Top 25 Interview Questions With Answers For Python

Master your next Python interview with these 25 essential questions and detailed answers to showcase your coding skills and knowledge.

Top 25 Python Interview Questions with Answers

1. What is Python and what are its key features?

• Python is a high-level, interpreted, general-purpose programming language.
• It supports multiple programming paradigms: procedural, object-oriented, and functional.
• Features include easy syntax, dynamic typing, automatic memory management, and a vast standard library.
• It is widely used in web development, data science, automation, and AI.

2. What are Python’s data types?

• Numeric: int, float, complex
• Text: str
• Sequence: list, tuple, range
• Mapping: dict
• Set types: set, frozenset
• Boolean: bool
• Binary: bytes, bytearray, memoryview

3. What is the difference between list and tuple in Python?

A list is mutable, meaning its elements can be changed, while a tuple is immutable. Lists use square brackets [], and tuples use parentheses (). Lists are slower but more flexible. Tuples are faster and used when data should not change.

4. What is PEP 8 and why is it important?

PEP 8 is Python’s style guide for writing readable code. It covers naming conventions, indentation, spacing, and line length. Following PEP 8 ensures consistency across Python codebases. It improves readability, maintainability, and collaboration.

5. Explain the concept of Python namespaces.

• A namespace is a container that holds a mapping of names to objects.
• Types: Local, Global, Built-in, and Enclosing.
• Prevents name clashes and ensures variable names are unique within a scope.
• Managed using dictionaries internally.

6. What are *args and kwargs in Python functions?

*args allows a function to accept any number of positional arguments as a tuple. **kwargs lets it accept any number of keyword arguments as a dictionary. They provide flexibility when calling functions with dynamic input. Common in decorators and wrappers.

7. What are Python decorators?

Decorators are functions that modify the behavior of other functions or methods. They use @decorator_name syntax above a function definition. Common use cases include logging, access control, and memoization. Decorators are built on closures and higher-order functions.

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

• Shallow copy creates a new object but inserts references to the original objects.
• Deep copy creates a new object and recursively copies all nested objects.
• copy.copy() is for shallow, copy.deepcopy() is for deep copy.
• Deep copy avoids unintentional changes in nested objects

9. Explain list comprehension with an example.

• A concise way to create lists in one line.
• Syntax: [expression for item in iterable if condition]
• Example: [x*x for x in range(5) if x%2==0] results in [0, 4, 16]
• More readable and faster than using loops.

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

== checks if the values of two variables are equal, while is checks if they refer to the same object in memory. For immutable objects like numbers and strings, they may appear similar but are different operations. is is often used for identity checks. == is for logical equivalence.

11. What is the purpose of the with statement in Python?

The with statement simplifies exception handling for resource management, such as file operations. It ensures that resources are properly closed after their use. It is implemented using context managers. Common usage: with open('file.txt') as f:.

12. What is a lambda function?

• A lambda function is an anonymous function defined using the lambda keyword.
• Syntax: lambda arguments: expression
• Useful for short, throwaway functions.
• Common in functional programming and functions like map(), filter(), and sorted().

13. Explain Python’s memory management.

• Python uses reference counting and garbage collection for memory management.
• Memory is managed using private heap space.
• The gc module handles cyclic references.
• Memory allocation is done via Python memory manager and object-specific allocators.

14. What are Python generators?

Generators are functions that return an iterator using the yield keyword. Unlike regular functions, they do not store the entire sequence in memory. They are useful for handling large data streams. Each call to next() resumes where the last yield occurred.

15. Difference between Python 2 and Python 3.

• Python 3 uses print() as a function; Python 2 uses it as a statement.
• Integer division in Python 3 returns float by default.
• Unicode support is better in Python 3.
• Python 2 is deprecated since 2020; Python 3 is the future.

16. What are Python modules and packages?

• A module is a single Python file containing definitions and statements.
• A package is a collection of modules in a directory with an __init__.py file.
• Helps in code organization and reusability.
• Use import to include them in your script.

17. What is the difference between @staticmethod and @classmethod?

@staticmethod does not take the class or instance as its first argument. @classmethod takes cls as the first argument and can access class-level variables. Use staticmethod when method logic doesn’t need class data. Use classmethod when logic depends on class attributes.

18. What is the difference between mutable and immutable types in Python?

Mutable objects can be changed after creation, while immutable ones cannot. Lists, dictionaries, and sets are mutable. Strings, tuples, and integers are immutable. This affects how variables are passed and copied in functions.

19. What is the Global Interpreter Lock (GIL)?

The GIL is a mutex that allows only one thread to execute in the Python interpreter at a time. It prevents true multi-core CPU execution in CPython. This limits multithreading for CPU-bound tasks. However, it's not an issue for I/O-bound operations.

20. How does exception handling work in Python?

• Python handles exceptions using try, except, else, and finally blocks.
• try: block to test for errors.
• except: block to handle the error.
• else: runs if no error occurs.
• finally: always runs, used for cleanup.

21. What are Python’s built-in data structures?

• List: Ordered, mutable sequence.
• Tuple: Ordered, immutable sequence.
• Set: Unordered collection of unique items.
• Dictionary: Key-value pairs; mutable and unordered.
• These structures form the core of most Python applications.

22. What is the difference between Python arrays and lists?

Arrays (from the array module) are homogeneous and more memory-efficient. Lists can hold mixed data types and are more flexible. Arrays are used when numeric computation is critical. Lists are more commonly used for general-purpose storage.

23. Explain Python’s map(), filter(), and reduce() functions.

• map(): Applies a function to all items in an iterable.
• filter(): Filters items based on a condition.
• reduce(): Applies a rolling computation to items (requires functools).
• All support functional programming and operate lazily.

24. How can you manage dependencies in Python projects?

• Use requirements.txt to list packages.
• Use pip or pipenv for installation.
• Use virtual environments (venv, virtualenv) to isolate dependencies.
• Tools like poetry and conda also manage packages and environments.

25. How do you handle files in Python?

• Open a file using open(filename, mode).
• Read/write using read(), write(), readlines(), etc.
• Always close using close() or with block.
• Modes include 'r', 'w', 'a', 'rb', 'wb', etc.