Q29: Write a Python program to merge two dictionaries.

dict1 = {'a': 1, 'b': 2}
dict2 = {'b': 3, 'c': 4}

# Using the update() method
dict1.update(dict2)
print(dict1)
# Output: {'a': 1, 'b': 3, 'c': 4}

# Using dictionary unpacking (Python 3.5+)
merged = {**dict1, **dict2}
print(merged)
# Output: {'a': 1, 'b': 3, 'c': 4}

Q30: Write a Python program to count the frequency of each word in a text.

text = "apple banana apple strawberry banana apple"
words = text.split()
freq = {}

for word in words:
    freq[word] = freq.get(word, 0) + 1

print(freq)
# Output: {'apple': 3, 'banana': 2, 'strawberry': 1}

Q31: Write a function to compute the nth Fibonacci number.

def fibonacci(n):
    if n <= 0:
        return 0
    elif n == 1:
        return 1
    else:
        return fibonacci(n-1) + fibonacci(n-2)

print(fibonacci(7))  # Output: 13

Q32: Implement a simple calculator using functions.

def add(x, y):
    return x + y

def subtract(x, y):
    return x - y

def multiply(x, y):
    return x * y

def divide(x, y):
    if y == 0:
        return "Error! Division by zero."
    return x / y

print(add(5, 3))       # 8
print(subtract(10, 4)) # 6
print(multiply(2, 3))  # 6
print(divide(10, 0))   # Error! Division by zero.

Q33: Write a Python program to read a CSV file and print its contents.

import csv

with open('data.csv', newline='') as csvfile:
    reader = csv.reader(csvfile)
    for row in reader:
        print(row)

Note: 'data.csv' should be a valid CSV file in the working directory.

Q34: Write a Python class to represent a bank account with deposit and withdrawal methods.

class BankAccount:
    def __init__(self, owner, balance=0):
        self.owner = owner
        self.balance = balance

    def deposit(self, amount):
        self.balance += amount
        print(f"Deposited ${amount}. New balance is ${self.balance}.")

    def withdraw(self, amount):
        if amount > self.balance:
            print("Insufficient funds!")
        else:
            self.balance -= amount
            print(f"Withdrew ${amount}. New balance is ${self.balance}.")

account = BankAccount("Alice", 1000)
account.deposit(500)
account.withdraw(200)
account.withdraw(1500)

Q35: Write a program to catch division by zero errors gracefully.

try:
    a = 10
    b = 0
    result = a / b
except ZeroDivisionError:
    print("Error: Division by zero is not allowed.")
else:
    print("Result:", result)

Q36: What is the difference between == and is operators?

Answer:

• == checks if the values of two variables are equal.
• is checks if two variables point to the same object in memory.

a = [1, 2, 3]
b = a
c = list(a)

print(a == c)  # True (values are equal)
print(a is c)  # False (different objects)
print(a is b)  # True (same object)

Q37: Explain list slicing with examples.

my_list = [0, 1, 2, 3, 4, 5, 6]

print(my_list[1:5])   # [1, 2, 3, 4]
print(my_list[:3])    # [0, 1, 2]
print(my_list[4:])    # [4, 5, 6]
print(my_list[::2])   # [0, 2, 4, 6] (every second element)
print(my_list[::-1])  # [6, 5, 4, 3, 2, 1, 0] (reversed list)

Q38: What is a generator? Write a simple example.

def countdown(n):
    while n > 0:
        yield n
        n -= 1

for i in countdown(5):
    print(i)
# Output: 5 4 3 2 1

Q39: Explain the difference between shallow copy and deep copy.

Answer:

• Shallow copy: copies the object but references nested objects.
• Deep copy: copies the object and recursively copies nested objects.

import copy

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

original[0][0] = 99
print(shallow)  # [[99, 2], [3, 4]] (affected)
print(deep)     # [[1, 2], [3, 4]] (unaffected)

Q40: How do you create and activate a virtual environment in Python?

Answer:

# Create a virtual environment named 'venv'
python -m venv venv

# Activate (Windows)
venv\Scripts\activate

# Activate (Unix/Mac)
source venv/bin/activate

Virtual environments help manage dependencies and isolate projects.

