex applications, where the code is organized into modules, classes, and functions.

10. What is the difference between a list and a tuple in Python?

The main difference is that lists are mutable, meaning their elements can be changed, while tuples are immutable, meaning that once created, they can’t be altered. Lists are defined using square brackets [], and tuples with parentheses ().

11. How would you reverse a string in Python without using built-in functions?

You may also come across Python logic interview questions like this one. 

You can reverse a string using slicing or a loop. Here’s how:

def reverse_string(s):

    reversed_str = “”

    for char in s:

        reversed_str = char + reversed_str

    return reversed_str

print(reverse_string(“hello”))  # Output: “olleh”

Python Interview Questions for 3 Years Experienced Candidates

12. Explain the concept of asynchronous programming in Python and how it is implemented using asyncio.

Asynchronous programming in Python allows you to write programs that can perform multiple operations concurrently without waiting for I/O-bound tasks to complete. Python’s asyncio module is used to implement this, allowing you to define coroutines using async def and control execution using await. It helps improve the performance of I/O-bound programs, such as web servers or API calls.

13. What is FastAPI, and why would you use it in Python development?

You can also expect FastAPI interview questions like this one.  

FastAPI is a modern, fast (high-performance) web framework for building APIs with Python. It is designed to be easy to use while enabling asynchronous programming, which makes it significantly faster than traditional frameworks like Flask. FastAPI automatically generates documentation, validates data, and allows for dependency injection, making it ideal for creating scalable and efficient APIs.

Python Interview Questions for 4 Years Experienced Candidates

14. What is Python’s garbage collection, and how does it work?

This is one of the most important python interview questions JavaTpoint. 

Python uses automatic garbage collection to free memory by removing objects that are no longer in use. It uses reference counting to track how many references exist for an object, and when the reference count drops to zero, the object is destroyed. Additionally, Python uses a cyclic garbage collector to detect and handle circular references that reference counting alone can’t resolve.

15. What is a dictionary in Python, and how would you update a dictionary with another dictionary?

This is one of the most common Python dictionary interview questions.

A dictionary in Python is a collection of key-value pairs. You can update a dictionary using the update() method, which merges two dictionaries. 

Example:

dict1 = {‘a’: 1, ‘b’: 2}

dict2 = {‘b’: 3, ‘c’: 4}

dict1.update(dict2)

print(dict1)  # Output: {‘a’: 1, ‘b’: 3, ‘c’: 4}

Python Interview Questions for 5 Years Experienced Candidates

16. Explain what Matplotlib is and how you would create a simple plot using it.

You may also come across Python Matplotlib interview questions like this one. 

Matplotlib is a popular data visualization library in Python that enables you to create static, interactive, and animated visualizations. Here’s a simple plot example:

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]

y = [2, 4, 6, 8, 10]

plt.plot(x, y)

plt.title(“Simple Line Plot”)

plt.xlabel(“X-axis”)

plt.ylabel(“Y-axis”)

plt.show()

17. What is the Global Interpreter Lock (GIL) in Python, and why is it important?

The GIL is a mutex in Python that protects access to Python objects, preventing multiple native threads from executing Python bytecodes simultaneously. This lock ensures that only one thread runs in the interpreter at a time, which simplifies memory management but can be a performance bottleneck for CPU-bound tasks in multi-threaded programs.

Python Interview Questions for 10 Years Experienced Candidates

18. How do you approach solving a complex algorithmic problem in Python?

This is one of the most important Python logical questions you may face during an interview.

Start by fully understanding the problem and breaking it down into smaller components. Use a combination of algorithmic techniques like dynamic programming, recursion, or greedy algorithms depending on the problem. Always aim to find the most efficient solution by analyzing the time and space complexity (using Big O notation). Test your solution with both edge and large input cases to ensure robustness.

19. Explain what memory management techniques Python uses.

Python uses dynamic memory allocation, managed by the Python memory manager, which allocates heap space for objects. Python also uses reference counting and a cyclic garbage collector to manage memory and clean up unused objects. Additionally, Python optimizes memory for smaller objects using pools and arenas.

Advanced Python Questions

Here are some advanced interview questions in Python programming and their answers. 

20. How would you create a Python function that mimics the behaviour of the range() function but works with floating-point numbers?

You may come across Python tricky interview questions like this one. 

