50+ Python Interview Questions and Answers for 2026

Table of Content

Python will be very popular in 2026. It is used for AI systems cloud automation building APIs and handling data.

Because many people use Python, interviews have become harder and more practical.

Whether you are a beginner, a mid-level developer, a QA engineer or a senior engineer this guide will help you learn all the important Python concepts.

In this comprehensive resource, you will find:

50+ fully explained Python interview questions
Conceptual, theory, and practical coding questions
Multiple python practice questions
Hands-on python coding practice problems
Real-world python coding problems and solutions
Separate sections for freshers and experienced professionals

This guide is made to help with interviews at companies like Google Microsoft Meta Netflix Paytm Swiggy Zoho and more. These companies ask Python questions to check problem-solving skills, coding style, clear thinking and understanding of software design.

Section 1: Why Python Interviews Matter in 2026

Python is not just a simple coding language today. It is used to build modern software. With AI cloud automation and data science growing Python has become the main choice for developers.

✔ Why Python Is Critical for Modern Tech Roles

Python remains the industry favorite because of:

Clean & readable syntax
Huge library ecosystem (NumPy, Pandas, FastAPI, Django, TensorFlow, etc.)
Cross-platform support
Fast development cycles
Strong community support

✔ Python Powers Almost Every Modern Tech Domain

Today, Python is deeply integrated into:

Backend development
Cloud & DevOps automation
Cybersecurity scripting
Machine learning & AI
Data analytics pipelines
Test automation frameworks
API and microservices architecture

This is why companies like Google, Microsoft, Netflix, Paytm, Zoom, and Meta extensively rely on python interview questions during hiring rounds to test:

Logical reasoning
Real-world coding skills
Code optimization
API design thinking
Debugging and troubleshooting
Problem-solving approach

Modern hiring demands not only theory but also hands-on python coding practice and the ability to solve python coding problems and solutions under time pressure.

This guide merges theory + practical knowledge to help you stand out in all interview rounds.

Section 2: Python Basics — Top 20 Python Basic Interview Questions

The following are the most important python basic interview questions frequently asked in fresher-level and junior developer interviews in 2026.

These ensure you have a strong foundation before moving to advanced topics.

Q1. What is Python? Why is it so popular?

Python is a high-level programming language. It is easy to read simple to use and helps people work faster. Python is used in AI machine learning automation data science backend coding cloud work DevOps security and web applications.

Why is Python so popular in 2026?

Python is popular because it is strong and easy to use.

Extremely Easy to Learn and Use
Python code is almost like English. Beginners can quickly understand how programming works. This is why many python basic interview questions start with simple topics like variables loops and data types.

2. Huge Ecosystem of Libraries and Frameworks

Python offers massive libraries like:

NumPy, Pandas → Data analysis
TensorFlow, PyTorch → Machine learning
Django, Flask, FastAPI → Backend development
Boto3, Fabric → Cloud automation
Selenium, PyTest → Automation testing

This makes Python ideal not just for developers but also for testers, data scientists, and cloud engineers.

Cross-Platform and Works Anywhere
Python can run on Linux Windows macOS Android and small devices. This makes it very flexible to use in real life.
Strong Community and Company Support
Companies like Google Microsoft Amazon Meta Netflix use Python a lot. This means Python will keep getting updates and new features.
Good for Automation and Fast Development
Python is used to write scripts for repeated tasks in DevOps AI and other work. It helps finish work quickly.

Because of these reasons the question What is Python is one of the most common python interview questions. It is often asked for both beginners and experienced Python roles.

What are the Key Features of Python

Q2. What are the Key Features of Python?

Python stands out due to several powerful features that make development faster and more efficient.

1. Interpreted Language

Python code is executed line-by-line using the CPython interpreter.
This feature makes debugging simpler and is why Python is preferred in python coding practice and python practice questions used in companies.

2. Object-Oriented Programming (OOP)

Python supports:

Classes
Inheritance
Polymorphism
Encapsulation

Yet it maintains flexibility to be used as a procedural or functional programming language as well.

3. Portable and Cross-Platform

Write code once, run it anywhere — without modification. This is a major benefit in multi-environment development environments like cloud, DevOps, and distributed systems.

4. Highly Scalable and Extensible

Python can integrate with:

C/C++ for performance
Java (via Jython)
.NET (via IronPython)

This hybrid flexibility allows developers to build scalable applications used in production at companies like Instagram and Dropbox.

5. Huge Standard Library

Python includes a “batteries included” philosophy. The standard library provides modules for:

OS operations
File handling
Networking
Regex
Database handling
Testing
Encryption
JSON processing

This reduces dependency on third-party tools—one reason Python dominates automation-based python coding problems and solutions.

