Python Interview Questions - Paginated

Python Interview Questions

A list of frequently asked Python interview questions with answers for freshers and

experienced are given below.

1️⃣ What is Python?

Python is a general-purpose, high-level programming language created by Guido van Rossum and released in 1991. It features:

Cross-platform compatibility: Runs equally well on Windows, Linux, UNIX, and macOS
Object-oriented design: Supports OOP concepts with elegant implementation
Dynamic typing and binding: No need to declare variable types
Rich built-in data structures: Lists, dictionaries, sets, and more
Concise syntax: Requires fewer lines of code compared to other languages

Python has become the language of choice for:

Data Science
Machine Learning
Artificial Intelligence
Web Development
Automation and Scripting
Scientific Computing

Key Stat: Python has over 8.2 million developers worldwide, making it one of the most popular programming languages.

2️⃣ Why Python?

# Python's simplicity in action
def greet(name):
    return f"Hello, {name}!"

print(greet("Developer"))  # Outputs: Hello, Developer!

Python offers numerous advantages that make it the preferred choice for many developers:

Feature	Benefit
🔄 Interpreted Language	Code executes immediately without compilation step
🌐 Cross-Platform	Works on Windows, Mac, Linux, Raspberry Pi, etc.
📝 Simple Syntax	Easy to read and write with minimal punctuation
⚡ Rapid Development	Create prototypes and MVPs quickly
🧩 Multiple Paradigms	Supports procedural, object-oriented, and functional programming
🆓 Free & Open Source	No licensing costs with extensive community support
📚 Rich Standard Library	"Batteries included" philosophy reduces need for external dependencies
🔌 Extensible	Easily integrates with C/C++ modules for performance-critical tasks

Python's growing popularity according to TIOBE index

3️⃣ What are the applications of Python?

Python's versatility makes it suitable for a wide range of applications:

Web Development

Frameworks: Django, Flask, Pyramid, FastAPI
CMS Systems: Plone, Django CMS
Popular Sites: Instagram, Pinterest, Mozilla, Spotify

Data Science & ML

Libraries: NumPy, Pandas, SciPy, Matplotlib
ML Frameworks: TensorFlow, PyTorch, Scikit-learn
Applications: Predictive analytics, recommendation systems

Automation & Scripting

System administration
DevOps tools
Task automation

Other Application Areas

🎮 Game Development: PyGame, Panda3D
🔬 Scientific Computing: Used at CERN, NASA
🖼️ Image Processing: Pillow, OpenCV
💼 Business Applications: Odoo, Tryton
🖥️ Desktop GUIs: Tkinter, PyQt, Kivy
🤖 Robotics: ROS (Robot Operating System)
🔒 Cybersecurity: Network scanning, penetration testing

Pro Tip: For interviews, be prepared to discuss how you've used Python in real-world applications relevant to the position you're applying for.

4️⃣ What are the advantages of Python?

Key Advantages of Python

⚙️ Interpreted Language

Python code is executed line by line, eliminating the compilation step and making development faster. The interpreter can run on any platform, making Python truly portable.

🔓 Free and Open Source

Python can be freely distributed and used commercially without licensing fees. Its open-source nature means continuous improvement by a global community.

🧩 Extensible and Embeddable

Python can be extended with modules written in C, C++, or other languages. It can also be embedded into existing applications to provide a scripting interface.

🎯 Object-Oriented

Python's object-oriented approach helps in creating reusable, modular code with clean abstractions.

📊 Rich Data Structures

Python comes with built-in data structures like:

# List example
my_list = [1, 2, 3, 'Python']

# Dictionary example
my_dict = {'language': 'Python', 'version': 3.10}

# Tuple example
my_tuple = (1, 2, 'immutable')

# Set example
my_set = {1, 2, 3, 3}  # Stores {1, 2, 3}

📖 Readability

Python's clean syntax with proper indentation enforces code readability, making maintenance easier.

🌉 Cross-Platform

Write once, run anywhere - Python programs can run on any platform with minimal or no modifications.

5️⃣ What is PEP 8?

PEP 8 is the Python Enhancement Proposal that provides style guidelines for Python code. Created in 2001 by Guido van Rossum (Python's creator), Barry Warsaw, and Nick Coghlan, it's the coding convention most Python developers follow.

Key PEP 8 Recommendations:

# Correct indentation (4 spaces)
def function_name(parameter_1, parameter_2):
    """Docstring explaining the function"""
    # Space after # for inline comments
    result = parameter_1 + parameter_2  # Good spacing around operators
    return result

# Correct naming conventions
CONSTANT_VALUE = 100
class MyClass:
    pass

Style Element	Recommendation
Indentation	4 spaces (no tabs)
Line Length	Maximum of 79 characters
Blank Lines	2 lines between top-level definitions, 1 line between methods
Imports	One per line, grouped in order: standard library, third-party, local application
Whitespace	Avoid extraneous spaces, use before/after operators
Naming	lowercase_with_underscores for functions/variables, CamelCase for classes
Comments	Complete sentences, start with # and space

Interview Tip: Mentioning your adherence to PEP 8 demonstrates your commitment to writing clean, maintainable code that follows community standards.

6️⃣ What do you mean by Python literals?

Python literals are data items that have a fixed value. They represent themselves rather than variables.

Types of Python Literals

📝 String Literals

Represented by text enclosed in quotes:

# Single quotes
name = 'Python'

# Double quotes
language = "Python 3.10"

# Triple quotes (multiline)
description = '''Python is
a programming
language'''

# Raw string (ignores escape characters)
raw_string = r"C:\new\file.txt"

🔢 Numeric Literals

# Integer literal
count = 100

# Float literal
pi = 3.14159

# Complex literal
complex_num = 3 + 4j

✅ Boolean Literals

is_valid = True
has_error = False

# Booleans can be used in arithmetic (True=1, False=0)
x = True + 3  # x = 4
y = False + 5  # y = 5

🚫 Special Literal - None

# None represents absence of value
empty_value = None
print(empty_value is None)  # True

🔄 Collection Literals

# List literal
my_list = [1, 2, 3, 'Python']

# Dictionary literal
my_dict = {'name': 'Python', 'version': 3.10}

# Tuple literal
my_tuple = (1, 2, 'Python')

# Set literal
my_set = {1, 2, 3}

Interview Note: Understanding literals is fundamental to Python programming and shows your grasp of basic syntax.