Python’s built-in range() works only with integers. To create a similar function for floating-point numbers:

def float_range(start, stop, step):

    while start < stop:

        yield round(start, 10)  # rounding to avoid floating-point precision errors

        start += step

for num in float_range(0.5, 5.5, 0.5):

    print(num)

This function generates floating-point numbers from start to stop, incrementing by step.

21. Explain string interning in Python and its impact on memory usage.

This is one of the most important Python String interview questions.

String interning is an optimization technique in Python where identical immutable strings are stored only once in memory. This reduces memory usage and improves performance when comparing strings. Python automatically interns certain strings, like small strings or identifiers. 

22. You have to write a Python program to find the second-highest number in a list. Can you implement it?

You can also expect Python machine test questions similar to this one.

def second_highest(numbers):

    first, second = float(‘-inf’), float(‘-inf’)

    for num in numbers:

        if num > first:

            second = first

            first = num

        elif first > num > second:

            second = num

    return second

numbers = [12, 35, 1, 10, 34, 1]

print(second_highest(numbers))  # Output: 34

Python Interview Questions for Data Analyst

Here are some common Python programming interview questions and answers for data analysts. 

23. How would you handle missing data in a dataset using Python?

In Python, missing data can be handled using the pandas library. Common methods include:

• Dropping rows with missing values using dropna()
• Filling missing values using fillna(), where you can replace missing values with the mean, median, mode, or a constant value.

24. Explain the difference between apply(), map(), and applymap() functions in pandas.

• map(): Used to apply a function element-wise to a Series.
• apply(): Used to apply a function along either axis (rows or columns) of a DataFrame.
• applymap(): Used to apply a function element-wise to all elements of a DataFrame.

Python Interview Questions for Data Science

These are some important Python programming questions interview and their answers for data science. 

25. How do you perform web scraping in Python using BeautifulSoup?

This is one of the most important Python web scraping interview questions for data science. 

Web scraping can be performed using the BeautifulSoup library, which helps parse HTML and extract data.

import requests

from bs4 import BeautifulSoup

url = ‘https://example.com’

response = requests.get(url)

soup = BeautifulSoup(response.text, ‘html.parser’)

# Extracting all paragraph texts

paragraphs = soup.find_all(‘p’)

for para in paragraphs:

    print(para.get_text())

26. How do you calculate the correlation between two variables in Python?

You can calculate the correlation between two variables using the corr() function from the pandas library, which computes the Pearson correlation coefficient by default.

import pandas as pd

data = {‘A’: [1, 2, 3, 4], ‘B’: [10, 20, 30, 40]}

df = pd.DataFrame(data)

correlation = df[‘A’].corr(df[‘B’])

print(correlation)

Python Interview Questions for Data Engineer

Here are some important Python interview questions and answers for data engineers. 

27. What are Python functions, and how would you create a function that returns multiple values?

You may also come across Python function interview questions for data engineers like this one. 

A Python function is a reusable block of code defined using the def keyword. To return multiple values from a function, you can return them as a tuple, list, or dictionary. 

Example:

def get_coordinates():

    x = 5

    y = 10

    return x, y

x_coord, y_coord = get_coordinates()

print(x_coord, y_coord)

28. How does Python handle memory management, and why is it important for data engineers?

Python uses automatic memory management, including garbage collection, to free up memory by removing objects that are no longer needed. For data engineers handling large datasets, understanding memory management is important to optimize performance and prevent memory leaks, especially when dealing with large-scale data pipelines.

NumPy and Pandas Interview Questions

These are some common Pandas and NumPy interview questions and their answers. 

NumPy Interview Questions

29. What is NumPy, and why is it used in Python?

NumPy (Numerical Python) is a Python library used for numerical computing. It provides support for arrays and matrices, along with a large collection of mathematical functions to operate on these arrays. It’s widely used for data analysis, scientific computing, and performing mathematical operations.

30. How does broadcasting work in NumPy?

Broadcasting in NumPy allows arrays of different shapes to be used together in arithmetic operations. NumPy automatically expands the smaller array along its dimensions to match the shape of the larger array. This avoids the need for manually reshaping arrays, making operations more efficient. For example:

Pandas Python Interview Questions

31. How do you merge two DataFrames in Pandas?

You can merge two DataFrames using the merge() function in Pandas, similar to SQL joins. You can specify the type of join (e.g., inner, outer, left, right) and the key(s) on which the DataFrames will be merged. 

