Top 30 Python Interview Questions with Answers 2026 Guide

Python remains the most-asked skill on Indian tech job postings, and interviewers now expect working code, not just definitions. This guide is organised by real Python interview questions instead of generic difficulty buckets, so you can prep exactly what a specific round will test.

TL;DR Summary

• Python interviews test basics first: data types, functions, loops, lists, tuples, dictionaries, and indentation.
• Intermediate questions focus on file handling, exceptions, list comprehension, lambda functions, and coding logic.
• Advanced rounds cover decorators, generators, GIL, memory management, async programming, and scalable project structure.
• Interviewers check syntax, logic, debugging, performance, and clean code thinking.
• Best preparation comes from practicing code, understanding concepts, and revising all difficulty levels.

If you’re just starting your Python journey or preparing for your first tech interview, this section is for you. These questions cover the basics, from data types and syntax to simple coding exercises, and are often asked to gauge how well you understand Python’s core concepts. Mastering these is your first step to building a solid foundation.

Most Python interviews test the same core: syntax fluency, data structures, and how you think through edge cases out loud. Recruiters at Indian product companies and FAANG offices now expect candidates to write runnable code, not just describe concepts. This guide is trimmed to the questions that actually come up, grouped by experience level so you can focus your prep.

Fresher-Level Python Interview Questions

1. What is Python?

Python is an interpreted, object-oriented, high-level, general-purpose programming language with dynamic semantics. The implementation of Python was started in December 1989 by Guido Van Rossum at CWI in the Netherlands.

In February 1991, he published the code to alt. sources. Furthermore, in 1994, Python 1.0 was released.

print("Hello, Python")  # runs top to bottom, no compilation step needed

2. What are the key features of Python?

Developers love Python for a few solid reasons:

• Simplicity & Readability: The syntax is clear and resembles English, making it beginner-friendly.
• Interpreted Language: Python executes lines one by one, which simplifies debugging.
• Dynamically Typed: You don’t need to declare variable types; Python figures it out.
• Cross-Platform Compatibility: Write once, run anywhere (Windows, Linux, Mac).
• Large Standard Library: You get modules for math, file I/O, JSON, OS-level operations, and more out of the box.

If you want to understand why learning Python is important, read the blog – Top 12 Key Benefits of Learning Python 

3. Difference between is and ==?

== checks value equality, is checks identity (same memory object).

a = [1, 2]
b = [1, 2]
print(a == b)   # True
print(a is b)   # False

4. How do you write a function?

def add(a, b):
    return a + b
print(add(3, 5))  # 8

5. What are Python’s built-in data types?

int, float, str, bool, list, tuple, dict, set — each is an object with its own methods.

Junior-Level Python Interview Questions

6. How do you check membership in a list?

fruits = ["apple", "banana"]
print("banana" in fruits)  # True

7. Why is indentation important?

Python uses whitespace, not braces, to define code blocks. Standard is 4 spaces.

8. How do you handle user input?

age = int(input("Enter age: "))  # input() always returns a string, cast as needed

9. What are *args and **kwargs?

def total(*args, **kwargs):
    return sum(args), kwargs
print(total(1, 2, 3, name="Kiran"))  # (6, {'name': 'Kiran'})

10. Explain list comprehension.

squares = [x**2 for x in range(5) if x % 2 == 0]  # [0, 4, 16]

Senior-Level Python Interview Questions

11. How do you handle exceptions?

try:
    x = 10 / 0
except ZeroDivisionError:
    print("Can't divide by zero")
finally:
    print("Done")

12. What is a lambda function?

double = lambda x: x * 2
print(double(5))  # 10

13. How do you read/write files?

with open("data.txt", "r") as f:
    content = f.read()  # auto-closes file

14. append() vs extend()?

append() adds one item (even a list, as a single element); extend() unpacks and adds each item.

a = [1, 2]
a.extend([3, 4])  # [1, 2, 3, 4]

15. What are decorators, and why use them?

Decorators wrap a function to add behavior — logging, timing, auth — without touching its source.

def logger(func):
    def wrapper(*a, **kw):
        print("Called:", func.__name__)
        return func(*a, **kw)
    return wrapper

@logger
def greet(): print("Hi")

Python OOP Interview Questions with Code Examples

16. What does __init__ do?

It’s the constructor — runs automatically when an object is created.

python

class Employee:
    def __init__(self, name, salary):
        self.name = name
        self.salary = salary

17. What is self?

A reference to the current instance, used to access its attributes and methods inside the class.