Q41: What are *args and **kwargs? Give an example usage.

def func(*args, **kwargs):
    print("args:", args)
    print("kwargs:", kwargs)

func(1, 2, 3, name="Alice", age=30)
# args: (1, 2, 3)
# kwargs: {'name': 'Alice', 'age': 30}

Q42: What is duck typing in Python?

Answer: Duck typing means an object's suitability is determined by the presence of methods and properties, not by its type. If it walks like a duck and quacks like a duck, it is treated as a duck.

def quack(duck):
    duck.quack()

class Duck:
    def quack(self):
        print("Quack!")

class Person:
    def quack(self):
        print("I'm pretending to quack!")

quack(Duck())   # Quack!
quack(Person()) # I'm pretending to quack!

Q43: Explain Python’s memory management and garbage collection.

Answer:

• Python uses reference counting to keep track of objects.
• When an object’s reference count hits zero, it is deleted.
• Garbage collector handles cyclic references that reference counting misses.
• Python’s gc module can be used to interact with the garbage collector.

Q44: What are decorators in Python? Provide a simple example.

def decorator(func):
    def wrapper():
        print("Before the function runs.")
        func()
        print("After the function runs.")
    return wrapper

@decorator
def say_hello():
    print("Hello!")

say_hello()
# Output:
# Before the function runs.
# Hello!
# After the function runs.

Q45: Explain map(), filter(), and reduce() functions with examples.

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

# map() - apply function to all items
squared = list(map(lambda x: x**2, numbers))
print(squared)  # [1, 4, 9, 16, 25]

# filter() - filter items based on condition
evens = list(filter(lambda x: x % 2 == 0, numbers))
print(evens)  # [2, 4]

# reduce() - apply function cumulatively
from functools import reduce
sum_all = reduce(lambda a, b: a + b, numbers)
print(sum_all)  # 15

Q46: What is the purpose of the with statement in file handling?

Answer: The with statement ensures that resources are properly managed. For files, it automatically closes the file after the block executes, even if exceptions occur.

with open("file.txt", "r") as f:
    data = f.read()
# file is automatically closed here

Q47: What is multithreading and multiprocessing? When to use each?

Answer:

• Multithreading: Multiple threads within the same process share memory. Useful for I/O-bound tasks.
• Multiprocessing: Multiple processes with separate memory spaces. Useful for CPU-bound tasks.

Q48: Explain the difference between a module and a package.

Answer:

• Module: A single Python `.py` file containing code.
• Package: A directory containing multiple modules and an `__init__.py` file.

Q49: How can you handle missing keys in a dictionary?

my_dict = {'a': 1}

# Using get() with default
value = my_dict.get('b', 0)
print(value)  # 0

# Using defaultdict from collections
from collections import defaultdict
dd = defaultdict(int)
print(dd['missing'])  # 0

Q50: How do you debug Python code?

Answer: Use print statements, Python's built-in pdb debugger, or IDE debuggers to step through code and inspect variables.

import pdb

def buggy_func(x):
    pdb.set_trace()  # program pauses here
    return x / 0  # will cause error

buggy_func(10)

Q51: Explain what is PEP 8.

Answer: PEP 8 is the official Python style guide that defines best practices for writing readable Python code, including naming conventions, indentation, spacing, and more.

Q52: Write a Python program to find all prime numbers between 1 and 100.

for num in range(2, 101):
    is_prime = True
    for i in range(2, int(num ** 0.5) + 1):
        if num % i == 0:
            is_prime = False
            break
    if is_prime:
        print(num, end=" ")

Q53: How do you create a Python package?

Answer: Create a directory with an __init__.py file (can be empty). Put modules (.py files) inside the directory. Import using the package name.

Q54: What is the Global Interpreter Lock (GIL) in Python?

Answer: The GIL is a mutex that protects access to Python objects, preventing multiple native threads from executing Python bytecodes at once. It simplifies memory management but limits true multi-threading in CPU-bound programs.

Q55: How do you document Python functions?

def add(a, b):
    """Add two numbers and return the result.

    Args:
        a (int): First number.
        b (int): Second number.

    Returns:
        int: Sum of a and b.
    """
    return a + b

Q56: What are Python's special (dunder) methods? Give examples.