7️⃣ Explain Python Functions

Functions in Python are blocks of reusable code designed to perform a specific task, promoting code reusability and modularity.

Types of Functions in Python

1️⃣ Built-in Functions

These are pre-defined functions that come with Python:

# Examples of built-in functions
length = len("Python")  # Returns 6
maximum = max(10, 20, 30)  # Returns 30
numbers = list(range(5))  # Returns [0, 1, 2, 3, 4]

2️⃣ User-defined Functions

Functions created by the programmer:

# Simple user-defined function
def greet(name):
    """This function greets the person passed in as a parameter"""
    return f"Hello, {name}!"

# Function with default parameter
def power(base, exponent=2):
    """Returns base raised to exponent power"""
    return base ** exponent

# Function with multiple return values
def statistics(numbers):
    """Returns min, max and average of numbers"""
    return min(numbers), max(numbers), sum(numbers)/len(numbers)

3️⃣ Anonymous (Lambda) Functions

Compact, one-line functions without a formal definition:

# Lambda function for squaring a number
square = lambda x: x**2

# Using lambda with map
numbers = [1, 2, 3, 4]
squared = list(map(lambda x: x**2, numbers))  # [1, 4, 9, 16]

Function Arguments

Argument Type	Description	Example
Required	Must be provided	`def add(a, b):`
Default	Optional with default values	`def greet(name="Guest"):`
Variable Length	Accept multiple values	`def sum(*args):`
Keyword	Named parameters	`def profile(**kwargs):`

Interview Tip: Be prepared to write functions demonstrating different parameter types and return patterns during technical interviews.

8) What is zip() function in Python?

A list of frequently asked Python interview questions with answers for freshers and

experienced are given below.

1️⃣ What is Python?

Python is a general-purpose, high-level programming language created by Guido van Rossum and released in 1991. It features:

Cross-platform compatibility: Runs equally well on Windows, Linux, UNIX, and macOS
Object-oriented design: Supports OOP concepts with elegant implementation
Dynamic typing and binding: No need to declare variable types
Rich built-in data structures: Lists, dictionaries, sets, and more
Concise syntax: Requires fewer lines of code compared to other languages

Python has become the language of choice for:

Data Science
Machine Learning
Artificial Intelligence
Web Development
Automation and Scripting
Scientific Computing

Key Stat: Python has over 8.2 million developers worldwide, making it one of the most popular programming languages.

2️⃣ Why Python?

# Python's simplicity in action

def greet(name):

return f"Hello, {name}!"

print(greet("Developer")) # Outputs: Hello, Developer!

Python offers numerous advantages that make it the preferred choice for many developers:

Feature	Benefit
🔄 Interpreted Language	Code executes immediately without compilation step
🌐 Cross-Platform	Works on Windows, Mac, Linux, Raspberry Pi, etc.
📝 Simple Syntax	Easy to read and write with minimal punctuation
⚡ Rapid Development	Create prototypes and MVPs quickly
🧩 Multiple Paradigms	Supports procedural, object-oriented, and functional programming
🆓 Free & Open Source	No licensing costs with extensive community support
📚 Rich Standard Library	"Batteries included" philosophy reduces need for external dependencies
🔌 Extensible	Easily integrates with C/C++ modules for performance-critical tasks

Python's growing popularity according to TIOBE index

3️⃣ What are the applications of Python?

Python's versatility makes it suitable for a wide range of applications:

Web Development

Frameworks: Django, Flask, Pyramid, FastAPI
CMS Systems: Plone, Django CMS
Popular Sites: Instagram, Pinterest, Mozilla, Spotify

Data Science & ML

Libraries: NumPy, Pandas, SciPy, Matplotlib
ML Frameworks: TensorFlow, PyTorch, Scikit-learn
Applications: Predictive analytics, recommendation systems

Automation & Scripting

System administration
DevOps tools
Task automation

Other Application Areas

🎮 Game Development: PyGame, Panda3D
🔬 Scientific Computing: Used at CERN, NASA
🖼️ Image Processing: Pillow, OpenCV
💼 Business Applications: Odoo, Tryton
🖥️ Desktop GUIs: Tkinter, PyQt, Kivy
🤖 Robotics: ROS (Robot Operating System)
🔒 Cybersecurity: Network scanning, penetration testing

Pro Tip: For interviews, be prepared to discuss how you've used Python in real-world applications relevant to the position you're applying for.

4️⃣ What are the advantages of Python?

Key Advantages of Python

⚙️ Interpreted Language

Python code is executed line by line, eliminating the compilation step and making development faster. The interpreter can run on any platform, making Python truly portable.

🔓 Free and Open Source

Python can be freely distributed and used commercially without licensing fees. Its open-source nature means continuous improvement by a global community.

🧩 Extensible and Embeddable

Python can be extended with modules written in C, C++, or other languages. It can also be embedded into existing applications to provide a scripting interface.

🎯 Object-Oriented

Python's object-oriented approach helps in creating reusable, modular code with clean abstractions.

📊 Rich Data Structures

Python comes with built-in data structures like:

# List example

my_list = [1, 2, 3, 'Python']

# Dictionary example

my_dict = {'language': 'Python', 'version': 3.10}

# Tuple example

my_tuple = (1, 2, 'immutable')

# Set example

my_set = {1, 2, 3, 3} # Stores {1, 2, 3}

📖 Readability

Python's clean syntax with proper indentation enforces code readability, making maintenance easier.

