Python Interview Questions For Freshers

Basic Level Questions

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

Answer: Python is a high-level, interpreted, and general-purpose programming language.

• Key Features:

  • Easy to Learn: Simple syntax, readable like English.

  • Interpreted: Code is executed line by line, which makes debugging easy.

  • Dynamically Typed: You don't need to declare variable types.

  • Free and Open-Source: Anyone can use and contribute to it.

  • Large Standard Library: Comes with pre-built modules for many tasks.

  • Portable: Code written on one OS can run on another with little to no change.

2. How is memory managed in Python?

Answer: Python uses an automatic memory management mechanism known as Garbage Collection. The Python memory manager handles a private heap space where all objects are stored. The built-in gc module identifies and deletes objects that are no longer in use (i.e., objects with zero reference count) to free up memory.

3. What are the differences between a list and a tuple?

Answer:

4. What are Python's key data structures?

Answer: The main built-in data structures are often called "Collections":

• List: Ordered, mutable collection. [1, 2, 3]

• Tuple: Ordered, immutable collection. (1, 2, 3)

• Set: Unordered, mutable collection of unique elements. {1, 2, 3}

• Dictionary (dict): Unordered collection of key-value pairs. {'key': 'value'}

5. What is PEP 8?

Answer: PEP 8 is the official Python Enhancement Proposal that provides style guidelines for writing readable and consistent Python code. It covers topics like indentation (use 4 spaces), line length (max 79 characters), naming conventions (e.g., snake_case for variables and functions), and more.

Intermediate Level Questions

6. Explain the difference between is and == in Python.

Answer:

• == is a value equality operator. It checks if the values of two objects are the same.

• is is an identity equality operator. It checks if both operands refer to the exact same object in memory (i.e., if their id() is the same).

Example:

python

list1 = [1, 2, 3]
list2 = [1, 2, 3]
list3 = list1

print(list1 == list2) # True (values are same)
print(list1 is list2) # False (different objects in memory)
print(list1 is list3) # True (same object)

7. What are list comprehensions? Give an example.

Answer: A list comprehension is a concise and readable way to create lists in a single line of code.
Syntax: [expression for item in iterable if condition]

Example: Create a list of squares for even numbers from 0 to 9.

python

# Traditional way
squares = []
for i in range(10):
    if i % 2 == 0:
        squares.append(i**2)

# Using List Comprehension
squares = [i**2 for i in range(10) if i % 2 == 0]
# Output: [0, 4, 16, 36, 64]

8. How do you handle exceptions in Python?

Answer: Exceptions are handled using try, except, else, and finally blocks.

python

try:
    # Code that might raise an exception
    result = 10 / 0
except ZeroDivisionError:
    # Handle a specific exception
    print("You can't divide by zero!")
except Exception as e:
    # Handle any other exception
    print(f"An error occurred: {e}")
else:
    # Code to run if no exception was raised
    print("Division successful!")
finally:
    # Code that always runs, used for cleanup (e.g., closing files)
    print("This always executes.")

9. What is the difference between append() and extend() for lists?

Answer:

• append(): Adds its argument as a single element to the end of the list. The length of the list increases by one.

  python

  my_list = [1, 2, 3]
  my_list.append([4, 5])
  print(my_list) # Output: [1, 2, 3, [4, 5]]

• extend(): Iterates over its argument and adds each element to the end of the list. The length of the list increases by the number of elements in the iterable.

  python

  my_list = [1, 2, 3]
  my_list.extend([4, 5])
  print(my_list) # Output: [1, 2, 3, 4, 5]

   

10. What are *args and **kwargs? When are they used?

Answer:

• *args (Non-Keyword Arguments): Allows you to pass a variable number of positional arguments to a function. Inside the function, args is a tuple.

• **kwargs (Keyword Arguments): Allows you to pass a variable number of keyword arguments (like name='Alice'). Inside the function, kwargs is a dictionary.

Example:

python

def my_function(a, *args, **kwargs):
    print(f"a: {a}")
    print(f"args: {args}") # Tuple of positional arguments
    print(f"kwargs: {kwargs}") # Dict of keyword arguments

my_function(10, 20, 30, 40, name="Bob", age=25)
# Output:
# a: 10
# args: (20, 30, 40)
# kwargs: {'name': 'Bob', 'age': 25}

11. What is the purpose of the __init__ method?

Answer: The __init__ method is a special constructor method in a Python class. It is automatically called when a new instance (object) of that class is created. Its primary purpose is to initialize the object's attributes.