Answer: Special methods begin and end with double underscores and allow customization of class behavior.

class Vector:
    def __init__(self, x, y):
        self.x = x
        self.y = y

    def __str__(self):
        return f"Vector({self.x}, {self.y})"

v = Vector(1, 2)
print(v)  # Output: Vector(1, 2)

Q57: How do you use list comprehensions with conditions?

numbers = [1, 2, 3, 4, 5, 6]
evens = [x for x in numbers if x % 2 == 0]
print(evens)  # [2, 4, 6]

Q58: What are Python’s built-in functions to inspect objects?

Answer: type(), dir(), help(), isinstance(), id().

import sys

print("Script name:", sys.argv[0])
print("Arguments:", sys.argv[1:])

Q61: What are Python decorators and how do they work? Provide an example.

Answer: Decorators are functions that modify the behavior of other functions or methods without changing their code.

def decorator_func(func):
    def wrapper():
        print("Before function call")
        func()
        print("After function call")
    return wrapper

@decorator_func
def say_hello():
    print("Hello!")

say_hello()

# Output:
# Before function call
# Hello!
# After function call

Q62: What is the use of the with statement and context managers?

Answer: The with statement simplifies exception handling by encapsulating common preparation and cleanup tasks, like opening and closing files automatically.

with open('file.txt', 'r') as f:
    content = f.read()
# file is automatically closed here

Q63: What are comprehensions in Python? Give examples of list, dict, and set comprehensions.

# List comprehension
squares = [x**2 for x in range(5)]  # [0,1,4,9,16]

# Dictionary comprehension
square_dict = {x: x**2 for x in range(5)}  # {0:0,1:1,2:4,3:9,4:16}

# Set comprehension
square_set = {x**2 for x in range(5)}  # {0,1,4,9,16}

Q64: Explain multithreading and multiprocessing in Python. When would you use each?

Answer:

• Multithreading: Runs multiple threads in the same process to handle I/O-bound tasks concurrently. Limited by the GIL for CPU-bound tasks.
• Multiprocessing: Runs separate processes for CPU-bound tasks, bypassing GIL for true parallelism.

Q65: How do you install external Python packages?

Answer: Use pip package manager:

pip install package_name

Q66: What is a virtual environment and why is it important?

Answer: A virtual environment isolates project dependencies so that each project can have its own package versions, avoiding conflicts.

# Create virtual env
python -m venv env

# Activate (Windows)
env\Scripts\activate

# Activate (Linux/Mac)
source env/bin/activate

Q67: What does it mean to write Pythonic code?

Answer: Writing Pythonic code means following Python's idioms and best practices for clear, concise, readable, and efficient code.

Q68: What is PEP 8?

Answer: PEP 8 is the official Python style guide that recommends coding standards to improve code readability.

Q69: How can you improve code performance in Python?

Answer: Use efficient data structures, built-in functions, avoid unnecessary loops, use generators, and optimize algorithms.

Q70: Explain common debugging techniques in Python.

Answer: Use print statements, Python debugger (pdb), IDE debuggers, logging module, and unit testing.

Q71: What are docstrings and how do you write them?

Answer: Docstrings are string literals used to document modules, classes, and functions. They use triple quotes immediately after the definition.

def add(a, b):
    """Return the sum of a and b."""
    return a + b

Q72: Write a generator that yields even numbers up to n.

def even_numbers(n):
    for i in range(0, n+1, 2):
        yield i

for num in even_numbers(10):
    print(num)

Q73: Write a decorator that logs function calls.

def log_calls(func):
    def wrapper(*args, **kwargs):
        print(f"Calling {func.__name__} with args {args} kwargs {kwargs}")
        result = func(*args, **kwargs)
        print(f"{func.__name__} returned {result}")
        return result
    return wrapper

@log_calls
def add(a, b):
    return a + b

add(5, 7)

Q74: Write a Python program to flatten a nested list.

def flatten(lst):
    flat_list = []
    for item in lst:
        if isinstance(item, list):
            flat_list.extend(flatten(item))
        else:
            flat_list.append(item)
    return flat_list

print(flatten([1, [2, [3, 4], 5], 6]))  # [1,2,3,4,5,6]

Q75: Explain list slicing with examples.

lst = [0,1,2,3,4,5]

print(lst[1:4])    # [1, 2, 3]
print(lst[:3])     # [0, 1, 2]
print(lst[3:])     # [3, 4, 5]
print(lst[-3:-1])  # [3, 4]
print(lst[::2])    # [0, 2, 4]

Q76: What is duck typing?