🌉 Cross-Platform

Write once, run anywhere - Python programs can run on any platform with minimal or no modifications.

5️⃣ What is PEP 8?

Key PEP 8 Recommendations:

# Correct indentation (4 spaces)

def function_name(parameter_1, parameter_2):

"""Docstring explaining the function"""

# Space after # for inline comments

result = parameter_1 + parameter_2 # Good spacing around operators

return result

# Correct naming conventions

CONSTANT_VALUE = 100

class MyClass:

pass

Style Element	Recommendation
Indentation	4 spaces (no tabs)
Line Length	Maximum of 79 characters
Blank Lines	2 lines between top-level definitions, 1 line between methods
Imports	One per line, grouped in order: standard library, third-party, local application
Whitespace	Avoid extraneous spaces, use before/after operators
Naming	lowercase_with_underscores for functions/variables, CamelCase for classes
Comments	Complete sentences, start with # and space

Interview Tip: Mentioning your adherence to PEP 8 demonstrates your commitment to writing clean, maintainable code that follows community standards.

6️⃣ What do you mean by Python literals?

Python literals are data items that have a fixed value. They represent themselves rather than variables.

Types of Python Literals

📝 String Literals

Represented by text enclosed in quotes:

# Single quotes

name = 'Python'

# Double quotes

language = "Python 3.10"

# Triple quotes (multiline)

description = '''Python is

a programming

language'''

# Raw string (ignores escape characters)

raw_string = r"C:\new\file.txt"

🔢 Numeric Literals

# Integer literal

count = 100

# Float literal

pi = 3.14159

# Complex literal

complex_num = 3 + 4j

✅ Boolean Literals

is_valid = True

has_error = False

# Booleans can be used in arithmetic (True=1, False=0)

x = True + 3 # x = 4

y = False + 5 # y = 5

🚫 Special Literal - None

# None represents absence of value

empty_value = None

print(empty_value is None) # True

🔄 Collection Literals

# List literal

my_list = [1, 2, 3, 'Python']

# Dictionary literal

my_dict = {'name': 'Python', 'version': 3.10}

# Tuple literal

my_tuple = (1, 2, 'Python')

# Set literal

my_set = {1, 2, 3}

Interview Note: Understanding literals is fundamental to Python programming and shows your grasp of basic syntax.

7️⃣ Explain Python Functions

Functions in Python are blocks of reusable code designed to perform a specific task, promoting code reusability and modularity.

Types of Functions in Python

1️⃣ Built-in Functions

These are pre-defined functions that come with Python:

# Examples of built-in functions

length = len("Python") # Returns 6

maximum = max(10, 20, 30) # Returns 30

numbers = list(range(5)) # Returns [0, 1, 2, 3, 4]

2️⃣ User-defined Functions

Functions created by the programmer:

# Simple user-defined function

def greet(name):

"""This function greets the person passed in as a parameter"""

return f"Hello, {name}!"

# Function with default parameter

def power(base, exponent=2):

"""Returns base raised to exponent power"""

return base ** exponent

# Function with multiple return values

def statistics(numbers):

"""Returns min, max and average of numbers"""

return min(numbers), max(numbers), sum(numbers)/len(numbers)

3️⃣ Anonymous (Lambda) Functions

Compact, one-line functions without a formal definition:

# Lambda function for squaring a number

square = lambda x: x**2

# Using lambda with map

numbers = [1, 2, 3, 4]

squared = list(map(lambda x: x**2, numbers)) # [1, 4, 9, 16]

Function Arguments

Argument Type	Description	Example
Required	Must be provided	def add(a, b):
Default	Optional with default values	def greet(name="Guest"):
Variable Length	Accept multiple values	def sum(*args):
Keyword	Named parameters	def profile(**kwargs):

Interview Tip: Be prepared to write functions demonstrating different parameter types and return patterns during technical interviews.

8) What is zip() function in Python?

Python zip() function returns a zip object, which maps a similar index of multiple

containers. It takes an iterable, convert into iterator and aggregates the elements

based on iterables passed. It returns an iterator of tuples.

Signature

1. zip(iterator1, iterator2, iterator3 ...)

Parameters

iterator1, iterator2, iterator3: These are iterator objects that are joined together.

Return

It returns an iterator from two or more iterators.

Note: If the given lists are of different lengths, zip stops generating tuples when the first

list ends. It means two lists are having 3, and 5 lengths will create a 3-tuple.

9) What is Python's parameter passing mechanism?

There are two parameters passing mechanism in Python:

o Pass by references

o Pass by value

By default, all the parameters (arguments) are passed "by reference" to the functions.

Thus, if you change the value of the parameter within a function, the change is

reflected in the calling function as well. It indicates the original variable. For example,

if a variable is declared as a = 10, and passed to a function where it's value is modified

to a = 20. Both the variables denote to the same value.

The pass by value is that whenever we pass the arguments to the function only values

pass to the function, no reference passes to the function. It makes it immutable that

means not changeable. Both variables hold the different values, and original value

persists even after modifying in the function.

Python has a default argument concept which helps to call a method using an arbitrary

number of arguments.

10) How to overload constructors or methods in Python?

Python's constructor: _init__ () is the first method of a class. Whenever we try to

instantiate an object __init__() is automatically invoked by python to initialize members

of an object. We can't overload constructors or methods in Python. It shows an error

if we try to overload.

Example:

1. class student:
2. def __init__(self, name):
3. self.name = name
4. def __init__(self, name, email):
5. self.name = name
6. self.email = email
7.
8. # This line will generate an error
9. #st = student("suneetha")
10.
11. # This line will call the second constructor
12. st = student("suneetha", "suneetha@gmail.com")
13. print("Name: ", st.name)
14. print("Email id: ", st.email)

Output:

Name: suneetha

Email id: suneetha@gmail.com

11) What is the difference between remove() function and del

statement?

The user can use the remove() function to delete a specific object in the list.