Example:

import pandas as pd

df1 = pd.DataFrame({‘ID’: [1, 2, 3], ‘Name’: [‘Alice’, ‘Bob’, ‘Charlie’]})

df2 = pd.DataFrame({‘ID’: [1, 2, 4], ‘Score’: [85, 92, 88]})

result = pd.merge(df1, df2, on=’ID’, how=’inner’)

print(result)  # Output: merged DataFrame with common ‘ID’

32. What are the differences between loc[] and iloc[] in Pandas?

loc[] is label-based, meaning it selects rows and columns by labels or boolean conditions. iloc[], on the other hand, is integer-based and selects rows and columns by index positions. 

Example:

df = pd.DataFrame({‘A’: [10, 20, 30], ‘B’: [40, 50, 60]})

print(df.loc[0, ‘A’])  # Output: 10 (by label)

print(df.iloc[0, 0])   # Output: 10 (by index position)

Python DSA Interview Questions

Here are some important Python DSA questions and their answers. 

33. What are the main differences between a stack and a queue?

This is one of the most common Python data structures interview questions.

A stack follows the Last In, First Out (LIFO) principle, where the last added element is the first removed. A queue follows the First In, First Out (FIFO) principle, where the first added element is the first removed.

34. What is binary search, and how does it work?

Binary search is an efficient algorithm for finding an item in a sorted list. It repeatedly divides the search space in half, comparing the target value to the middle element, and continues until the item is found or the search space is empty. Its time complexity is O(log n).

Also Read –

Python REST API Interview Questions

Here are some common Python API interview questions and their answers. 

35. What is a RESTful API, and what are its key principles?

A RESTful API (Representational State Transfer) is an architectural style for designing networked applications. Its key principles include statelessness (each request from a client contains all the information needed), client-server separation (the client and server operate independently), and the use of standard HTTP methods (GET, POST, PUT, DELETE) to perform operations.

36. How do you handle errors in a Python REST API?

Error handling in a Python REST API can be managed using HTTP status codes to indicate the type of error (e.g., 404 for Not Found, 500 for Internal Server Error). You can also return meaningful error messages in the response body, allowing clients to understand what went wrong.

Python Scenario Based Interview Questions

These are some important scenario-based questions and answers on Python programming.

37. You need to process a large CSV file and filter out specific rows based on certain conditions. How would you approach this task?

“I would use the pandas library to read the CSV file efficiently. I would load the data into a DataFrame, apply filtering conditions using boolean indexing, and then export the filtered DataFrame back to a new CSV file. This approach allows for handling large datasets effectively and easily.”

38. You are tasked with writing a function that checks if a given string is a palindrome. How would you implement this?

This is one of the most common Python scenario based coding questions. 

“I would define a function that compares the string to its reverse. If they are the same, the string is a palindrome. This can be done using slicing in Python.”

Here’s a simple implementation for the palindrome check:

def is_palindrome(s):

    # Remove spaces and convert to lowercase

    cleaned_s = ”.join(s.split()).lower()

    return cleaned_s == cleaned_s[::-1]

# Example usage

print(is_palindrome(“A man a plan a canal Panama”))  # Output: True

print(is_palindrome(“Hello”))  # Output: False

Python Coding Interview Questions

Here are some important Python coding questions and answers.

39. How do you reverse a string in Python?

You can reverse a string using slicing. 

For example:

def reverse_string(s):

    return s[::-1]

40. How would you find the maximum value in a list without using built-in functions?

This is how you should answer such python coding questions. 

You can iterate through the list and keep track of the maximum value found:

def find_max(lst):

    max_value = lst[0]

    for num in lst:

        if num > max_value:

            max_value = num

    return max_value

41. Write a function to check if two strings are anagrams of each other.

You can check if two strings have the same character counts:

def are_anagrams(str1, str2):

    return sorted(str1) == sorted(str2)

42. Write a function to calculate the factorial of a number.

It is one of the most commonly asked Python programs for interview.

The factorial can be calculated using recursion or iteration. Here’s a recursive approach:

def factorial(n):

    if n == 0 or n == 1:

        return 1

    return n * factorial(n – 1)

43. What will be the output of the following code?

x = [1, 2, 3]

y = x

y.append(4)

print(x)

This is one of the most common Python output based questions.