6. Support for Multiple Programming Paradigms

Python supports:

Functional programming
Object-oriented programming
Scripting
Modular programming

This versatility is a major factor interviewers test through python programming questions and answers.

This question appears regularly in python interview questions for freshers because it checks conceptual understanding rather than syntax knowledge.

Q3. What is PEP 8? Why is it Important?

PEP 8 (Python Enhancement Proposal 8) is the official style guide for writing clean and readable Python code. It defines formatting rules for:

Indentation
Variable naming conventions
Line length
Code structure
Spacing
Comments and documentation
Best practices for import statements

Why is PEP 8 important?

Companies expect Python developers to write clean, scalable, and maintainable code. In real python coding practice rounds, messy code—even if correct—reduces scores.

What PEP 8 Improves:

✔ Readability

Helps teams understand code easily.

✔ Consistency

Standard style across large projects.

✔ Professionalism

Shows discipline and coding maturity.

✔ Debugging and Collaboration

Code that follows PEP 8 is easier to debug, modify, and maintain.

Example: PEP 8 Compliant Code

def calculate_total(price, tax):

total = price + (price * tax)

return total

Interviewers often ask PEP 8 questions in:

python interview questions for experienced
python coding practice rounds
python coding problems and solutions

Because they want to check whether you can write clean, industry-level code.

Q4. What are Lists and Tuples?

Lists and tuples are two important ways to store data in Python. They are used very often and appear in many python basic interview questions. They are also asked in python interview questions for freshers and for experienced Python jobs.

Both store ordered collections of elements, but they differ in behavior and performance.

Key Differences Between List and Tuple

Feature	List	Tuple
Mutability	Mutable (elements can be changed)	Immutable (elements cannot be modified)
Syntax	[]	()
Performance	Slower due to mutability overhead	Faster because they are fixed
Use Case	When modification is required	When data must remain unchanged
Memory Usage	Uses more memory	Uses less memory

Examples

List Example

fruits = ["apple", "banana", "mango"]

fruits.append("orange") # Allowed

Tuple Example

user = ("Lalit", 27, "Developer")

# user[0] = "Amit" → Not allowed (immutable)

Where Lists and Tuples Are Used in Interviews?

Lists appear in python coding practice problems like sorting, searching, merging, and iteration.
Tuples appear in system design questions, function returns, and immutable data structures.

This is why this question is almost always included in python basic interview questions.

Q5. What is a Dictionary in Python?

A dictionary in Python is an unordered, mutable, and key-value pair data structure. It is one of the most powerful built-in types and is heavily used in real-world python coding problems and solutions.

Structure

Keys → must be unique and immutable
Values → can be any type

Example

user = {

"name": "Lalit",

"role": "Developer",

"experience": 3

}

Key Features

✔ Fast lookup (O(1) average time)
✔ Ideal for structured data
✔ Extensively used in APIs, JSON, configuration files, and backend applications

Why Dictionaries Are Important in Interviews

JSON parsing uses dictionaries
REST API data is dictionary-based
Many python practice questions involve dictionary manipulation

Interviewers frequently test:

Merging dictionaries
Iterating through keys/values
Using dict comprehensions
Handling nested dictionaries

Q6. Explain Python Variables.

Variables in Python are names (identifiers) that reference objects stored in memory. Python uses dynamic typing, meaning you don’t need to declare the datatype explicitly.

Key Properties

✔ Dynamic Typing

x = 10

x = "Hello" # Allowed

✔ Object Reference Model

A variable does not store value directly — it stores a reference to an object in memory.

✔ No Type Declaration Required

name = "Lalit"

age = 25

salary = 75000.50

✔ Memory Allocation is Automatic

Python handles memory using:

Reference counting
Garbage collection

Why Interviewers Ask This Question

Understanding variables is essential for:

python programming questions and answers
debugging
writing efficient code
understanding mutability vs immutability

It is one of the most common python interview questions for freshers.

Q7. What is a Module in Python?

A module is simply a Python file (.py) that contains functions, classes, and variables which you can import and reuse in other programs.

Example: mymodule.py

def greet():

return "Hello from module"

Using the module

import mymodule

print(mymodule.greet())

Why Modules Matter

✔ They promote code reusability
✔ Help structure big projects
✔ Reduce repetition
✔ Used in every python coding practice exercise involving architecture

Modules are the building blocks of Python applications, which is why this appears frequently in python interview questions for experienced roles.

Q8. What is a Package in Python?

A package is a directory (folder) that contains multiple modules and includes an __init__.py file, which signals to Python that the directory should be treated as a package.