Example:

1. list_1 = [ 3, 5, 7, 3, 9, 3 ]

2. print(list_1)

3. list_1.remove(3)

4. print("After removal: ", list_1)

Output:

[3, 5, 7, 3, 9, 3]

After removal: [5, 7, 3, 9, 3]

If you want to delete an object at a specific location (index) in the list, you can either

use del or pop.

Example:

1. list_1 = [ 3, 5, 7, 3, 9, 3 ]

2. print(list_1)

3. del list_1[2]

4. print("After deleting: ", list_1)

Output:

[3, 5, 7, 3, 9, 3]

After deleting: [3, 5, 3, 9, 3]

Note: You don't need to import any extra module to use these functions for removing an

element from the list.

We cannot use these methods with a tuple because the tuple is different from the list.

12) What is swapcase() function in the Python?

It is a string's function which converts all uppercase characters into lowercase and vice

versa. It is used to alter the existing case of the string. This method creates a copy of

the string which contains all the characters in the swap case. If the string is in lowercase,

it generates a small case string and vice versa. It automatically ignores all the nonalphabetic characters. See an example below.

Example:

1. string = "IT IS IN LOWERCASE."

2. print(string.swapcase())

4. string = "it is in uppercase."

5. print(string.swapcase())

Output:

it is in lowercase.

IT IS IN UPPERCASE.

13) How to remove whitespaces from a string in Python?

To remove the whitespaces and trailing spaces from the string, Python providies

strip([str]) built-in function. This function returns a copy of the string after removing

whitespaces if present. Otherwise returns original string.

Example:

1. string = " javatpoint "

2. string2 = " javatpoint "

3. string3 = " javatpoint"

4. print(string)

5. print(string2)

6. print(string3)

7. print("After stripping all have placed in a sequence:")

8. print(string.strip())

9. print(string2.strip())

10. print(string3.strip())

Output:

javatpoint

After stripping all have placed in a sequence:

Javatpoint

javatpoint

14) How to remove leading whitespaces from a string in the

Python?

To remove leading characters from a string, we can use lstrip() function. It is Python

string function which takes an optional char type parameter. If a parameter is provided,

it removes the character. Otherwise, it removes all the leading spaces from the string.

Example:

1. string = " javatpoint "

2. string2 = " javatpoint "

3. print(string)

4. print(string2)

5. print("After stripping all leading whitespaces:")

6. print(string.lstrip())

7. print(string2.lstrip())

Output:

javatpoint

After stripping all leading whitespaces:

javatpoint

After stripping, all the whitespaces are removed, and now the string looks like the

below:

15) Why do we use join() function in Python?

The join() is defined as a string method which returns a string value. It is concatenated

with the elements of an iterable. It provides a flexible way to concatenate the strings.

See an example below.

Example:

1. str = "Rohan"

2. str2 = "ab"

3. # Calling function

4. str2 = str.join(str2)

5. # Displaying result

6. print(str2)

Output:

aRohanb

16) Give an example of shuffle() method?

This method shuffles the given string or an array. It randomizes the items in the array.

This method is present in the random module. So, we need to import it and then we

can call the function. It shuffles elements each time when the function calls and

produces different output.

Example:

1. # import the random module

2. import random

3. # declare a list

4. sample_list1 = ['Z', 'Y', 'X', 'W', 'V', 'U']

5. print("Original LIST1: ")

6. print(sample_list1)

7. # first shuffle

8. random.shuffle(sample_list1)

9. print("\nAfter the first shuffle of LIST1: ")

10. print(sample_list1)

11. # second shuffle

12. random.shuffle(sample_list1)

13. print("\nAfter the second shuffle of LIST1: ")

14. print(sample_list1)

Output:

Original LIST1:

['Z', 'Y', 'X', 'W', 'V', 'U']

After the first shuffle of LIST1:

['V', 'U', 'W', 'X', 'Y', 'Z']

After the second shuffle of LIST1:

['Z', 'Y', 'X', 'U', 'V', 'W']

17) What is the use of break statement?

The break statement is used to terminate the execution of the current loop. Break

always breaks the current execution and transfer control to outside the current block.

If the block is in a loop, it exits from the loop, and if the break is in a nested loop, it

exits from the innermost loop.

Example:

1. list_1 = ['X', 'Y', 'Z']

2. list_2 = [11, 22, 33]

3. for i in list_1:

4. for j in list_2:

5. print(i, j)

6. if i == 'Y' and j == 33:

7. print('BREAK')

8. break

9. else:

10. continue

11. break

Output:

X 11

X 22

X 33

Y 11

Y 22

Y 33

BREAK

Python Break statement flowchart.

18) What is tuple in Python?

A tuple is a built-in data collection type. It allows us to store values in a sequence. It is

immutable, so no change is reflected in the original data. It uses () brackets rather than

[] square brackets to create a tuple. We cannot remove any element but can find in the

tuple. We can use indexing to get elements. It also allows traversing elements in

reverse order by using negative indexing. Tuple supports various methods like max(),

sum(), sorted(), Len() etc.

To create a tuple, we can declare it as below.

Example:

1. # Declaring tuple

2. tup = (2,4,6,8)

3. # Displaying value

4. print(tup)

6. # Displaying Single value

7. print(tup[2])

Output:

(2, 4, 6, 8)

It is immutable. So updating tuple will lead to an error.

Example:

1. # Declaring tuple

2. tup = (2,4,6,8)

3. # Displaying value

4. print(tup)

6. # Displaying Single value

7. print(tup[2])

9. # Updating by assigning new value

10. tup[2]=22

11. # Displaying Single value

12. print(tup[2])

Output:

tup[2]=22

TypeError: 'tuple' object does not support item assignment

(2, 4, 6, 8)

19) Which are the file related libraries/modules in Python?

The Python provides libraries/modules that enable you to manipulate text files and

binary files on the file system. It helps to create files, update their contents, copy, and

delete files. The libraries are os, os.path, and shutil.