Answer: Duck typing is a dynamic typing philosophy in Python where the object's suitability is determined by the presence of certain methods and properties, not the object's actual type.

Q77: What is the difference between a module and a package?

Answer: A module is a single Python file containing code. A package is a collection of modules organized in directories with an __init__.py file.

Q78: How does Python's garbage collector work?

Answer: Python uses reference counting and a cyclic garbage collector to free memory occupied by objects that are no longer in use.

Q79: What are dunder (double underscore) methods? Give examples.

Answer: Dunder methods are special methods with double underscores that provide operator overloading and object behavior customization, e.g., __init__, __str__, __repr__.

Q80: What is the difference between shallow copy and deep copy?

import copy

lst1 = [[1,2], [3,4]]
shallow = copy.copy(lst1)
deep = copy.deepcopy(lst1)

lst1[0][0] = 9
print(shallow)  # [[9,2], [3,4]]  # affected by change
print(deep)     # [[1,2], [3,4]]  # not affected

Q81: Why is Python called an interpreted language?

Answer: Because Python code is executed line-by-line by an interpreter without prior compilation to machine code.

Q82: What does it mean that Python is dynamically typed?

Answer: Variable types are determined at runtime, and you don’t need to declare them explicitly.

Q83: How does Python manage memory?

Answer: Python manages memory automatically via reference counting and garbage collection.

Q84: What is the difference between list.append() and list.extend()?

lst = [1,2]
lst.append([3,4])  # [1,2,[3,4]]
lst.extend([5,6])  # [1,2,[3,4],5,6]

Q85: How do you create a virtual environment?

python -m venv env
source env/bin/activate  # Linux/Mac
env\Scripts\activate     # Windows

Q86: How do you debug Python code?

Answer: Using print statements, Python’s pdb debugger, IDE tools, or logging module.

Q87: What is the Global Interpreter Lock (GIL)?

Answer: A mutex that allows only one thread to execute Python bytecode at a time, limiting true multithreading in CPU-bound tasks.

Q88: What is the difference between == and is?

Answer: == checks value equality, is checks object identity (if two variables point to the same object).

Q89: Explain how to handle missing keys in a dictionary.

my_dict = {'a':1}
print(my_dict.get('b', 'Not found'))  # returns 'Not found' instead of error

Q90: What is recursion? Give an example.

def factorial(n):
    if n == 0:
        return 1
    return n * factorial(n-1)

print(factorial(5))  # 120

Q91: What is the difference between a module and a package?

Answer: A module is a single Python file (.py), while a package is a directory with __init__.py containing multiple modules.

Q92: How do you document a Python function?

def add(a, b):
    """Add two numbers and return the result."""
    return a + b

Q93: Write a Python program to read user input until 'exit' is typed.

while True:
    data = input("Enter data (type 'exit' to quit): ")
    if data.lower() == 'exit':
        break
    print("You entered:", data)

Q94: Explain list slicing with step.

lst = [0,1,2,3,4,5,6,7,8,9]
print(lst[1:8:2])  # [1, 3, 5, 7]

Q95: What is a Python generator and why use it?

Answer: Generators produce items one at a time and only when needed, saving memory compared to returning a full list.

Q96: What are Python’s built-in data structures and their time complexities?

Answer:

• List: O(1) for append/pop at end, O(n) for search or insert/remove in middle.
• Dict: Average O(1) for lookup, insert, delete (hash table).
• Set: Similar to dict, average O(1) for add, remove, contains.
• Tuple: Immutable list, O(1) access.

Q97: Explain Python’s argument passing mechanism.

Answer: Python uses call by object reference (also called call by assignment). Mutable objects can be changed inside a function; immutable objects cannot.

