Basic to Intermediate Questions

1. What is the difference between break, continue, and pass?

Answer:

• break: Exits the entire loop immediately.

• continue: Skips the current iteration and moves to the next one.

• pass: A null operation - does nothing. Used as a placeholder where syntax requires a statement but you don't want any code to execute.

Example:

python

for i in range(5):
    if i == 2:
        continue  # Skip iteration when i is 2
    if i == 4:
        break    # Exit loop when i is 4
    print(i)
# Output: 0, 1, 3

def empty_function():
    pass  # Placeholder for future code

2. How do you swap two variables in Python?

Answer: Python allows swapping without a temporary variable:

python

a = 5
b = 10

# Pythonic way
a, b = b, a

print(a)  # 10
print(b)  # 5

3. What are lambda functions? When would you use them?

Answer: Lambda functions are small, anonymous functions defined with the lambda keyword. They can have any number of arguments but only one expression.

Syntax: lambda arguments: expression

Use Cases: When you need a simple function for a short period, typically with functions like map(), filter(), or sort().

Example:

python

# Regular function
def square(x):
    return x * x

# Lambda equivalent
square = lambda x: x * x

# Using with map()
numbers = [1, 2, 3, 4]
squared = list(map(lambda x: x**2, numbers))
print(squared)  # [1, 4, 9, 16]

4. What is the difference between range() and xrange()?

Answer: In Python 2, range() returns a list, while xrange() returns a generator (memory efficient). In Python 3, xrange() was removed, and range() behaves like Python 2's xrange() - it returns a range object that generates numbers on demand.

5. How do you reverse a list in Python?

Answer: Several ways:

python

my_list = [1, 2, 3, 4]

# Method 1: Using reverse() method (modifies original)
my_list.reverse()
print(my_list)  # [4, 3, 2, 1]

# Method 2: Using slicing (creates new list)
reversed_list = my_list[::-1]
print(reversed_list)  # [4, 3, 2, 1]

# Method 3: Using reversed() function
reversed_list = list(reversed(my_list))
print(reversed_list)  # [4, 3, 2, 1]

6. What are docstrings in Python?

Answer: Docstrings are string literals that appear right after the definition of a function, method, class, or module. They are used to document code and can be accessed using help() or the __doc__ attribute.

Example:

python

def add_numbers(a, b):
    """
    This function adds two numbers and returns the result.
    
    Parameters:
    a (int/float): First number
    b (int/float): Second number
    
    Returns:
    int/float: Sum of a and b
    """
    return a + b

print(help(add_numbers))
print(add_numbers.__doc__)

7. How do you handle file operations in Python?

Answer: Using the open() function with different modes:

python

# Writing to a file
with open('file.txt', 'w') as f:
    f.write("Hello, World!")

# Reading from a file
with open('file.txt', 'r') as f:
    content = f.read()
    print(content)

# Appending to a file
with open('file.txt', 'a') as f:
    f.write("\nAppended text")

8. What is the difference between / and // operators?

Answer:

• /: Regular division - returns a float result

• //: Floor division - returns the integer part of the quotient (rounds down)

Example:

python

print(7 / 2)   # 3.5
print(7 // 2)  # 3
print(-7 // 2) # -4 (rounds towards negative infinity)

9. How do you remove duplicates from a list?

Answer:

python

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

# Method 1: Convert to set and back to list
unique_list = list(set(my_list))
print(unique_list)  # [1, 2, 3, 4, 5]

# Method 2: Using dict.fromkeys() (preserves order in Python 3.7+)
unique_list = list(dict.fromkeys(my_list))
print(unique_list)  # [1, 2, 3, 4, 5]

# Method 3: Using loop (preserves order)
unique_list = []
for item in my_list:
    if item not in unique_list:
        unique_list.append(item)

10. What is the purpose of __name__ == "__main__"?

Answer: This construct allows you to execute code only when the script is run directly, not when it's imported as a module.

Example:

python

# my_script.py
def my_function():
    print("This is a function")

if __name__ == "__main__":
    print("Script is running directly")
    my_function()
# When run directly: Both print statements execute
# When imported: Only the function definition is loaded

Object-Oriented Programming Questions

11. Explain inheritance in Python with an example.

Answer: Inheritance allows a class to inherit attributes and methods from another class.

Example:

python

class Animal:
    def __init__(self, name):
        self.name = name
    
    def speak(self):
        pass

class Dog(Animal):  # Dog inherits from Animal
    def speak(self):
        return "Woof!"

class Cat(Animal):  # Cat inherits from Animal
    def speak(self):
        return "Meow!"

dog = Dog("Buddy")
print(dog.name)     # Buddy
print(dog.speak())  # Woof!

12. What is method overriding?

Answer: Method overriding occurs when a subclass provides a specific implementation of a method that is already defined in its parent class.

Example:

python

class Parent:
    def show(self):
        print("Parent's method")

class Child(Parent):
    def show(self):  # Overriding parent's method
        print("Child's method")

obj = Child()
obj.show()  # Output: "Child's method"

13. What are getters and setters in Python? How do you implement them?

Answer: Getters and setters are used to control access to class attributes. In Python, we use properties with the @property decorator.

