Top 10 Python Interview Questions with Detailed Answers

Preparing for a Python interview can feel overwhelming, especially if you are not sure what kind of questions to expect. To help you strengthen your preparation, this article covers the top 10 Python interview questions with detailed answers. Each answer includes explanations, code examples, and key points that interviewers often look for. Whether you are a fresher or an experienced developer, this guide will help you revise the essentials and present your knowledge with confidence.1. What is Python?

What is Python?

Python is a high-level, interpreted programming language that emphasizes readability and ease of use. Designed by Guido van Rossum and first released in 1991, Python has become one of the most widely used languages in data science, web development, machine learning, automation, and more.

Key points to mention:

• High-level language: Abstracts away complex memory management.
• Interpreted: Executes code line by line, making debugging easier.
• Multi-paradigm support: Object-oriented, procedural, and functional styles.
• Cross-platform: Runs on Windows, Linux, macOS, and more.

Interviewers expect you to emphasize Python’s simplicity and its role as a versatile tool across domains.

What are Python’s key features?

Python is popular because of its rich features that support developers at all levels.

Essential features include:

• Easy syntax: Simple, English-like structure for faster coding.
• Interpreted and dynamically typed: No need to declare data types explicitly.
• Extensive standard libraries: Modules for math, file I/O, networking, data handling, etc.
• Cross-platform support: Write once, run anywhere.
• Huge community support: Abundant tutorials, open-source packages, and forums.

These features make Python suitable for both beginners and professionals, especially in areas like machine learning and data analytics.

3. What are Python’s data types?

Python provides a rich set of built-in data types to represent different kinds of information.

Common data types:

• Numeric types: int, float, complex
• Sequence types: str, list, tuple
• Mapping type: dict
• Set types: set, frozenset
• Boolean type: bool
• Special type: NoneType

Example:

x = 10          # int
y = 3.14        # float
z = 2 + 3j      # complex
name = "Alice"  # str
nums = [1, 2, 3] # list
coords = (1, 2)  # tuple
unique = {1, 2, 3} # set
flag = True       # bool
nothing = None    # NoneType

Interviewers may also ask about mutability — for instance, lists are mutable while tuples are immutable.

4. What is the difference between list, tuple, and set?

This is one of the most frequently asked Python interview questions. These three data structures serve different purposes:

• List: Ordered, mutable, allows duplicate elements.

lst = [1, 2, 2, 3]

• Tuple: Ordered, immutable, allows duplicate elements.

tpl = (1, 2, 2, 3)

• Set: Unordered, mutable, only unique items.

st = {1, 2, 3}

Key differences:

• Lists and tuples maintain order; sets do not.
• Lists and sets are mutable; tuples are not.
• Sets automatically eliminate duplicates.

Understanding when to use each is crucial for efficient programming.

What are *args and **kwargs?

In Python, functions can accept a variable number of arguments using *args and **kwargs.

• *args: Captures extra positional arguments as a tuple.
• **kwargs: Captures extra keyword arguments as a dictionary.

Example:

def demo_func(*args, **kwargs):
    print("Positional args:", args)
    print("Keyword args:", kwargs)

# Function call
demo_func(1, 2, 3, name="Alice", age=25)

Output:

Positional args: (1, 2, 3)
Keyword args: {'name': 'Alice', 'age': 25}

This flexibility is especially useful when writing general-purpose functions.

What is a lambda function?

A lambda function is an anonymous, one-line function used for short, throwaway operations.

Syntax:

lambda arguments: expression

Example:

square = lambda x: x**2
print(square(5))  # Output: 25

Lambda functions are commonly used inside higher-order functions like map(), filter(), and sorted().

Example with filter:

nums = [1, 2, 3, 4, 5]
even = list(filter(lambda x: x % 2 == 0, nums))
print(even)  # [2, 4]

What is list comprehension?

List comprehension provides a concise way to create lists using a single line of code.

Example:

squares = [x**2 for x in range(5)]
print(squares)  # [0, 1, 4, 9, 16]

With condition:

even_squares = [x**2 for x in range(10) if x % 2 == 0]
print(even_squares)  # [0, 4, 16, 36, 64]

This technique improves readability and often replaces longer loops.

What are Python modules and packages?

• Module: A Python file (.py) containing functions, classes, or variables. Example: math.py
• Package: A collection of modules in a directory with an __init__.py file.

Example:

Suppose we have the following structure:

my_project/
    __init__.py
    module1.py
    module2.py

Here, my_project is a package, while module1 and module2 are modules.

Importing:

import math
print(math.sqrt(16))  # 4.0

Packages help organize large codebases into manageable components.

What is the difference between deep copy and shallow copy?

Copying objects in Python can be tricky because of references.

• Shallow copy: Creates a new object but references the same nested objects.

import copy
lst1 = [[1, 2], [3, 4]]
lst2 = copy.copy(lst1)
lst2[0][0] = 99
print(lst1)  # [[99, 2], [3, 4]]

• Deep copy: Creates a completely independent copy, including nested objects.

lst1 = [[1, 2], [3, 4]]
lst3 = copy.deepcopy(lst1)
lst3[0][0] = 99
print(lst1)  # [[1, 2], [3, 4]]

Key point:

Deep copy avoids unexpected changes when working with complex data structures.

What is the difference between is and == in Python?

• ==** (Equality operator)**: Checks whether two objects have the same value.
• is** (Identity operator)**: Checks whether two variables point to the same object in memory.

Example:

a = [1, 2, 3]
b = [1, 2, 3]
print(a == b)  # True
print(a is b)  # False

In the example above, a and b have the same contents but are stored in different memory locations.

These top 10 Python interview questions cover fundamental concepts that are highly likely to appear in coding interviews. From data types and function arguments to lambda functions and object copying, these topics test your ability to write efficient, clear, and bug-free Python code. The more you practice these questions with examples, the more confident you will feel during interviews.