18. staticmethod vs classmethod?

class Utils:
    @staticmethod
    def add(a, b): return a + b       # no instance/class access needed

    @classmethod
    def create(cls): return cls()      # receives the class itself as 'cls'

19. What are magic (dunder) methods?

Special methods like __str__, __len__, __eq__ that let your objects work with built-in syntax.

class Point:
    def __init__(self, x, y): self.x, self.y = x, y
    def __eq__(self, other): return self.x == other.x and self.y == other.y

20. What is Method Resolution Order (MRO)?

The order Python searches base classes in multiple inheritance, using C3 linearization. Check it with ClassName.__mro__.

Python Data Science Interview Questions

21. NumPy array vs Python list?

NumPy arrays are faster and support vectorized math; lists don’t.

import numpy as np
arr = np.array([1, 2, 3])
print(arr * 2)  # [2 4 6] — no loop needed

22. How do you handle missing values in pandas?

import pandas as pd
df = pd.DataFrame({"age": [25, None, 30]})
df["age"].fillna(df["age"].mean(), inplace=True)

23. Difference between a pandas Series and DataFrame?

A Series is one-dimensional (a single column); a DataFrame is two-dimensional (rows and columns), essentially a collection of Series.

24. What is broadcasting in NumPy?

NumPy automatically expands smaller arrays to match a larger array’s shape during arithmetic, avoiding explicit loops

a = np.array([1, 2, 3])
print(a + 5)  # [6 7 8] — 5 is "broadcast" to each element

25. How do you split data for training and testing?

from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)

Python Interview Questions Asked at FAANG India

26. What is the Global Interpreter Lock (GIL)?

A CPython mechanism that lets only one thread execute Python bytecode at a time, limiting true parallelism for CPU-bound work. It doesn’t affect I/O-bound tasks.

27. Generators vs regular functions?

def countdown(n):
    while n > 0:
        yield n   # pauses and resumes instead of returning everything at once
        n -= 1

28. copy() vs deepcopy()?

import copy
a = [[1, 2], [3, 4]]
b = copy.copy(a)        # shallow — nested lists still shared
c = copy.deepcopy(a)    # deep — fully independent

29. Multithreading vs multiprocessing — when do you use which?

Multithreading suits I/O-bound work (network calls, file reads); multiprocessing suits CPU-bound work since it bypasses the GIL using separate processes.

30. How do you structure a Python project for scale?

Separate folders for app logic, tests, and config, with dependency management and logging as their own layer, not one giant script.

Common Mistakes To Avoid

1. Skipping edge cases in coding rounds: Interviewers at FAANG India specifically probe empty inputs and negative numbers — always test for them out loud.
2. Confusing is with ==: A frequent trick question; always default to == unless you specifically need identity comparison.
3. Ignoring the GIL in system design answers: Claiming “just use threading” for CPU-heavy work is a common senior-round red flag.
4. Overusing except Exception: Catching everything hides real bugs — catch specific exceptions instead.

Want structured, hands-on Python prep with real projects? Check out HCL GUVI’s Python Zero to Hero course, built for exactly this kind of interview readiness.

Quick-Reference Cheatsheet

Conclusion

In conclusion, interviews are not just about syntax recall; they’re about how you think, structure your code, and solve problems under pressure. The key is not to memorize answers but to practice implementing them, tweaking them, and understanding the “why” behind each one. 

Bookmark this guide, revisit the tough ones, and keep coding. You’re closer to cracking that dream Python role than you think!