Top 10+ Python Interview Questions for Freshers (2025)

1. What is Python? Explain Some Key Applications of Python in Technology

Python is a dynamic and versatile high-level programming language introduced by Guido van Rossum in 1991. Maintained by the Python Software Foundation, it stands out for its simplicity and readability, enabling developers to write clean and efficient code with fewer lines. Its adaptability has made it a favorite in various domains.

Key Applications of Python:

1. System Automation: Automating mundane tasks and managing system operations effortlessly.
2. Web Development: Building dynamic and scalable websites using popular frameworks like Django and Flask.
3. Game Creation: Designing interactive games with libraries such as Pygame.
4. Software Engineering: Developing powerful software tools and applications.
5. Data Science and Mathematics: Tackling complex calculations and data analysis with tools like Pandas and NumPy.

Python’s widespread use in technology has cemented its place as a top choice for developers worldwide.

2. What Are the Advantages of Using Python as a Tool in Today’s Tech Landscape?

Python offers numerous benefits, making it a preferred language across industries and applications. Here are some key advantages:

Benefits of Python:

1. Object-Oriented Language: Encourages modularity and code reuse through object-oriented programming (OOP) principles.
2. High-Level Language: Simplifies complex programming tasks by abstracting underlying hardware details.
3. Dynamically Typed: Allows flexible coding as variables are determined at runtime, reducing the need for explicit declarations.
4. Rich Machine Learning Libraries: Offers extensive support for AI and ML through libraries like TensorFlow, Keras, and PyTorch.
5. Third-Party Modules: Enhances functionality with a vast ecosystem of readily available modules and packages.
6. Open Source: Backed by a thriving community, ensuring continuous updates and resources.
7. Portable and Interactive: Enables cross-platform compatibility and supports interactive testing and debugging.
8. Versatility Across OS: Seamlessly operates across platforms such as Windows, macOS, and Linux.

In the present scenario, Python’s adaptability and extensive library support have made it a crucial tool for emerging fields like data science, web development, and artificial intelligence.

3. Is Python a compiled language or an interpreted language?

Python is both a compiled and interpreted language. When you run Python code, it is first compiled into bytecode, which is a platform-independent representation of the code. This bytecode is then executed by the Python Virtual Machine (PVM), which interprets the bytecode and converts it into machine-specific instructions based on your operating system and hardware.

In simple terms:

1. Python compiles your code into bytecode for efficiency.
2. The PVM interprets and runs the bytecode on your machine.

This process ensures Python’s flexibility and platform independence. It’s one of the most common Python Interview Questions for Freshers asked during interviews.

4. What does the ‘#’ symbol do in Python?

In Python, the # symbol is used to add comments. Anything written after the # on the same line is ignored by the Python interpreter and is meant for the programmer to leave notes or explanations in the code.

For example:

# This is a comment, and the Python interpreter ignores it
print("Hello, world!")  # This prints a message to the console

Comments are helpful for explaining code and making it more readable, especially in larger programs.

5. What is the difference between a Mutable datatype and an Immutable datatype?

In Python, data types can be categorized as mutable or immutable based on whether their values can be changed after they are created.

• Mutable data types are those whose values can be modified after creation. This means you can change, add, or remove elements in these data types. Examples include:
  • List
  • Dictionary
  • Set
  Example: my_list = [1, 2, 3] my_list[0] = 10 # Modifying an element in the list print(my_list) # Output: [10, 2, 3]
• Immutable data types are those whose values cannot be changed after they are created. Once an object of an immutable type is assigned, it cannot be altered. Examples include:
  • String
  • Tuple
  • Integer
  Example: my_string = "Hello" my_string[0] = "h" # This will raise an error, as strings are immutable

The key difference is that mutable types can be altered, while immutable types cannot. It’s one of the most common Python Interview Questions for Freshers asked during interviews.

6. How are arguments passed by value or by reference in Python?

In Python, arguments are passed by object reference, also known as pass by assignment. This means that when you pass an argument to a function, you are actually passing a reference to the object, not a copy of the object.

