Python Advanced Topics Interview Questions (original) (raw)

Last Updated : 26 Aug, 2025

Advanced Python refers to concepts and features that go beyond the basics of syntax, loops, and simple data structures. It focuses on deeper aspects of the language, design patterns, and performance-oriented programming.

1. How is Exceptional handling done in Python?

Exception handling in Python is done using try, except, else, and finally blocks. It allows a program to catch and handle runtime errors gracefully without crashing.

• **try: A block of code that is monitored for errors.
• **except: Executes when an error occurs in the try block.
• **finally: Executes after the try and except blocks, regardless of whether an error occurred. It’s used for cleanup tasks.

**Example: Trying to divide a number by zero will cause an exception.

Python `

n = 10 try: res = n / 0 # This will raise a ZeroDivisionError

except ZeroDivisionError: print("Can't be divided by zero!")

`

Output

Can't be divided by zero!

**Explanation: In this example, dividing number by 0 raises a **ZeroDivisionError. The try block contains the code that might cause an exception and the except block handles the exception, printing an error message instead of stopping the program.

2. What are Decorators?

Decorators are a powerful and flexible way to modify or extend the behavior of functions or methods, without changing their actual code. A decorator is essentially a function that takes another function as an argument and returns a new function with enhanced functionality.

Decorators are often used in scenarios such as logging, authentication and memorization, allowing us to add additional functionality to existing functions or methods in a clean, reusable way.

3. How do you debug a Python program?

• **Using pdb (Python Debugger): pdb is a built-in module that allows you to set breakpoints and step through the code line by line. You can start the debugger by adding import pdb; pdb.set_trace() in your code where you want to begin debugging. Python `

import pdb x = 5 pdb.set_trace() # Debugger starts here print(x)

`

**Output

> /home/repl/02c07243-5df9-4fb0-a2cd-54fe6d597c80/main.py(4)()
-> print(x)
(Pdb)

• **Using logging Module: For more advanced debugging, the logging module provides a flexible way to log messages with different severity levels (INFO, DEBUG, WARNING, ERROR, CRITICAL). Python `

import logging logging.basicConfig(level=logging.DEBUG) logging.debug("This is a debug message")

`

**Output

DEBUG:root:This is a debug message

4. What are Iterators in Python?

Iterators in Python are objects that allow traversal over a sequence of elements one at a time, without exposing the underlying structure. They implement two methods:

• **__iter__() – Returns the iterator object itself.
• **__next__() – Returns the next item in the sequence and raises StopIteration when the sequence ends. **Example: Python `

l = [1, 2, 3] it = iter(l) # this is the iterator print(next(it)) # 1

`

5. What are Generators in Python?

Generators in Python provide a simple way to create iterators. They are written like normal functions but use the yield keyword instead of return. When a function contains yield, it automatically becomes a generator function. Each time yield is called, the function’s state is saved, and execution can be resumed from the same point later. Generators follow the iterator protocol (iter and next), but unlike regular iterators, they are created automatically by using yield.

6. How is memory management done in Python?

Python uses its private heap space to manage the memory. All the objects and data structures are stored in the private heap space. Even the programmer can not access this private space as the interpreter takes care of this space. Python also has an inbuilt garbage collector, which recycles all the unused memory and frees the memory and makes it available to the heap space.

7. How to delete a file using Python?

We can delete a file using Python by following approaches:

1. Python Delete File using os. remove
2. Delete file in Python using the send2trash module

8. What is PIP?

PIP (Python Package Installer for Python) is the standard package manager for Python. It allows you to install, upgrade, and manage third-party Python libraries and packages from the Python Package Index (PyPI) or other repositories.

9. What is a zip function?

Python zip() function returns a zip object, which maps a similar index of multiple containers. It takes an iterable, converts it into an iterator and aggregates the elements based on iterables passed. It returns an iterator of tuples.

**Syntax:

_zip(*iterables)

10. What are Pickling and Unpickling?

• **Pickling: The pickle module converts any Python object into a byte stream (not a string representation). This byte stream can then be stored in a file, sent over a network, or saved for later use. The function used for pickling is pickle.dump().
• **Unpickling: The process of retrieving the original Python object from the byte stream (saved during pickling) is called unpickling. The function used for unpickling is pickle.load().

11. Write a code to display the current time?

Python `

import time print(time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()))

`

Output

2025-08-23 12:20:00

12. What are unit tests in Python?

Unit Testing is the first level of software testing where the smallest testable parts of the software are tested. This is used to validate that each unit of the software performs as designed. The unit test framework is Python’s xUnit style framework. The White Box Testing method is used for Unit testing.

13. Python Global Interpreter Lock (GIL)?

The Global Interpreter Lock (GIL) in Python is a mutex (mutual exclusion lock) that ensures only one thread executes Python bytecode at a time within a single process. This means that even in multi-threaded programs, only one thread can run Python code at once, while others wait. As a result, true parallel execution of threads is not possible for CPU-bound tasks. However, GIL does not affect multi-processing, and threads can still be useful for I/O-bound operations where tasks spend time waiting for input/output.

14. What are Function Annotations in Python?

• Function Annotation is a feature that allows you to add metadata to function parameters and return values. This way you can specify the input type of the function parameters and the return type of the value the function returns.
• Function annotations are arbitrary Python expressions that are associated with various parts of functions. These expressions are evaluated at compile time and have no life in Python’s runtime environment. Python does not attach any meaning to these annotations. They take life when interpreted by third-party libraries, for example, mypy.

15. What are Exception Groups in Python?

Exception Groups are a feature introduced in Python 3.11 that allow multiple exceptions to be grouped and raised together. They are particularly useful in concurrent or parallel programming, where multiple errors might occur simultaneously.

Key Points:

• Represented by the ExceptionGroup class.
• Can contain one or more exceptions.
• Allows handling multiple exceptions collectively using except*.

16. What is Walrus Operator?

• Walrus Operator allows you to assign a value to a variable within an expression. This can be useful when you need to use a value multiple times in a loop, but don't want to repeat the calculation.
• Walrus Operator is represented by the '****:=**' syntax and can be used in a variety of contexts including while loops and if statements.

**Note: Python versions before 3.8 doesn't support Walrus Operator.

Python `

a = [1, 2, 3, 4, 5]

while (n := len(a)) > 0: print(a.pop())

`