Folder Structure Example

myproject/

utils/

__init__.py

math_ops.py

string_ops.py

Purpose of Packages

Organize large applications
Group related modules
Increase maintainability

Interview Tip

Packages appear in python programming questions and answers when dealing with:

application architecture
project structure
modularity

Q9. Explain Python’s Indentation Rule.

Unlike most languages that use { } braces, Python uses indentation to define code blocks.

Example

if age > 18:

print("Adult")

else:

print("Minor")

The default indentation is 4 spaces, not tabs.

Why Indentation Matters

✔ Improves readability
✔ Prevents logical errors
✔ Makes code clean and consistent
✔ Ensures PEP 8 compliance

This is why indentation rules are heavily tested in python practice questions and python coding practice rounds.

Q10. What are Python Namespaces?

A namespace is a mapping between names (identifiers) and the objects they refer to.

Think of it as a container that holds names and helps avoid naming conflicts.

Types of Namespaces

Local Namespace
Inside functions.
Global Namespace
At the module level.
Built-in Namespace
Contains built-in functions like print(), len().

Example

x = 10 # Global namespace

def func():

y = 20 # Local namespace

Why Namespaces Matter in Interviews

They are essential for understanding:

variable scope
memory management
debugging
closures

This question is frequently seen in python interview questions for experienced candidates.

**Q11. What are *args and kwargs in Python? (Deep Explanation)

In Python, *args and **kwargs allow you to pass a variable number of arguments to a function. They are essential for flexible function design and frequently appear in python interview questions for experienced roles.

**1. *args (Non-Keyword Variable Arguments)**

*args collects extra positional arguments into a tuple.

Example

def total(*numbers):

return sum(numbers)

print(total(10, 20, 30)) # Output: 60

2. kwargs (Keyword Variable Arguments)**

**kwargs collects extra keyword arguments into a dictionary.

Example

def user_info(**details):

return details

print(user_info(name="Lalit", age=28))

Why This Question is Important

Used in decorators
Used in class inheritance
Used in API functions
Appears in python practice questions and python programming questions and answers

Q12. What is Type Casting in Python?

Type casting means converting one datatype into another. Python supports explicit and implicit type conversion.

Explicit Type Casting

The programmer manually converts the type.

x = "10"

y = int(x)

Implicit Type Casting

Python automatically converts the type.

x = 10

y = 10.5

result = x + y # Result becomes float

Why Type Casting Matters

Used heavily in python coding practice
Important for input handling
Required in mathematical and data science programs

Q13. Difference Between remove(), pop(), and del?

These are common operations for modifying lists and are frequently asked in python basic interview questions.

Method	Purpose	Example
remove()	Removes the first matching value	lst.remove(5)
pop()	Removes item by index and returns it	lst.pop(2)
del	Deletes index, slice, or entire object	del lst[1], del lst

Example

lst = [10, 20, 30, 40]

lst.remove(20) # removes the value 20

lst.pop(1) # removes item at index 1

del lst[0] # deletes first element

Interview Tip

pop() is the only one that returns the removed element — useful in python coding problems and solutions.

Q14. What is a Lambda Function?

A lambda function is a small, anonymous, inline function defined using the lambda keyword.

Syntax

lambda arguments: expression

Example

square = lambda x: x*x

print(square(5)) # Output: 25

Where Lambda Functions Are Used

Sorting
Filtering
Map/Reduce operations
Functional programming
Interview coding tasks

They appear in many python programming questions and answers because they make code compact and expressive.

Q15. What is the Difference Between append() and extend()?

These are common list methods that behave differently.

append()

Adds one element to the list.

lst = [1, 2, 3]

lst.append([4, 5])

# Result: [1, 2, 3, [4, 5]]

extend()

Adds each element of an iterable to the list.

lst = [1, 2, 3]

lst.extend([4, 5])

# Result: [1, 2, 3, 4, 5]

Why Interviewers Ask This

Misuse of append() and extend() is common among beginners, making this a high-frequency python basic interview question.

Q16. Explain List Comprehension.

List comprehension is a concise and efficient way to build new lists. It is widely tested in python coding practice and python practice questions.

Syntax

[expression for item in iterable if condition]

Example

squares = [x*x for x in range(10)]

Why It's Important

Faster than loops
Clean and readable
Used in python coding problems and solutions involving data transformation

Q17. What is the pass Statement?

pass is a null statement in Python. It does nothing and is used as a placeholder when a statement is syntactically required.

Example

def future_function():

pass

Where pass is Used

Empty loops
Empty classes
Skeleton code
Prototyping

Interviewers ask this to check understanding of Python’s structure and indentation rules.

