Most-asked Python Interview Questions for Freshers [2025 Updated]

I have made a complete list of the Top Python interview questions for freshers to help you impress the recruiters. I have stated each Python Interview Question carefully by taking help from development experts depending on what could be asked in the upcoming interviews. 

Read this section carefully and boost your opportunities of getting your dream job. This article will give you a solid understanding of Python, the most dynamic programming language.  

Let’s begin this, 

Q1. What are the most basic data types in Python?

Python have a vast range of basic data types, and they are;

• Numbers
• Lists
• Tuples
• Dictionaries
• Strings
• Sets
• Integers
• Boolean
• NoneType

Q2. Explain the benefits of using Python language.

Python language offers a range of benefits, and they are as follows;

• The simple and readable syntax of Python is easy to apply.
• This versatile language is widely used in the field of data analysis, web development and machine learning.
• This has cross-platform compatibility and is highly compatible with macOS, Windows, and Linux.
• This is a dynamically typed programming language. 
• This is an open-source language, and anybody can access it without paying any extra charges.
• It also has extensive libraries such as Pandas, NumPy, and TensorFlow to do faster development.
• This is an object-oriented programming language.
• It also offers a large community support provisioning necessary help and resources. 

These benefits make Python the most dynamic programming language for freshers as well as professionals. 

Q3. What are the different types of applications Python can be used for?

Python is used widely to create a range of applications, and they are;

• Data analysis and visualization with the integration of tools such as Pandas
• Desktop applications
• Game development
• Web applications with the integration of frameworks such as Flask and Django
• Machine learning and AI with the integration of libraries like PyTorch and TensorFlow
• Automation Scripts 
• Complex mathematics
• Software development

Q4. What are Python literals, and state the different types of literals of Python?

The term Python Literals is referred to as some constant values that showcase data in a program. Literals offer constant values straight in Python code.

There are different types of literals present in Python, and they are;

• String Literals referred to as text that is enclosed in quotes
• Numeric Literals are referred to as integers, complex numbers, and floats.
• Boolean Literals referred to False and True booleans
• Special Literals referred to None Value and Null Value
• Collection Literals are referred to as Tuples, dictionaries, sets and lists.

Q5. What is the meaning of the symbol ‘#’ in Python?

The symbol’ #’ in Python refers to the element that is applied to comment on each aspect that comes posted on the line. This is specially used in the comments for Python. The things that are written after ‘#’ can be ignored and will not be executed.

If you want to boost the readability of your codes and explanations, you must use comments.

Q6. What do you mean by Lambda Function?

The term Lambda is an anonymous and very tiny function in Python. It is highly represented with the help of the Lambda keyword and encounters any number of arguments yet offers only one specific expression. This is often used rather than the whole ‘def’ statement while a function definition is not that complicated as well as simple to understand.

These are often employed for simple and tiny operations for robust programming.

Q7. What is the difference between a dictionary and a set in Python?

The term Dictionary in Python refers to the thing that collects and stores data in the form of key-value pairs. Keys are unique, and an example of the dictionary is {“a”: 1, “b”: 2}

The term Sets stores or collects unique as well as unordered elements. An instance of Sets is {1, 2, 3}.

The significant difference between dictionaries and sets is sets store unique elements, while dictionary maps the keys to different values. 

Q8. How do you differentiate between the remove() function and the del statement?

Removes () helps in deleting all the special elements or characters by value from the specific list. 

For example, 

lst = [1, 2, 3] 

lst.remove(3) # Removes 3

The term ‘del’ statement helps you to delete any item through the index or eliminate a variable completely.

For example, 

lst = [1, 2, 3] 

del lst[2] # Deletes the item at index 2  

Q9. Can you explain split() and join() functions in Python?

The term split() function is used to split a string depending on a delimiter to a different list of strings.

On the other hand, the term join() functions in Python are used to join a variety of lists dependent on a delimiter to offer a single type of string. 