Here, os and os.path - modules include a function for accessing the filesystem

while shutil - module enables you to copy and delete the files.

20) What are the different file processing modes supported by

Python?

Python provides four modes to open files. The read-only (r), write-only (w), read-write

(rw) and append mode (a). 'r' is used to open a file in read-only mode, 'w' is used to

open a file in write-only mode, 'rw' is used to open in reading and write mode, 'a' is

used to open a file in append mode. If the mode is not specified, by default file opens

in read-only mode.

o Read-only mode (r): Open a file for reading. It is the default mode.

o Write-only mode (w): Open a file for writing. If the file contains data, data would be

lost. Other a new file is created.

o Read-Write mode (rw): Open a file for reading, write mode. It means updating mode.

o Append mode (a): Open for writing, append to the end of the file, if the file exists.

21) What is an operator in Python?

An operator is a particular symbol which is used on some values and produces an

output as a result. An operator works on operands. Operands are numeric literals or

variables which hold some values. Operators can be unary, binary or ternary. An

operator which requires a single operand known as a unary operator, which require

two operands known as a binary operator and which require three operands is

called ternary operator.

Example:

1. # Unary Operator

2. A = 12

3. B = -(A)

4. print (B)

5. # Binary Operator

6. A = 12

7. B = 13

8. print (A + B)

9. print (B * A)

10. #Ternary Operator

11. A = 12

12. B = 13

13. min = A if A < B else B

14.

15. print(min)

Output:

# Unary Operator

-12

# Binary Operator

156

# Ternary Operator

22) What are the different types of operators in Python?

Python uses a rich set of operators to perform a variety of operations. Some individual

operators like membership and identity operators are not so familiar but allow to

perform operations.

o Arithmetic OperatorsRelational Operators

o Assignment Operators

o Logical Operators

o Membership Operators

o Identity Operators

o Bitwise Operators

Arithmetic operators perform basic arithmetic operations. For example "+" is used to

add and "?" is used for subtraction.

Example:

1. # Adding two values

2. print(12+23)

3. # Subtracting two values

4. print(12-23)

5. # Multiplying two values

6. print(12*23)

7. # Dividing two values

8. print(12/23)

Output:

-11

276

0.5217391304347826

Relational Operators are used to comparing the values. These operators test the

conditions and then returns a boolean value either True or False.

# Examples of Relational Operators

Example:

1. a, b = 10, 12

2. print(a==b) # False

3. print(a

4. print(a<=b) # True

5. print(a!=b) # True

Output:

False

True

Assignment operators are used to assigning values to the variables. See the examples

below.

Example:

1. # Examples of Assignment operators

2. a=12

3. print(a) # 12

4. a += 2

5. print(a) # 14

6. a -= 2

7. print(a) # 12

8. a *=2

9. print(a) # 24

10. a **=2

11. print(a) # 576

Output:

576

Logical operators are used to performing logical operations like And, Or, and Not.

See the example below.

Example:

1. # Logical operator examples

2. a = True

3. b = False

4. print(a and b) # False

5. print(a or b) # True

6. print(not b) # True

Output:

False

True

Membership operators are used to checking whether an element is a member of the

sequence (list, dictionary, tuples) or not. Python uses two membership operators in

and not in operators to check element presence. See an example.

Example:

1. # Membership operators examples

2. list = [2,4,6,7,3,4]

3. print(5 in list) # False

4. cities = ("india","delhi")

5. print("tokyo" not in cities) #True

Output:

False

True

Identity Operators (is and is not) both are used to check two values or variable which

are located on the same part of the memory. Two variables that are equal does not

imply that they are identical. See the following examples.

Example:

1. # Identity operator example

2. a = 10

3. b = 12

4. print(a is b) # False

5. print(a is not b) # True

Output:

False

True

Bitwise Operators are used to performing operations over the bits. The binary

operators (&, |, OR) work on bits. See the example below.

Example:

1. # Identity operator example

2. a = 10

3. b = 12

4. print(a & b) # 8

5. print(a | b) # 14

6. print(a ^ b) # 6

7. print(~a) # -11

Output:

-11

23) How to create a Unicode string in Python?

In Python 3, the old Unicode type has replaced by "str" type, and the string is treated

as Unicode by default. We can make a string in Unicode by using art.title.encode("utf8") function.

Example:

1. unicode_1 = ("\u0123", "\u2665", "\U0001f638", "\u265E", "\u265F", "\u2168")

2. print (unicode_1)

Output:

unicode_1: ('ģ', '♥', '😸', '♞', '♟', 'Ⅸ')

24) is Python interpreted language?

Python is an interpreted language. The Python language program runs directly from

the source code. It converts the source code into an intermediate language code,

which is again translated into machine language that has to be executed.

Unlike Java or C, Python does not require compilation before execution.

25) How is memory managed in Python?

Memory is managed in Python in the following ways:

o Memory management in python is managed by Python private heap space. All Python

objects and data structures are located in a private heap. The programmer does not

have access to this private heap. The python interpreter takes care of this instead.

o The allocation of heap space for Python objects is done by Python's memory manager.

The core API gives access to some tools for the programmer to code.

o Python also has an inbuilt garbage collector, which recycles all the unused memory

and so that it can be made available to the heap space.

26) What is the Python decorator?

Decorators are very powerful and a useful tool in Python that allows the programmers

to add functionality to an existing code. This is also called metaprogramming because

a part of the program tries to modify another part of the program at compile time. It

allows the user to wrap another function to extend the behaviour of the wrapped

function, without permanently modifying it.

Example:

1. def function_is_called():

2. def function_is_returned():

3. print("JavaTpoint")

4. return function_is_returned

5. new_1 = function_is_called()

6. # Outputs "JavaTpoint"

7. new_1()

Output:

JavaTpoint

Functions vs. Decorators

A function is a block of code that performs a specific task whereas a decorator is a

function that modifies other functions.

27) What are the rules for a local and global variable in Python?