Q18. What is the Difference Between sort() and sorted()?

Both are used to sort elements, but they behave differently.

sort()

Works only on lists
Sorts the list in-place
Returns None

numbers = [3, 1, 4]

numbers.sort()

sorted()

Works on any iterable
Returns a new sorted list
Original data remains unchanged

result = sorted([3, 1, 4])

In Interviews

Used in python programming questions and answers involving:

Sorting algorithms
Comparators
Custom sorting using key functions

Q19. What is Slicing in Python?

Slicing allows you to extract sub-parts of lists, strings, tuples, and other sequences.

Syntax

sequence[start:stop:step]

Example

text = "PythonInterview"

print(text[0:6]) # Output: Python

print(text[::-1]) # Reverse string

Importance in Interviews

Common in:

string manipulation questions
array-based problems
python coding practice rounds

Q20. What is the Use of init() in Python?

__init__() is a constructor method in Python used to initialize object attributes when an object is created.

Example

class User:

def __init__(self, name, role):

self.name = name

self.role = role

u = User("Lalit", "Developer")

Why It's Important

Core part of OOP
Used heavily in class-based interview questions
Common in python interview questions for experienced

This completes the most frequently asked python basic interview questions.

Section 3: Top Python Interview Questions for Freshers (Deep Explanations)

These questions frequently appear in entry-level technical rounds at companies like Google, TCS, Infosys, Accenture, and Tech Mahindra. Each explanation below is presented in a clear, practical, and beginner-friendly manner.

Q21. What is the difference between Python 2 and Python 3? (Deep Explanation)

Python 2 and Python 3 are fundamentally different languages. Most modern companies now use Python 3, and understanding the differences is a common part of python interview questions for freshers.

Key Differences

Feature	Python 2	Python 3
Print statement	print "Hello"	print("Hello")
Unicode	Text stored as ASCII	Strings are Unicode by default
Division	5/2 → 2 (integer division)	5/2 → 2.5 (true division)
Libraries	Many outdated	Modern, more powerful libraries
Future support	Discontinued in 2020	Actively supported

Why This Matters in Interviews

Companies expect developers to work with Python 3 because:

Better performance
Cleaner syntax
Stronger security
Modern library support for ML, AI, and automation

This makes it one of the most repeated python interview questions.

Q22. What are Python Data Types?

Python provides a rich set of built-in data types that form the foundation of python programming questions and answers during interviews.

Built-in Data Types

int → integers
float → decimal values
str → strings
list → ordered, mutable collections
tuple → ordered, immutable collections
dict → key-value mappings
set → unordered unique elements
complex → complex numbers (3+4j)

Why Data Types Are Important

Data types help Python determine:

how values are stored
what operations can be performed
memory usage

Understanding data types is mandatory for python practice questions.

Q23. What is Mutability?

Mutability refers to whether an object’s value can change after it is created.

Mutable Objects

Can be modified in place:

list
dict
set

lst = [1, 2]

lst.append(3) # Modified

Immutable Objects

Cannot be changed once created:

tuple
str
int
float

text = "hello"

# text[0] = "H" ❌ Not allowed

Why Interviewers Ask This

Mutability affects:

memory usage
performance
thread safety
function behavior

This appears in almost every set of python interview questions for freshers.

Q24. What is an Iterator?

An iterator is an object in Python that can be iterated (looped) one item at a time.

Requirements

An iterator must implement:

__iter__()
__next__()

Example

nums = iter([10, 20, 30])

print(next(nums)) # 10

print(next(nums)) # 20

Real-World Use

Iterators power:

loops
generators
file reading
data streaming

Interviewers use iterator questions to test fundamental Python comprehension.

Q25. What is a Generator?

A generator is a special function that returns values one at a time using the yield keyword instead of return.

Example

def generate_numbers():

for i in range(5):

yield i

Benefits

✔ Saves memory
✔ Faster than creating full lists
✔ Ideal for large datasets

Why This Appears in Interviews

Generators are widely used in:

data pipelines
machine learning
streaming APIs

This makes it an essential concept in python coding practice.

Q26. What is the difference between local and global variables?

Local Variable

Declared inside a function
Available only inside that function

def func():

x = 5 # local variable

Global Variable

Declared outside functions
Can be accessed throughout the program

x = 10 # global variable

global Keyword

x = 100

def change():

global x

x = 200

Why Companies Ask This

It tests understanding of:

variable scope
memory management
debugging

A common part of python interview questions for freshers.

Q27. What is Recursion?

Recursion occurs when a function calls itself until a base condition is reached.