The output will be [1, 2, 3, 4]. Since y is a reference to the same list as x, any changes made to y will also affect x.

Infosys Python Developer Interview Questions

Here are some commonly asked Infosys python interview questions and their answers. 

44. Infosys emphasizes continuous learning. Can you describe a recent Python project you worked on and what new skills you developed during it?

“Recently, I worked on a web application that involved data visualization using Python with libraries like Matplotlib and Seaborn. I developed skills in data manipulation with Pandas and learned how to deploy the application using Flask. This project also helped me improve my understanding of RESTful APIs and how to integrate them for data retrieval.”

45. How can you implement machine learning in Python using libraries like scikit-learn?

This is one of the most commonly asked Python ML interview questions.

Machine learning in Python can be implemented using libraries like scikit-learn by following these steps: import the necessary modules, prepare your data (features and labels), split the data into training and test sets, choose a model (e.g., decision tree, linear regression), train the model using the training data, and evaluate its performance using the test data.

TCS Python Interview Questions

Here are some important Python questions you may come across during your interview at TCS. 

46. Why are you interested in this Python role at TCS?

“I am excited about this Python role at TCS because it offers the opportunity to work on innovative projects that leverage my skills in data analysis and machine learning. TCS’s focus on teamwork and continuous learning aligns perfectly with my career goals, and I believe I can contribute effectively while growing professionally.”

47. TCS values teamwork and collaboration. Can you share an experience where you collaborated with a team on a Python project and what role you played?

“In my last internship, I was part of a team developing a machine learning model to predict customer churn. My role involved preprocessing data using Pandas and collaborating closely with team members to share insights. We held regular meetings to discuss our progress, and I helped integrate the model into a web application using Flask. This experience taught me the importance of clear communication and leveraging team strengths.”

Accenture Python Interview Questions

These are some Accenture Python mock interview questions and their answers.

48. Accenture focuses on innovation. Can you discuss a time when you applied a creative solution in a Python project?

“During a project to automate data entry processes for a client, I noticed that traditional methods were time-consuming. I proposed using Python with Selenium to create a web scraper that could gather data from various online sources automatically. This not only saved hours of manual work but also improved data accuracy. The client was impressed with the solution, and it led to a more streamlined workflow.”

49. How do you approach learning new technologies or tools in Python?

“I approach learning new technologies by starting with online courses and tutorials to build a foundational understanding. Then, I apply what I learn by working on small projects or contributing to open-source. Accenture’s emphasis on innovation motivates me to stay updated with the latest tools, ensuring I can bring fresh ideas to my work.”

Python Google Interview Questions

Here are some common Python full stack developer interview questions asked at Google. 

50. How do you optimize a web application for performance?

“To optimize a web application, I focus on minimizing HTTP requests, compressing assets, and implementing caching strategies. I also use tools like Google PageSpeed Insights to identify bottlenecks and ensure efficient database queries to enhance overall performance.”

51. Can you explain how you would implement authentication in a Flask application?

“For authentication in a Flask application, I would use Flask-Login for session management. I would implement user registration and login functionalities, hash passwords with a library like bcrypt, and protect routes with decorators to ensure only authenticated users can access specific resources.”

Capgemini Python Interview Questions

Here are some common Python interview topics and questions you may come across at Capgemini. 

52. What is the purpose of using virtual environments in Python?

Virtual environments allow developers to create isolated spaces for Python projects, ensuring that each project can have its own dependencies and versions without conflicts. This helps maintain clean and manageable project setups.

53. Why are you interested in a Python role at Capgemini?

“I am drawn to a Python role at Capgemini because of the company’s commitment to innovation and technology-driven solutions. I admire Capgemini’s collaborative culture and am excited about the opportunity to work on diverse projects that make a positive impact.”

Cognizant Python Interview Questions

Here are some important Python theoretical questions you may be asked at Cognizant during an interview. 

54. What are Python decorators and how do they work?

Python decorators are functions that modify the behavior of another function. They are defined using the @decorator_name syntax and are commonly used for logging, access control, or modifying input and output of functions, allowing for cleaner and more reusable code.

55. Cognizant values agile methodologies. How do you incorporate agile practices in your Python projects?

“In my Python projects, I incorporate agile practices by breaking tasks into smaller user stories and using iterative development cycles. I prioritize regular stand-up meetings for team communication, utilize tools like JIRA for tracking progress, and adapt quickly to feedback, ensuring continuous improvement throughout the project lifecycle.”