Q98: What is the difference between staticmethod and classmethod?

class MyClass:
    @staticmethod
    def static_method():
        print("Static method called")

    @classmethod
    def class_method(cls):
        print(f"Class method called for {cls}")

MyClass.static_method()  # No cls or self
MyClass.class_method()   # Receives cls as class reference

Q99: How do you handle exceptions with else and finally?

try:
    print("Try block")
except Exception:
    print("Except block")
else:
    print("Else block (if no exception)")
finally:
    print("Finally block (always executes)")

Q100: How do you merge two dictionaries?

# Python 3.9+
dict1 = {'a': 1}
dict2 = {'b': 2}
merged = dict1 | dict2
print(merged)  # {'a': 1, 'b': 2}

# Before 3.9
merged = {**dict1, **dict2}

Q101: What is a namedtuple?

Answer: An immutable, lightweight object type from the collections module with named fields for better readability.

from collections import namedtuple
Point = namedtuple('Point', ['x', 'y'])
p = Point(1, 2)
print(p.x, p.y)  # 1 2

Q102: What is monkey patching in Python?

Answer: Dynamically changing or extending a class or module at runtime without modifying the original source code.

Q103: Explain the difference between shallow and deep copy with an example.

import copy
lst = [[1,2], [3,4]]

shallow_copy = copy.copy(lst)
deep_copy = copy.deepcopy(lst)

lst[0][0] = 99

print(shallow_copy)  # [[99, 2], [3, 4]]
print(deep_copy)     # [[1, 2], [3, 4]]

Q104: What is the difference between filter(), map(), and reduce()?

Answer:

• filter(): Filters items based on a function returning True or False.
• map(): Applies a function to all items in an iterable.
• reduce(): Repeatedly applies a function to items to reduce them to a single value (from functools).

Q105: How can you implement a singleton pattern in Python?

class Singleton:
    _instance = None

    def __new__(cls):
        if cls._instance is None:
            cls._instance = super().__new__(cls)
        return cls._instance

obj1 = Singleton()
obj2 = Singleton()
print(obj1 is obj2)  # True

Q106: How do you sort a list of dictionaries by a key?

people = [{'name': 'Alice', 'age': 30}, {'name': 'Bob', 'age': 25}]
sorted_people = sorted(people, key=lambda x: x['age'])
print(sorted_people)

Q107: What is a Python iterator and iterable?

Answer: An iterable is an object you can loop over (e.g., list, tuple). An iterator is an object with a __next__() method that returns items one by one.

Q108: How to create a custom iterator?

class Counter:
    def __init__(self, low, high):
        self.current = low
        self.high = high

    def __iter__(self):
        return self

    def __next__(self):
        if self.current > self.high:
            raise StopIteration
        else:
            self.current += 1
            return self.current - 1

for c in Counter(1, 3):
    print(c)

Q109: Explain the difference between a generator and a list.

Answer: Generators yield items on demand and use less memory. Lists hold all items in memory.

Q110: How can you handle command-line arguments in Python?

import sys

print("Arguments:", sys.argv)  # List of command-line arguments

# Or use argparse for advanced parsing

Q111: What are Python’s built-in functions for type conversion?

Answer: int(), float(), str(), bool(), list(), tuple(), dict(), set().

Q112: What is list unpacking? Provide an example.

a, b, *rest = [1, 2, 3, 4, 5]
print(a)    # 1
print(b)    # 2
print(rest) # [3, 4, 5]

Q113: How do you reverse a string in Python?

s = "Hello"
print(s[::-1])  # "olleH"

Q114: What are f-strings? Show an example.

name = "Alice"
age = 30
print(f"My name is {name} and I am {age} years old.")

Q115: How do you check if a key exists in a dictionary?

my_dict = {'a': 1, 'b': 2}
if 'a' in my_dict:
    print("Key exists")

Q116: What is the difference between isinstance() and type()?

Answer: isinstance() checks inheritance too, type() checks exact type.

Q117: How can you measure execution time of a code snippet?

import time

start = time.time()
# code block
end = time.time()
print("Execution time:", end - start, "seconds")

Q118: Explain the difference between a list and a tuple.

Answer: Lists are mutable; tuples are immutable. Tuples can be used as dictionary keys.

Q119: What is the purpose of the pass statement?

Answer: pass is a null statement used as a placeholder when syntax requires a statement but no action is needed.

Q120: How do you raise an exception in Python?

raise ValueError("Invalid input")