Example

def factorial(n):

if n == 1:

return 1

return n * factorial(n-1)

Important Concepts

Base case
Recursive case
Stack memory

Where Recursion Appears in Interviews

Common in python coding practice involving:

factorial
Fibonacci
tree traversal
divide and conquer problems

Q28. Explain try-except-finally.

This is Python’s primary error-handling mechanism.

Structure

try:

# risky code

except Exception:

# handle error

finally:

# always executes

Purpose

try → executes code
except → catches exceptions
finally → runs even if error occurs

Why It Matters

Handling exceptions is crucial for:

file operations
API requests
database access
automation scripts

Appears in python programming questions and answers for freshers and experienced engineers.

Q29. What is File Handling in Python?

File handling allows reading and writing data to external files.

Basic Functions

open() → open file
read() → read data
write() → write data
close() → close file

Example

with open("data.txt", "r") as f:

content = f.read()

File Modes

"r" → read
"w" → write
"a" → append
"rb" → read binary

Why Companies Test This

Used in:

automation
backend logs
configuration loads
data processing

A favorite topic in python practice questions.

Q30. What are Decorators in Python?

A decorator is a function that modifies or enhances another function without changing its actual code.

Example

def log(func):

def wrapper():

print("Function is running")

func()

return wrapper

@log

def greet():

print("Hello!")

Where Decorators Are Used

Authentication
Logging
API rate limiting
Performance measurement

Why It’s an Important Interview Topic

Decorators combine:

functions
closures
higher-order logic

This question is frequently asked in python interview questions for freshers and intermediate developers.

Section 4: Top 20 Python Interview Questions for Experienced.

These advanced topics commonly appear in python interview questions for experienced, especially for roles involving backend systems, scalable architectures, automation, and distributed computing.

Q31. Explain GIL (Global Interpreter Lock).

The Global Interpreter Lock (GIL) is a mutex in CPython that ensures only one thread executes Python bytecode at any given time—even on multi-core processors.
It prevents memory corruption by making Python’s memory management thread-safe, but also limits parallel execution of CPU-bound threads.

Why GIL exists

CPython uses reference counting for memory management.
Modifying reference counters across threads might cause race conditions.
The GIL simplifies implementation by serializing bytecode execution.

Impact on performance

CPU-bound programs: Slower with threads due to GIL.
I/O-bound programs: Threads work well because they frequently release GIL.

Workarounds

Use multiprocessing to bypass GIL.
Use C extensions or NumPy (which run outside GIL).
Prefer asyncio for async I/O tasks.

GIL is always asked in python interview questions for experienced, especially for system design roles.

Q32. Difference between multiprocessing and multithreading?

Feature	Multithreading	Multiprocessing
GIL impact	Threads blocked by GIL for CPU tasks	Each process has its own Python interpreter—no GIL
Memory	Shared	Independent
Best for	I/O-bound tasks	CPU-bound tasks
Performance	Lightweight; lower overhead	Higher overhead; true parallelism
Communication	Shared variables, queues	IPC, queues, pipes

Summary

Use multithreading for network requests, file handling, I/O waits.
Use multiprocessing for ML models, number crunching, data processing pipelines.

This difference is heavily tested as part of python interview questions for experienced.

Q33. What are closures in Python?

A closure occurs when an inner function remembers and uses variables from the outer function, even after the outer function has finished executing.

Example

def outer(msg):

def inner():

print(msg)

return inner

f = outer("Hello")

f() # remembers msg even after outer ends

Why closures matter

Used in decorators
Enable data hiding
Allow function factories

Closures are essential in python programming practice and functional-style coding.

Q34. What are Python descriptors?

Descriptors are objects that define how attributes are accessed in classes.
A descriptor must implement one or more of these methods:

__get__(self, instance, owner)
__set__(self, instance, value)
__delete__(self, instance)

Use cases

Implementing custom attribute access
Validation (e.g., typed fields in frameworks)
Property creation
ORM field descriptors (like Django fields)

Example

class Value:

def __get__(self, obj, objtype):

return obj._value

def __set__(self, obj, val):

obj._value = val

class Test:

x = Value()

Descriptors are commonly asked in deep python interview questions for experienced.

Q35. Explain metaclasses.

A metaclass is the class of a class — meaning it defines how a class behaves.
Just like classes create objects, metaclasses create classes.

Use cases

Enforcing coding standards
Validating class attributes
Creating frameworks (Django ORM uses metaclasses)
Auto-registering classes in a registry

Example

class Meta(type):

def __new__(cls, name, bases, attrs):

print("Creating class:", name)

return super().__new__(cls, name, bases, attrs)

class Test(metaclass=Meta):

pass

Metaclasses are a high-level concept and frequently appear in python interview questions for experienced engineers.