Global Variables:

o Variables declared outside a function or in global space are called global variables.

o If a variable is ever assigned a new value inside the function, the variable is implicitly

local, and we need to declare it as 'global' explicitly. To make a variable globally, we

need to declare it by using global keyword.

o Global variables are accessible anywhere in the program, and any function can access

and modify its value.

Example:

1. A = "JavaTpoint"

2. def my_function():

3. print(A)

4. my_function()

Output:

JavaTpoint

Local Variables:

o Any variable declared inside a function is known as a local variable. This variable is

present in the local space and not in the global space.

o If a variable is assigned a new value anywhere within the function's body, it's assumed

to be a local.

o Local variables are accessible within local body only.

Example:

1. def my_function2():

2. K = "JavaTpoint Local"

3. print(K)

4. my_function2()

Output:

JavaTpoint Local

28) What is the namespace in Python?

The namespace is a fundamental idea to structure and organize the code that is more

useful in large projects. However, it could be a bit difficult concept to grasp if you're

new to programming. Hence, we tried to make namespaces just a little easier to

understand.

A namespace is defined as a simple system to control the names in a program. It

ensures that names are unique and won't lead to any conflict.

Also, Python implements namespaces in the form of dictionaries and maintains nameto-object mapping where names act as keys and the objects as values.

29) What are iterators in Python?

In Python, iterators are used to iterate a group of elements, containers like a list.

Iterators are the collection of items, and it can be a list, tuple, or a dictionary. Python

iterator implements __itr__ and next() method to iterate the stored elements. In Python,

we generally use loops to iterate over the collections (list, tuple).

In simple words: Iterators are objects which can be traversed though or iterated upon.

30) What is a generator in Python?

In Python, the generator is a way that specifies how to implement iterators. It is a

normal function except that it yields expression in the function. It does not implements

__itr__ and next() method and reduce other overheads as well.

If a function contains at least a yield statement, it becomes a generator. The yield

keyword pauses the current execution by saving its states and then resume from the

same when required.

31) What is slicing in Python?

Slicing is a mechanism used to select a range of items from sequence type like list,

tuple, and string. It is beneficial and easy to get elements from a range by using slice

way. It requires a : (colon) which separates the start and end index of the field. All the

data collection types List or tuple allows us to use slicing to fetch elements. Although

we can get elements by specifying an index, we get only single element whereas using

slicing we can get a group of elements.

Example:

1. Q = "JavaTpoint, Python Interview Questions!"

2. print(Q[2:25])

Output:

vaTpoint, Python Interv

32) What is a dictionary in Python?

The Python dictionary is a built-in data type. It defines a one-to-one relationship

between keys and values. Dictionaries contain a pair of keys and their corresponding

values. It stores elements in key and value pairs. The keys are unique whereas values

can be duplicate. The key accesses the dictionary elements.

Keys index dictionaries.

Example:

The following example contains some keys Country Hero & Cartoon. Their

corresponding values are India, Modi, and Suneetha respectively.

1. dict = {'Country': 'India', 'Hero': 'Modi', 'Cartoon': 'Suneetha '}

2. print ("Country: ", dict['Country'])

3. print ("Hero: ", dict['Hero'])

4. print ("Cartoon: ", dict['Cartoon'])

Output:

Country: India

Hero: Modi

Cartoon: Suneetha

33) What is Pass in Python?

Pass specifies a Python statement without operations. It is a placeholder in a

compound statement. If we want to create an empty class or functions, the pass

keyword helps to pass the control without error.

Example:

1. class Student:

2. pass # Passing class

3. class Student:

4. def info():

5. pass # Passing function

34) Explain docstring in Python?

The Python docstring is a string literal that occurs as the first statement in a module,

function, class, or method definition. It provides a convenient way to associate the

documentation.

String literals occurring immediately after a simple assignment at the top are called

"attribute docstrings".

String literals occurring immediately after another docstring are called "additional

docstrings".

Python uses triple quotes to create docstrings even though the string fits on one line.

Docstring phrase ends with a period (.) and can be multiple lines. It may consist of

spaces and other special chars.

Example:

1. # One-line docstrings

2. def hello():

3. """A function to greet."""

4. return "hello"

35) What is a negative index in Python and why are they used?

The sequences in Python are indexed and it consists of the positive as well as negative

numbers. The numbers that are positive uses '0' that is uses as first index and '1' as the

second index and the process go on like that.

The index for the negative number starts from '-1' that represents the last index in the

sequence and '-2' as the penultimate index and the sequence carries forward like the

positive number.

The negative index is used to remove any new-line spaces from the string and allow

the string to except the last character that is given as S[:-1]. The negative index is also

used to show the index to represent the string in correct order.

36) What is pickling and unpickling in Python?

The Python pickle is defined as a module which accepts any Python object and

converts it into a string representation. It dumps the Python object into a file using the

dump function; this process is called Pickling.

The process of retrieving the original Python objects from the stored string

representation is called as Unpickling.

37) Which programming language is a good choice between

Java and Python?

Java and Python both are object-oriented programming languages. Let's compare

both on some criteria given below:

Criteria Java Python

Ease of use Good Very Good

Coding Speed Average Excellent

Data types Static type Dynamic type

Data Science and Machine learning application Average Very Good

38) What is the usage of help() and dir() function in Python?

Help() and dir() both functions are accessible from the Python interpreter and used for

viewing a consolidated dump of built-in functions.

Help() function: The help() function is used to display the documentation string and

also facilitates us to see the help related to modules, keywords, and attributes.

Dir() function: The dir() function is used to display the defined symbols.

39) What are the differences between Python 2.x and Python

3.x?

Python 2.x is an older version of Python. Python 3.x is newer and latest version. Python

2.x is legacy now. Python 3.x is the present and future of this language.

The most visible difference between Python2 and Python3 is in print statement

(function). In Python 2, it looks like print "Hello", and in Python 3, it is print ("Hello").

String in Python2 is ASCII implicitly, and in Python3 it is Unicode.