However, how the object behaves inside the function depends on whether the object is mutable or immutable:

1. Mutable objects (like lists, dictionaries, or sets) can be modified within the function. Changes made to these objects will affect the original object outside the function because they reference the same memory location. Example: def modify_list(lst): lst.append(4) # Modifying the list inside the function my_list = [1, 2, 3] modify_list(my_list) print(my_list) # Output: [1, 2, 3, 4]
2. Immutable objects (like integers, floats, strings, and tuples) cannot be modified directly inside the function. When you try to change their value, Python creates a new object instead of modifying the original one. Therefore, the original object remains unchanged. Example: def modify_number(num): num = num + 1 # Reassigning a new value to the number my_num = 5 modify_number(my_num) print(my_num) # Output: 5 (original value remains unchanged)

In summary, Python’s argument passing mechanism is neither purely pass-by-value nor pass-by-reference. It is best described as pass-by-object-reference, meaning that the behavior depends on whether the object is mutable or immutable.

7. What is the difference between a Set and Dictionary?

Set:

• A set is an unordered collection of unique items in Python.
• Sets are mutable, meaning that you can add or remove items after the set is created.
• A set does not allow duplicate values and automatically removes any duplicate elements.
• Sets are typically used when you need to store a collection of unique items, without caring about the order.
• Syntax: my_set = {1, 2, 3, 4}

Dictionary:

• A dictionary is an unordered collection of key-value pairs in Python.
• Each key in a dictionary is unique, and each key is associated with a value.
• A dictionary is mutable, meaning you can add, remove, or modify key-value pairs.
• Dictionaries are useful when you need to store data in pairs (key-value), where you can look up values using their corresponding keys.
• Syntax: my_dict = {"name": "Alice", "age": 25, "city": "New York"}

Key Differences:

Feature	Set	Dictionary
Data Structure	Unordered collection of unique items	Unordered collection of key-value pairs
Syntax	{1, 2, 3}	{"key": "value"}
Duplicate Elements	Does not allow duplicates	Keys must be unique, but values can be duplicates
Data Representation	Stores individual values	Stores key-value pairs
Mutability	Mutable	Mutable
Use Case	When you need unique items	When you need to map keys to values

In summary, sets are used for storing unique, unordered items, while dictionaries are used for storing key-value pairs, where each key maps to a specific value. It’s one of the most common Python Interview Questions for Freshers asked during interviews.

8. What is List Comprehension? Give an Example.

List comprehension is a concise way to create lists in Python. It provides a syntactic sugar that allows you to generate a new list by performing operations on elements from an existing iterable (like a list, tuple, or range) in a single line of code.

It consists of an expression followed by a for loop inside square brackets [].

Syntax:

[expression for item in iterable]

• expression: The value or operation that will be included in the new list.
• for item in iterable: A loop that iterates over each element in the iterable.

Example:

Let’s create a list of square numbers from 1 to 9 using list comprehension:

# List comprehension to get square numbers from 1 to 9
squares = [i**2 for i in range(1, 10)]
print(squares)

Output:

[1, 4, 9, 16, 25, 36, 49, 64, 81]

Explanation:

In this example:

• The expression is i**2, which calculates the square of each number.
• The iterable is range(1, 10), which generates numbers from 1 to 9.
• The list comprehension generates a list of squared numbers from 1 to 9.

List comprehensions are useful for making code more readable and efficient, especially when you need to filter, map, or transform elements in an iterable.

9. What is a lambda function?

A lambda function in Python is a small, anonymous (unnamed) function that can take any number of arguments but is restricted to a single expression. Lambda functions are used primarily for short-term tasks where defining a full function is not necessary.

The syntax for defining a lambda function is:

lambda arguments: expression

• arguments: The parameters or inputs to the function.
• expression: A single statement or operation that is evaluated and returned by the function.

Example:

# Defining a lambda function that multiplies two numbers
a = lambda x, y: x * y
print(a(7, 19))

Output:

133

Explanation:

• lambda x, y: x * y defines a lambda function that takes two parameters x and y, and returns their product.
• The function is called with a(7, 19), and the result is 133.

Key Points:

• Lambda functions are anonymous (without a name).
• They can only have a single expression but can accept multiple parameters.
• They are commonly used for short, throwaway functions where defining a full function would be overkill.

Lambda functions are especially useful when you need to pass a small function as an argument to higher-order functions like map(), filter(), or sorted().

10. What is the swapcase function in Python?

The swapcase() function in Python is a string method that converts all uppercase characters to lowercase and vice versa in the string. This method doesn’t modify the original string but returns a new string with the case of all characters swapped. It is useful when you want to change the case of a string in one go.

For Example:

string = "TalentCareers"
string.swapcase()

Output:

"tALENTcAREERS"

Explanation:

• Original String: "TalentCareers"
• After applying swapcase(): The uppercase letters are converted to lowercase, and the lowercase letters are converted to uppercase.

Key Points:

• The swapcase() method does not change the original string, it returns a new string with swapped cases.
• This method is useful for formatting or altering the case of the entire string without using multiple functions.