Q36. What is Monkey Patching?

Monkey patching means modifying code at runtime without altering the original source file.

Example

import math

math.sqrt = lambda x: "patched!"

print(math.sqrt(4))

Use cases

Hotfixing functions dynamically
Testing (mocking methods)
Extending behavior of libraries not under your control

Risk

Can break code unexpectedly
Hard to debug

Because of its power and risk, it's a frequent topic in senior-level python interview questions.

Q37. What is memoization?

Memoization is a technique to speed up functions by caching previously computed results.

Why used?

Saves time for repetitive function calls
Optimizes recursive functions such as Fibonacci

Example

from functools import lru_cache

@lru_cache(maxsize=None)

def fib(n):

if n < 2:

return n

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

Memoization is very common in python coding practice, algorithm interviews, and performance optimization.

Q38. Explain async and await.

async and await enable asynchronous, non-blocking programming in Python.

Key concepts

async function → returns a coroutine
await → pauses execution until awaited task completes
Uses an event loop
Ideal for thousands of concurrent network operations

Example

import asyncio

async def task():

print("Start")

await asyncio.sleep(1)

print("End")

asyncio.run(task())

Async programming appears often in python interview questions for experienced relating to backend APIs.

Q39. What is the difference between deep copy and shallow copy?

Type	Behavior
Shallow Copy	Copies only the outer object; inner objects share references
Deep Copy	Recursively copies everything, creating independent objects

Example

import copy

shallow = copy.copy(obj)

deep = copy.deepcopy(obj)

Use case

Deep copy is used when modifying nested objects without affecting originals.

This is usually asked during python coding problems and solutions.

Q40. What is a context manager?

A context manager handles setup and teardown logic using __enter__() and __exit__().

Usage Example

with open("data.txt") as f:

content = f.read()

Why useful

Manages resources safely
Avoids memory leaks
Closes files, DB connections, locks, sockets

Custom context manager example

class Manager:

def __enter__(self):

print("Start")

def __exit__(self, *args):

print("End")

with Manager():

pass

Context managers frequently appear in advanced python programming questions and answers.

Section 5: Important Python Coding Problems and Solutions (Top 15 — Deep Explanations)

This section covers real-world python coding problems and solutions frequently asked in technical interviews at companies like TCS, Infosys, Wipro, Accenture, Amazon, and startups.
These foundational challenges help you improve your python coding practice, especially for online assessments and onsite coding rounds.

Q41. Reverse a string without using slicing

Problem

Reverse a string without using Python’s slicing feature (s[::-1]).

Solution

def rev(s):

res = ""

for ch in s:

res = ch + res

return res

Explanation (Deep)

We iterate through each character.
Instead of appending at the end, we prepend each character to res.
This builds the reversed string step-by-step.

Time Complexity:

O(n) — iterates through the string once.

This question repeatedly appears in python coding practice and beginner-level python programming questions and answers.

Q42. Check if a number is prime

Solution

def is_prime(n):

if n < 2:

return False

for i in range(2, int(n**0.5)+1):

if n % i == 0:

return False

return True

Explanation (Deep)

A prime number is divisible only by 1 and itself.
We optimize by checking till square root of n, not the whole range.
If any divisor is found, the number is not prime.

Time Complexity:

O(√n) — optimized for large input.

Prime-check problems are essential in python coding problems and solutions for freshers.

Q43. Find the factorial using recursion

Solution

def fact(n):

return 1 if n == 0 else n * fact(n-1)

Explanation (Deep)

Uses the mathematical definition:
n! = n × (n−1)!
Base case: factorial of 0 is 1.
Recursive function calls reduce the problem size steadily.

Time Complexity:

O(n) due to recursion depth.

Factorial recursion is a classic in python programming questions and answers.

Q44. Count vowels in a string

Solution

sum(ch in "aeiou" for ch in s.lower())

Explanation (Deep)

Convert the string to lowercase so checks are uniform.
Use a generator expression to count matches.
ch in "aeiou" returns True or False, and sum() converts them to integers.

Time Complexity:

O(n)

This lightweight approach appears often in python interview questions for freshers and python practice questions.

Q45. Find duplicates in a list

Solution

def dupes(lst):

seen = set()

return [x for x in lst if x in seen or seen.add(x)]

Explanation (Deep)

Maintain a seen set.
For each element:
- If already seen → it's a duplicate.
- If not → add to the set using seen.add(x).

Why this works

set.add() returns None, which is considered False.
This clever trick helps detect duplicates in one pass.

Time Complexity:

O(n) — set operations are O(1).

A very common task in python coding practice.