The xrange() method has removed from Python 3 version. A new keyword as is

introduced in Error handling.

40) How Python does Compile-time and Run-time code

checking?

In Python, some amount of coding is done at compile time, but most of the checking

such as type, name, etc. are postponed until code execution. Consequently, if the

Python code references a user-defined function that does not exist, the code will

compile successfully. The Python code will fail only with an exception when the code

execution path does not exist.

41) What is the shortest method to open a text file and display

its content?

The shortest way to open a text file is by using "with" command in the following

manner:

Example:

1. with open("FILE NAME", "r") as fp:

2. fileData = fp.read()

3. # To print the contents of the file

4. print(fileData)

Output:

"The data of the file will be printed."

42) What is the usage of enumerate () function in Python?

The enumerate() function is used to iterate through the sequence and retrieve the

index position and its corresponding value at the same time.

Example:

1. list_1 = ["A","B","C"]

2. s_1 = "Javatpoint"

3. # creating enumerate objects

4. object_1 = enumerate(list_1)

5. object_2 = enumerate(s_1)

7. print ("Return type:",type(object_1))

8. print (list(enumerate(list_1)))

9. print (list(enumerate(s_1)))

Output:

Return type:

[(0, 'A'), (1, 'B'), (2, 'C')]

[(0, 'J'), (1, 'a'), (2, 'v'), (3, 'a'), (4, 't'), (5, 'p'), (6, 'o'), (7,

'i'), (8, 'n'), (9, 't')]

43) Give the output of this example: A[3] if A=[1,4,6,7,9,66,4,94].

Since indexing starts from zero, an element present at 3rd index is 7. So, the output is

44) What is type conversion in Python?

Type conversion refers to the conversion of one data type iinto another.

int() - converts any data type into integer type

float() - converts any data type into float type

ord() - converts characters into integer

hex() - converts integers to hexadecimal

oct() - converts integer to octal

tuple() - This function is used to convert to a tuple.

set() - This function returns the type after converting to set.

list() - This function is used to convert any data type to a list type.

dict() - This function is used to convert a tuple of order (key,value) into a dictionary.

str() - Used to convert integer into a string.

complex(real,imag) - This functionconverts real numbers to complex(real,imag)

number.

45) How to send an email in Python Language?

To send an email, Python provides smtplib and email modules. Import these modules

into the created mail script and send mail by authenticating a user.

It has a method SMTP(smtp-server, port). It requires two parameters to establish SMTP

connection.

A simple example to send an email is given below.

Example:

1. import smtplib

2. # Calling SMTP

3. s = smtplib.SMTP('smtp.gmail.com', 587)

4. # TLS for network security

5. s.starttls()

6. # User email Authentication

7. s.login("sender@email_id", "sender_email_id_password")

8. # Message to be sent

9. message = "Message_sender_need_to_send"

10. # Sending the mail

11. s.sendmail("sender@email_id ", "receiver@email_id", message)

46) What is the difference between Python Arrays and lists?

Arrays and lists, in Python, have the same way of storing data. But, arrays can hold only

a single data type elements whereas lists can hold any data type elements.

Example:

1. import array as arr

2. User_Array = arr.array('i', [1,2,3,4])

3. User_list = [1, 'abc', 1.20]

4. print (User_Array)

5. print (User_list)

Output:

array('i', [1, 2, 3, 4])

[1, 'abc', 1.2]

47) What is lambda function in Python?

The anonymous function in python is a function that is defined without a name. The

normal functions are defined using a keyword "def", whereas, the anonymous

functions are defined using the lambda function. The anonymous functions are also

called as lambda functions.

48) Why do lambda forms in Python not have the statements?

Lambda forms in Python does not have the statement because it is used to make the

new function object and return them in runtime.

49) What are functions in Python?

A function is a block of code which is executed only when it is called. To define a

Python function, the def keyword is used.

Example:

1. def New_func():

2. print ("Hi, Welcome to JavaTpoint")

3. New_func() #calling the function

Output:

Hi, Welcome to JavaTpoint

50) What is __init__?

The __init__ is a method or constructor in Python. This method is automatically called

to allocate memory when a new object/ instance of a class is created. All classes have

the __init__ method.

Example:

1. class Employee_1:

2. def __init__(self, name, age,salary):

3. self.name = name

4. self.age = age

5. self.salary = 20000

6. E_1 = Employee_1("pqr", 20, 25000)

7. # E1 is the instance of class Employee.

8. #__init__ allocates memory for E1.

9. print(E_1.name)

10. print(E_1.age)

11. print(E_1.salary)

Output:

pqr

25000

51) What is self in Python?

Self is an instance or an object of a class. In Python, this is explicitly included as the

first parameter. However, this is not the case in Java where it's optional. It helps to

differentiate between the methods and attributes of a class with local variables.

The self-variable in the init method refers to the newly created object while in other

methods, it refers to the object whose method was called.

52) How can you generate random numbers in Python?

Random module is the standard module that is used to generate a random number.

The method is defined as:

1. import random

2. random.random

The statement random.random() method return the floating point number that is in

the range of [0, 1). The function generates random float numbers. The methods that

are used with the random class are the bound methods of the hidden instances. The

instances of the Random can be done to show the multi-threading programs that

creates a different instance of individual threads. The other random generators that

are used in this are:

randrange(a, b): it chooses an integer and define the range in-between [a, b). It

returns the elements by selecting it randomly from the range that is specified. It

doesn't build a range object.

uniform(a, b): it chooses a floating point number that is defined in the range of

[a,b).Iyt returns the floating point number

normalvariate(mean, sdev): it is used for the normal distribution where the mu is a

mean and the sdev is a sigma that is used for standard deviation.

The Random class that is used and instantiated creates independent multiple random

number generators.

53) What is PYTHONPATH?

PYTHONPATH is an environment variable which is used when a module is imported.