Also Read - Top 15 Agile Methodology Interview Questions and Answers

HCL Python Interview Questions

These are some common Python and SQL interview questions you may expect at HCL. 

56. What is the purpose of using list comprehensions in Python?

List comprehensions provide a concise way to create lists. They allow for the generation of new lists by applying an expression to each item in an existing iterable, resulting in cleaner and more readable code.

57. HCL emphasizes data-driven decision-making. How would you use Python to analyze data from a SQL database?

“To analyze data from a SQL database, I would use libraries like sqlite3 or SQLAlchemy to connect to the database and execute queries. I would then retrieve the data into a Pandas DataFrame for analysis, enabling efficient manipulation and visualization of the results.”

IBM Python Interview Questions

Here are some important Python array interview questions that you may be asked at IBM. 

58. What are the main differences between a Python list and an array?

The main differences are that Python lists can hold mixed data types, while arrays (from the array module) are restricted to a single data type for better performance and memory efficiency. Arrays are also more efficient for numerical operations, especially when using libraries like NumPy.

59. IBM values efficiency and optimization. How would you optimize array operations in Python?

“To optimize array operations, I would use NumPy, as it provides efficient array manipulations and vectorized operations. This reduces the need for explicit loops and takes advantage of low-level optimizations, leading to significant performance improvements, especially with large datasets.”

Also Read - Top 25+ Python OOPs Interview Question (2024)

Python Viva Questions

Here are some important Python lab viva questions and their answers. 

60. What are Python modules?

Python modules are files containing Python code that can define functions, classes, and variables. They allow for code organization and reuse, and can be imported into other Python scripts using the import statement.

61. How can you handle exceptions in Python?

Exceptions in Python can be handled using try and except blocks. Code that may cause an exception is placed in the try block, while the except block contains the code that executes if an exception occurs, allowing for graceful error handling.

Python Aptitude Questions

These are some common Python assessment questions and their answers. 

62. What will be the output of print(type([]) is list)?

The output will be True. An empty list is indeed of type list.

63. What does the len() function do in Python?

The len() function returns the number of items in an object, such as a list, string, or dictionary.

64. How do you convert a string to an integer in Python?

You can convert a string to an integer using the int() function, like this: int(“123”).

65. What will be the result of the expression 5 // 2 in Python?

The result will be 2. The // operator performs integer division, discarding the remainder.

Also Read - Top 15+ PySpark Interview Questions and Answers (2024)

Python MCQ Interview Questions

Here are some common Python MCQ questions for interview and their answers. 

66. What is the output of print(“Hello”[1])?

• A) H
• B) e
• C) l
• D) o

Answer: B) e

67. Which of the following is a mutable data type in Python?

• A) Tuple
• B) String
• C) List
• D) Integer

Answer: C) List

68. What will be the output of print(3 * ‘A’)?

• A) A
• B) AAA
• C) 3A
• D) Error

Answer: B) AAA

69. Which keyword is used to define a function in Python?

• A) func
• B) define
• C) def
• D) function

Answer: C) def

70. What does the strip() method do in Python?

• A) Removes all whitespace
• B) Removes leading and trailing whitespace
• C) Converts to uppercase
• D) Splits a string

Answer: B) Removes leading and trailing whitespace

Also Read - Top 30 Django Interview Questions Answers (2024)

Python Interview Cheat Sheet – Tips and Tricks

Are you looking for a Python cheat sheet for interview? Well, here are some easy tips you can follow. 

• Understand the question: Take your time to fully understand the question before answering. 
• Start simple: Begin with a straightforward solution, then discuss potential improvements or optimizations.
• Use examples: Illustrate your answers with simple examples to demonstrate your understanding.
• Practice common patterns: Familiarize yourself with common coding patterns and solutions to typical problems.
• Stay calm: If you get stuck, take a deep breath. It’s okay to pause and think before responding.
• Test your code: If coding, mentally run through your code to catch any errors before finalizing your answer.
• Review basic concepts: Be ready to explain fundamental concepts, as interviewers often ask for clarification on your answers.

Wrapping Up

These are the Top 70 Python interview questions and answers you can use to prepare for your next interview. Understanding these concepts will help you feel more confident. For the best Python jobs, visit Hirist. It’s an online job portal where you can easily find all types of IT jobs in India and overseas.