Q46. Check if a string is palindrome

Solution

s == s[::-1]

Explanation (Deep)

A palindrome reads the same forwards and backwards.
Using slicing simplifies this drastically.

Time Complexity:

O(n)

Palindrome checks are very frequent in python basic interview questions.

Q47. Find the second largest number in a list

Solution

sorted(list(set(nums)))[-2]

Explanation (Deep)

Convert list to set → removes duplicates.
Sort values.
Pick the second last element → second largest.

Edge Cases

List with less than 2 unique numbers.
Negative values.
Mixed unsorted data.

Time Complexity:

O(n log n) due to sorting.

These types of ranking questions are part of many python programming questions and answers.

Q48. Generate Fibonacci series

Solution

def fib(n):

a, b = 0, 1

for _ in range(n):

print(a, end=" ")

a, b = b, a + b

Explanation (Deep)

The Fibonacci sequence starts with 0 and 1, and each next number is the sum of the previous two.
This iterative approach avoids recursion overhead.

Time Complexity:

O(n)

Fibonacci is a classic in python coding problems and solutions for logic testing.

Q49. Remove duplicates from a list while maintaining order

Solution

list(dict.fromkeys(lst))

Explanation (Deep)

dict.fromkeys() removes duplicates while keeping insertion order.
Converting dict keys back to a list gives the cleaned result.

Time Complexity:

O(n)

This trick is extremely popular in interview assessments and python coding practice.

Q50. Check if two strings are anagrams

Solution

sorted(a) == sorted(b)

Explanation (Deep)

Two strings are anagrams if they contain the same characters in any order.
Sorting both strings aligns characters, making comparison easy.

Time Complexity:

O(n log n) due to sorting.

Anagram checks frequently appear in both python basic interview questions and python coding problems and solutions.

Section 6: Expert-Level Python Practice Questions (15 Real Interview Problems)

This section focuses on expert-level python practice questions often seen in FAANG, top MNCs, fintech companies, and high-growth startups.
These questions help sharpen your logic, problem-solving skills, and understanding of Python internals—crucial for senior technical interviews and advanced python coding practice.

Implement an LRU Cache

Building an LRU (Least Recently Used) cache tests your understanding of:

HashMaps
Doubly linked lists
Time complexity optimization

Professional-level companies expect O(1) operations for both insert and retrieval.

Rotate an Array by k Steps

Candidates should know the three recommended approaches:

Using slicing
Using a reverse algorithm
Using modular arithmetic

This checks your mastery of arrays, indices, and algorithm optimization.

Build Your Own map() Function

Implementing a custom map() tests:

First-class functions
Iterators
Functional programming concepts

This is a favorite in python coding problems and solutions due to its simplicity yet conceptual depth.

Merge Two Sorted Lists

A classic two-pointer problem.
Interviewers want to see clean logic and understanding of sorting strategies.
Often asked in python programming questions and answers for freshers and experienced.

Convert JSON to a Python Class

Tests your knowledge of:

json.loads()
OOP concepts
Dynamic attribute creation

Used frequently in backend and API-driven roles.

Extract Domain Name from URL

This python practice question checks your ability to use:

Regular expressions
Python’s urllib module
String manipulation

Flatten Nested Lists

This can be solved using:

Recursion
Iterative stack
Python generators

Interviewers test your ability to work with irregular data structures.

8. Implement Binary Search

A fundamental algorithm expected in any coding interview.
Candidates must implement both:

Iterative version
Recursive version

Find the Top 3 Frequent Elements

Requires using:

Dictionaries
Sorting
Heap (priority queue)

A common question for data-heavy roles in 2026.

Validate Parentheses

Check your stack knowledge.
You must handle edge cases involving mismatched or incomplete brackets.

Create a Custom Exception Class

Demonstrates your understanding of:

Error handling
Class inheritance
Custom application flows

Senior Python roles frequently expect this knowledge.

Remove Nth Node from End of a Linked List

Tests your knowledge of:

Two-pointer technique
Linked list traversal
Edge case handling

Convert List of Dicts into CSV

A practical task involving:

File handling
Python’s built-in csv module
Data formatting logic

This appears in many python coding practice assessments.

Build Your Own Decorator

This checks your understanding of:

Closures
Higher-order functions
Wrapper functions
Metadata preservation (functools.wraps)

Decorators are a fundamental concept in advanced Python development.

Create a Generator That Yields Infinite Numbers

Tests generator internals:

Lazy evaluation
yield keyword
Memory efficiency

A classic python practice question for automation engineers and data pipeline developers.

These 15 expert-level challenges help you master real-world python coding problems and solutions used in competitive hiring environments.