Example:

python

class Dog:
    def __init__(self, name, breed):
        self.name = name   # 'self' refers to the current instance
        self.breed = breed

my_dog = Dog("Fido", "Labrador") # __init__ is called here
print(my_dog.name) # Output: Fido

12. Explain the difference between a shallow copy and a deep copy.

Answer:

• Shallow Copy: Creates a new object but doesn't create copies of the objects inside the original object. Instead, it inserts references to the nested objects. Use copy.copy().

• Deep Copy: Creates a new object and recursively adds copies of all objects found inside the original object. Use copy.deepcopy().

Example:

python

import copy

original = [[1, 2], [3, 4]]
shallow = copy.copy(original)
deep = copy.deepcopy(original)

original[0][0] = 99

print(original) # [[99, 2], [3, 4]]
print(shallow)  # [[99, 2], [3, 4]] (Nested list is changed!)
print(deep)     # [[1, 2], [3, 4]] (Unaffected by the change)

13. What are Python decorators?

Answer: A decorator is a powerful tool that allows you to modify or extend the behavior of a function or method without permanently changing its code. It is a function that takes another function as an argument and returns a new function.

Example: A simple decorator to measure execution time.

python

import time

def timer_decorator(func):
    def wrapper():
        start_time = time.time()
        func()
        end_time = time.time()
        print(f"Function took {end_time - start_time} seconds to run.")
    return wrapper

@timer_decorator
def my_slow_function():
    time.sleep(2)

my_slow_function()

14. What is the difference between a module and a package in Python?

Answer:

• Module: A single Python file (with a .py extension) that contains Python code (functions, classes, variables). E.g., math.py is a module.

• Package: A collection of modules in a directory. A package must contain a special file named __init__.py (which can be empty) to distinguish it from a regular directory.

Advanced Beginner Level Questions

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

Answer: The GIL is a mutex (a lock) in CPython (the standard Python implementation) that allows only one thread to execute in the interpreter at a time. This means that even on a multi-core processor, CPython cannot achieve true parallelism with threads for CPU-bound tasks. It was designed to make memory management thread-safe. To achieve true parallelism, the multiprocessing module is often used instead of threading.

16. How can you achieve multithreading and multiprocessing in Python?

Answer:

• Multithreading: Use the threading module. It's best for I/O-bound tasks (like network requests, file operations) where the program is often waiting for external resources. Due to the GIL, it's not suitable for CPU-bound tasks.

• Multiprocessing: Use the multiprocessing module. It creates separate Python processes, each with its own Python interpreter and memory space, thus bypassing the GIL. It's best for CPU-bound tasks that can be parallelized.

17. What are generators in Python? Why are they used?

Answer: Generators are a simple way to create iterators using a function with the yield keyword instead of return. They generate items one at a time and only when asked (lazy evaluation), which is memory efficient for large datasets.

Example:

python

def square_generator(n):
    for i in range(n):
        yield i ** 2  # 'yield' pauses the function

# Using the generator
my_gen = square_generator(5)
for num in my_gen:
    print(num) # Output: 0, 1, 4, 9, 16

18. What is the with statement used for? Give an example.

Answer: The with statement is used for resource management and exception handling. It simplifies the management of common resources like file streams by ensuring that clean-up code (like closing a file) is executed, even if an exception occurs. This concept is known as a context manager.

Example: File Handling

python

# Without 'with' (manual closing)
file = open('file.txt', 'r')
content = file.read()
file.close() # Must not forget to close!

# With 'with' (recommended)
with open('file.txt', 'r') as file:
    content = file.read()
# The file is automatically closed when the block is exited.

19. Explain the self keyword in Python.

Answer: self represents the instance of the class. It is the first parameter of any instance method in a class. Through the self keyword, we can access the attributes and methods of that class. It binds the attributes with the given arguments. While the word self is a convention, it is not a reserved keyword; you could use any other name, but it is highly discouraged.

20. What is the difference between a static method and a class method?

Answer:

Example:

python

class MyClass:
    class_attr = 10

    @classmethod
    def class_method(cls):
        print(f"Class attribute is {cls.class_attr}")

    @staticmethod
    def static_method():
        print("I am independent of the class.")

MyClass.class_method() # Output: Class attribute is 10
MyClass.static_method() # Output: I am independent of the class.

Good luck with your interview! Remember to practice writing code by hand and explaining your thought process clearly.