Example:

python

class Person:
    def __init__(self, name):
        self._name = name  # Private variable convention
    
    @property
    def name(self):  # Getter
        return self._name
    
    @name.setter
    def name(self, value):  # Setter
        if isinstance(value, str):
            self._name = value
        else:
            raise ValueError("Name must be a string")

person = Person("Alice")
print(person.name)  # Alice (using getter)
person.name = "Bob" # Using setter
print(person.name)  # Bob

14. What is the difference between instance variables and class variables?

Answer:

• Instance variables: Belong to each instance/object. Defined using self.variable_name

• Class variables: Shared by all instances. Defined within the class but outside any methods

Example:

python

class Car:
    wheels = 4  # Class variable
    
    def __init__(self, brand):
        self.brand = brand  # Instance variable

car1 = Car("Toyota")
car2 = Car("Honda")

print(car1.wheels)  # 4
print(car2.wheels)  # 4

Car.wheels = 6  # Affects all instances
print(car1.wheels)  # 6

Intermediate to Advanced Questions

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

Answer:

• @staticmethod: Doesn't receive any implicit first argument. Can't access or modify class state.

• @classmethod: Receives the class (cls) as first argument. Can access and modify class state.

Example:

python

class MyClass:
    class_var = 10
    
    def __init__(self, value):
        self.value = value
    
    @classmethod
    def class_method(cls):
        return f"Class variable: {cls.class_var}"
    
    @staticmethod
    def static_method():
        return "This is a static method"

print(MyClass.class_method())   # Class variable: 10
print(MyClass.static_method())  # This is a static method

16. What are context managers? How do you create one?

Answer: Context managers manage resources and ensure proper cleanup. You can create one using:

1. A class with __enter__ and __exit__ methods

2. The contextlib module with @contextmanager decorator

Example using class:

python

class FileManager:
    def __init__(self, filename, mode):
        self.filename = filename
        self.mode = mode
    
    def __enter__(self):
        self.file = open(self.filename, self.mode)
        return self.file
    
    def __exit__(self, exc_type, exc_val, exc_tb):
        self.file.close()

# Usage
with FileManager('test.txt', 'w') as f:
    f.write('Hello')

17. How does Python's garbage collection work?

Answer: Python uses:

1. Reference counting: Objects are deleted when their reference count drops to zero

2. Generational garbage collection: For handling circular references, it uses three generations and collects older objects less frequently

Example:

python

import gc

# Check GC thresholds
print(gc.get_threshold())  # (700, 10, 10)

# Manually trigger collection
gc.collect()

18. What are metaclasses in Python?

Answer: Metaclasses are the "classes of classes" that define how classes behave. The default metaclass is type.

Example:

python

# Creating a class using type metaclass
MyClass = type('MyClass', (), {'attribute': 100})

obj = MyClass()
print(obj.attribute)  # 100

# Custom metaclass
class Meta(type):
    def __new__(cls, name, bases, dct):
        dct['custom_attr'] = 50
        return super().__new__(cls, name, bases, dct)

class MyClass(metaclass=Meta):
    pass

print(MyClass.custom_attr)  # 50

19. How do you handle JSON in Python?

Answer: Using the json module:

python

import json

# Python object to JSON string
data = {'name': 'John', 'age': 30, 'cities': ['NYC', 'London']}
json_string = json.dumps(data)
print(json_string)

# JSON string to Python object
python_obj = json.loads(json_string)
print(python_obj['name'])  # John

# Working with files
with open('data.json', 'w') as f:
    json.dump(data, f)

with open('data.json', 'r') as f:
    loaded_data = json.load(f)

20. What is the difference between __str__ and __repr__?

Answer:

• __str__: Meant for end-users - informal, readable representation

• __repr__: Meant for developers - official, unambiguous representation (should ideally allow recreating the object)

Example:

python

class Point:
    def __init__(self, x, y):
        self.x = x
        self.y = y
    
    def __str__(self):
        return f"Point({self.x}, {self.y})"
    
    def __repr__(self):
        return f"Point(x={self.x}, y={self.y})"

p = Point(3, 4)
print(str(p))   # Point(3, 4) - user friendly
print(repr(p))  # Point(x=3, y=4) - developer friendly

Bonus: Problem-Solving Questions

21. How would you find the most frequent element in a list?

Answer:

python

from collections import Counter

def most_frequent(lst):
    counter = Counter(lst)
    return counter.most_common(1)[0][0]

# Example
numbers = [1, 3, 2, 1, 4, 1, 3, 1]
print(most_frequent(numbers))  # 1

22. How do you check if a string is a palindrome?

Answer:

python

def is_palindrome(s):
    s = s.lower().replace(' ', '')  # Case insensitive, ignore spaces
    return s == s[::-1]

print(is_palindrome("racecar"))  # True
print(is_palindrome("hello"))    # False
print(is_palindrome("A man a plan a canal Panama"))  # True

These questions cover a wide range of Python concepts that are commonly asked in fresher interviews. Practice explaining the concepts clearly and writing clean, efficient code!