Section 7: Final Python Programming Questions and Answers (Advanced Mix — Deep)

This final section combines concept-heavy, reasoning-based python programming questions and answers asked during senior-level technical interviews in 2026.

Q51. What is Duck Typing? (Deep Explanation)

Duck Typing means the behavior of an object matters more than its actual type.

✔ If an object behaves like a list, Python treats it like a list.
✔ If it supports iteration, Python considers it iterable.

This aligns with Python’s philosophy:
“If it walks like a duck and quacks like a duck, it’s a duck.”

Why Do Interviewers Ask This?

To test understanding of Python’s dynamic typing, flexibility, and runtime behavior.
Highly common in python interview questions for experienced.

Q52. What is Pickling? (Deep Explanation)

Pickling is the process of serializing Python objects into bytes so they can be:

Stored in files
Transmitted over networks
Cached
Saved for later use

Python uses the pickle module for this.

Example:

import pickle

pickle.dump(obj, open("data.pkl", "wb"))

Why It Matters

Serialization is critical in:

Machine learning model storage
Distributed systems
API communication
Session management

Thus it appears frequently in python programming questions and answers.

Q53. What is a Virtual Environment? (Deep Explanation)

A Python virtual environment is an isolated workspace that contains:

Its own Python interpreter
Its own site-packages
Its own dependency versions

You can have different environments for:

Flask projects
Django projects
Data science notebooks
Automation tools

Why It’s Important

It prevents dependency conflicts, allowing cleaner deployments and reproducible builds.

Q54. What is a REST API in Python? (Deep Explanation)

REST (Representational State Transfer) is an architectural style for building scalable APIs.
In Python, REST APIs are commonly built using:

Flask – lightweight, simple routing
FastAPI – fastest Python framework, async-first
Django REST Framework (DRF) – enterprise-grade architecture

Key Characteristics of REST APIs

✔ Stateless communication
✔ JSON input/output
✔ Use of HTTP verbs (GET, POST, PUT, DELETE)
✔ Client–server separation

Why Interviewers Ask

REST APIs are essential for backend, cloud, DevOps, and microservice engineering roles in 2026.

Tags: Python Interview Questions and Answers

Q1. What is Python? Why is it so popular?

Why is Python so popular in 2026?

2. Huge Ecosystem of Libraries and Frameworks

Q2. What are the Key Features of Python?

1. Interpreted Language

2. Object-Oriented Programming (OOP)

3. Portable and Cross-Platform

4. Highly Scalable and Extensible

5. Huge Standard Library

6. Support for Multiple Programming Paradigms

Q3. What is PEP 8? Why is it Important?

Why is PEP 8 important?

What PEP 8 Improves:

✔ Readability

✔ Consistency

✔ Professionalism

✔ Debugging and Collaboration

Example: PEP 8 Compliant Code

Q4. What are Lists and Tuples?

Key Differences Between List and Tuple

Examples

List Example

Tuple Example

Where Lists and Tuples Are Used in Interviews?

Q5. What is a Dictionary in Python?

Structure

Example

Key Features

Why Dictionaries Are Important in Interviews

Q6. Explain Python Variables.

Key Properties

✔ Dynamic Typing

✔ Object Reference Model

✔ No Type Declaration Required

✔ Memory Allocation is Automatic

Why Interviewers Ask This Question

Q7. What is a Module in Python?

Example: mymodule.py

Using the module

Why Modules Matter

Q8. What is a Package in Python?

Folder Structure Example

Purpose of Packages

Interview Tip

Q9. Explain Python’s Indentation Rule.

Example

Why Indentation Matters

Q10. What are Python Namespaces?

Types of Namespaces

Example

Why Namespaces Matter in Interviews

Q11. What are *args and **kwargs in Python? (Deep Explanation)

1. *args (Non-Keyword Variable Arguments)

Example

2. **kwargs (Keyword Variable Arguments)

Example

Why This Question is Important

Q12. What is Type Casting in Python?

Explicit Type Casting

Implicit Type Casting

Why Type Casting Matters

Q13. Difference Between remove(), pop(), and del?

Example

Interview Tip

Q14. What is a Lambda Function?

Syntax

Example

Where Lambda Functions Are Used

Q15. What is the Difference Between append() and extend()?

append()

extend()

Why Interviewers Ask This

Q16. Explain List Comprehension.

Syntax

Example

Why It's Important

Q17. What is the pass Statement?

Example

Where pass is Used

Q18. What is the Difference Between sort() and sorted()?

**Q11. What are *args and kwargs in Python? (Deep Explanation)

**1. *args (Non-Keyword Variable Arguments)**

2. kwargs (Keyword Variable Arguments)**