Q10. What do you mean by decorators in Python?

Functions that modify the behaviour of other different functions or processes are referred to as decorators in Python. As they act as wrappers, you can include features of both post and prior to the wrapped function runs without changing the original code. Decorators are employed highly for functions where you can demand to include specific functionality dynamically, like memoization, logging and access control. They are set up by putting the decorator’s name prior to the function definition and then employing the @ symbol.

Q11. What do you mean by Module in Python?

The term Module in Python refers to the specific file that holds definitions and statements. The name of the module starts with the suffix “.py”, which acts as the file name. Code is split into comprehensible sections employing modules. By importing code from one specific program to another specific one, they promote the reuse of code. For example, you may load the math module with ‘import math’ to employ the mathematical features or functionalities it holds in your particular program.

Q12. What is the difference between lists and tuples?

There are huge differences exist between lists and tuples. The differences are as follows;

Lists are mutable types of data, whereas tuples are immutable types of data. This means that one can change, add and remove the elements in a list, while one cannot modify or remove a Tuple after its formation.

Lists consume the highest memory as compared to Tuples. The implication of different interactions is relatively faster in Tuples as compared to lists, which is highly time consuming. For performing various operations and success in deletion and insertion, a list is highly recommended. Tuples are better for accessing the different elements. 

Tuples are defined mainly using parentheses (), while lists are defined using square brackets. 

Q13. What do you mean by the concept of conditional statements in Python?

The concept of conditional statements in Python refers to the element that enables robust decision-making in code. The prime conditional statements include elif, if, and else. Such conditional statements assess a specific condition, and if this particular condition is ‘true’, the block of code within it runs effectively.

If this is ‘false’, the program can assess further specific conditions with ‘elif’ or run another block with ‘else’. This flow of control is essential for managing different settings and offers particular responses in a program.

Q14. Differentiate Break and Continue in Python.

In Python, the flow of loops can be altered with the application of the continue and the break functions. When an offered condition is fulfilled, a break is used to end a loop earlier. Control is given to the statement that comes just post to the loop when a break occurs. On the other hand, the resume skips the code that remains the recent cycle inside the loop and continues to the following one. When you wish to keep running a loop but bypass some sections of it, this is beneficial.

Q15. What is self in Python?

In Python, the feature self stands for the example of the class that is currently in application. It is used widely to get access to the latest variables and methods of the object. It defines example attributes separate from other processes in the class or from internal variables of a similar name. In Python, the term ‘self’ is a powerful pattern other than a specific keyword. Python simply passes it when the process is called in a particular example, and it should be the initial parameter supplied to functions in a specific class.

Q16. What is Inheritance in Python?

The term Inheritance in Python refers to the basic concept in specific object-specific programming such as Python; this is where new classes are formed from pre-existing classes. The derived is known as the child class, which inherits behaviours and attributes from the most basic class referred to as the parent class. 

Inheritance enables the reusing of code, making it simpler to make and handle web applications. Along with that, the features of the parent class can be changed or extended by the child class, leading to polymorphic behaviour.

Q17. What do you mean by membership operators?

The feature membership operators in Python refer to the operators that are employed to figure out whether a value is there in the sequence, like a tuple, string or list. There are two types of membership operators: ‘in’ and ‘not in’. If the specific value comes in sequence, the operator backs the true value. If ‘true’ is returned with the not in, then the value is not presented in a specific sequence. These membership operators aid in performing specific tests perfectly, making the code easier, simpler and clearer to understand. 

Q18. What do you mean by generators in Python?

Python generators are specific functions resulting in iterators. A generator employs the output keyword to generate a sequence of specific values one at a time, in contrast to normal sequences that return just one value. The current status of the function has been stopped and can be restored each time the yield is executed. As they generate variables frequently rather than restoring them all in memory just once, generators are cost-efficient. This is extremely beneficial when handling endless sequences or huge data sets. The following value from a generator in Python can be retrieved by employing the next() function.