Whenever a module is imported, PYTHONPATH is also looked up to check for the

presence of the imported modules in various directories. The interpreter uses it to

determine which module to load.

54) What are python modules? Name some commonly used

built-in modules in Python?

Python modules are files containing Python code. This code can either be functions

classes or variables. A Python module is a .py file containing executable code.

Some of the commonly used built-in modules are:

o os
o sys
o math
o random
o data time
o JSON

55) What is the difference between range & xrange?

For the most part, xrange and range are the exact same in terms of functionality. They

both provide a way to generate a list of integers for you to use, however you please.

The only difference is that range returns a Python list object and x range returns an

xrange object.

This means that xrange doesn't actually generate a static list at run-time like range

does. It creates the values as you need them with a special technique called yielding.

This technique is used with a type of object known as generators. That means that if

you have a really gigantic range you'd like to generate a list for, say one billion, xrange

is the function to use.

This is especially true if you have a really memory sensitive system such as a cell phone

that you are working with, as range will use as much memory as it can to create your

array of integers, which can result in a Memory Error and crash your program. It's a

memory hungry beast.

56) What advantages do NumPy arrays offer over (nested)

Python lists?

o Python's lists are efficient general-purpose containers. They support (fairly) efficient

insertion, deletion, appending, and concatenation, and Python's list comprehensions

make them easy to construct and manipulate.

o They have certain limitations: they don't support "vectorized" operations like

elementwise addition and multiplication, and the fact that they can contain objects of

differing types mean that Python must store type information for every element, and

must execute type dispatching code when operating on each element.

o NumPy is not just more efficient; it is also more convenient. We get a lot of vector and

matrix operations for free, which sometimes allow one to avoid unnecessary work. And

they are also efficiently implemented.

o NumPy array is faster and we get a lot built in with NumPy, FFTs, convolutions, fast

searching, basic statistics, linear algebra, histograms, etc.

57) Mention what the Django templates consist of.

The template is a simple text file. It can create any text-based format like XML, CSV,

HTML, etc. A template contains variables that get replaced with values when the

template is evaluated and tags (% tag %) that control the logic of the template.

58) Explain the use of session in Django framework?

Django provides a session that lets the user store and retrieve data on a per-site-visitor

basis. Django abstracts the process of sending and receiving cookies, by placing a

session ID cookie on the client side, and storing all the related data on the server side.

So, the data itself is not stored client side. This is good from a security perspective.

59) What data type would you use to store customer names and locations in Python?

For storing customer data with names and locations, a dictionary is the most appropriate data structure:

customers = {

"John Smith": "New York",

"Emily Johnson": "Chicago",

"Michael Brown": "Los Angeles",

"Sarah Davis": "Miami"

}

# Accessing a customer's location

print(customers["John Smith"]) # Output: New York

# Adding a new customer

customers["David Wilson"] = "Seattle"

# Updating a customer's location

customers["Emily Johnson"] = "Boston"

For more complex customer data, you might use nested dictionaries:

customers = {

"JD001": {

"name": "John Smith",

"location": "New York",

"phone": "555-123-4567",

"email": "john@example.com"

"EM002": {

"name": "Emily Johnson",

"location": "Chicago",

"phone": "555-987-6543",

"email": "emily@example.com"

}

Top 10 Python Interview Tips

1. Master the Fundamentals: Ensure you have strong understanding of core Python concepts like data structures, functions, and OOP principles.

2. Practice Coding Without IDE: Be comfortable writing code without auto-completion and syntax highlighting.

3. Time Complexity: Know the Big O notation for common operations on Python data structures and algorithms.

4. Prepare for Live Coding: Practice explaining your thought process while coding.

5. Review Standard Library: Be familiar with commonly used modules like collections, itertools, and functools.

6. Understand Python's Unique Features: Know Python-specific concepts like list comprehensions, generators, decorators, and context managers.

7. Prepare Concise Examples: Have clear, succinct examples ready for concepts like closures, decorators, etc.

8. Be Ready to Discuss Trade-offs: Know when to use different data structures and approaches.

9. Brush Up on Recent Changes: Be aware of new features in recent Python versions.

10.Review Your Projects: Be prepared to discuss any Python projects listed on your resume in detail.

Final Thoughts

Remember that success in a Python interview depends not just on technical knowledge but also on how you communicate your thought process. When answering questions:

1. Clarify the question if needed before jumping into an answer

2. Communicate your approach before coding

3. Think about edge cases and potential optimizations

4. Explain your code as you write it

5. Test your solution with examples, even on a whiteboard

Python's philosophy emphasizes readability and simplicity, so strive to write clean, Pythonic code during your interview.

Good luck on your Python interview journey!

References and Further Reading

Thank you for reading!

Your time and support mean a lot. If you enjoyed this post or have suggestions, ideas, or questions, I’d love to hear from you. Feel free to leave a comment, share your thoughts, or connect with me. Don’t forget to follow the blog for more inspiring content!

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Thursday, April 24, 2025

Top Python 60 Interviews in 2025: Top Questions & Answers

Python Interview Questions

1️⃣ What is Python?

2️⃣ Why Python?

3️⃣ What are the applications of Python?

Web Development

Data Science & ML

Automation & Scripting

Other Application Areas

4️⃣ What are the advantages of Python?

Key Advantages of Python

⚙️ Interpreted Language

🔓 Free and Open Source

🧩 Extensible and Embeddable

🎯 Object-Oriented

📊 Rich Data Structures

📖 Readability

🌉 Cross-Platform

5️⃣ What is PEP 8?

Key PEP 8 Recommendations:

6️⃣ What do you mean by Python literals?

Types of Python Literals

📝 String Literals

🔢 Numeric Literals

✅ Boolean Literals

🚫 Special Literal - None

🔄 Collection Literals

7️⃣ Explain Python Functions

Types of Functions in Python

1️⃣ Built-in Functions

2️⃣ User-defined Functions

3️⃣ Anonymous (Lambda) Functions

Function Arguments

Thank you for reading!

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