11. What is the difference between / and // in Python?

In Python, both / and // are used for division operations, but they work differently:

• / (Division Operator): This operator performs precise division, where the result is always a floating-point number (even when the numbers are integers).
• // (Floor Division Operator): This operator performs floor division, which returns the integer part of the division result (ignores the remainder) and rounds down to the nearest whole number.

Examples:

1. Using / (Precise Division):

result = 5 / 2
print(result)  # Output: 2.5

• Explanation: The division result is a floating-point number.

2. Using // (Floor Division):

result = 5 // 2
print(result)  # Output: 2

• Explanation: The division result is an integer (the fractional part is discarded, and it rounds down to the nearest whole number).

Key Points:

• / always returns a floating-point number.
• // performs floor division and returns an integer (if both operands are integers) or a float (if one or both operands are floats), but it discards the decimal part.

12. What is pass in Python?

pass is a placeholder in Python. It is used when you need to write a block of code but don’t want to do anything yet. It doesn’t perform any operation and is typically used as a temporary placeholder.

Example:

def my_function():
    pass  # Nothing happens here

• Explanation: The pass statement allows you to leave the function or block empty without causing an error.

It’s one of the most common Python Interview Questions for Freshers asked during interviews.

13. What are Built-in data types in Python?

Python provides several built-in data types that allow you to store and manipulate different types of data. Here are the most common ones:

1. Numeric Types: Represent numbers, including:
   • Integer (int): Whole numbers (e.g., 5, 100, -23).
   • Floating-point (float): Decimal numbers (e.g., 3.14, -0.001, 2.0).
   • Boolean (bool): Represents True or False.
   • Complex (complex): Numbers with a real and imaginary part (e.g., 3 + 4j).
2. Sequence Types: Ordered collections of data:
   • String (str): A collection of characters (e.g., "hello", "Python").
   • List (list): A mutable, ordered collection of items (e.g., [1, 2, 3], ["apple", "banana"]).
   • Tuple (tuple): An immutable, ordered collection of items (e.g., (1, 2, 3), ("a", "b", "c")).
   • Range (range): Represents a sequence of numbers (e.g., range(0, 10)).
3. Mapping Type:
   • Dictionary (dict): An unordered collection of key-value pairs (e.g., {"name": "Alice", "age": 25}).
4. Set Types: Unordered collections of unique elements:
   • Set (set): A collection of unique elements (e.g., {1, 2, 3}, {"apple", "orange"}).
   • Frozenset (frozenset): An immutable version of a set.
5. Binary Types: Used for handling binary data:
   • Bytes (bytes): Immutable sequence of bytes.
   • Bytearray (bytearray): Mutable sequence of bytes.
   • Memoryview (memoryview): A view object of byte data.

These built-in data types are fundamental in Python and allow you to store and manipulate various kinds of data effectively.

14. What is slicing in Python?

Slicing in Python allows you to extract a part of a sequence like a string, list, or tuple. It is a powerful operation that lets you specify the starting point, the endpoint, and the step between elements of the sequence.

Syntax:

sequence[start:end:step]

• start: The index where slicing starts (inclusive).
• end: The index where slicing ends (exclusive).
• step: The step between each element (optional, defaults to 1).

Example:

1. String Slicing:

text = "Hello, World!"
print(text[0:5])  # Output: Hello

In this example, the string text is sliced from index 0 to 5, but it excludes the character at index 5, resulting in “Hello”.

2. List Slicing:

numbers = [1, 2, 3, 4, 5, 6]
print(numbers[1:5])  # Output: [2, 3, 4, 5]

This slices the list from index 1 to 5, excluding the element at index 5.

3. Using Step:

text = "abcdef"
print(text[::2])  # Output: ace

Here, slicing is done with a step of 2, so it picks every other character starting from index 0.

Slicing creates a new sequence from the original one, without modifying the original data. It’s one of the most common Python Interview Questions for Freshers asked during interviews.

15. What is a namespace in Python?

A namespace in Python is like a container that holds a collection of identifiers (names) and their corresponding objects (values). It helps to organize and keep track of variables, functions, and objects, ensuring that they don’t conflict with each other.

Think of it like a directory or folder where every item has a unique name. Python uses namespaces to manage scope and avoid confusion between different variables or functions that may have the same name in different areas of the program.

For example, you can have a variable x in one function and another variable x in another function without them interfering with each other. It’s one of the most common Python Interview Questions for Freshers asked during interviews.