Python Interview Questions for Freshers with Answers PDF

Preparing for your first Python interview can feel daunting, but with the right resources, you can approach it with confidence. This guide offers a curated set of 50 essential Python interview questions tailored for beginners, each accompanied by clear, well-structured answers. For added convenience, a downloadable PDF is available for offline review. Covering foundational syntax as well as more complex topics, this blog is designed to equip you with the knowledge and practice needed to excel in your upcoming Python coding interview.

Why Python for Freshers?

Python stands out as a preferred programming language for beginners, owing to its straightforward syntax, clear readability, and expansive collection of libraries. Whether one aspires to pursue opportunities in web development, data science, or automation, a solid grasp of Python fundamentals remains essential. The following compilation of 50 questions is designed to evaluate core concepts, practical coding skills, and real-world applications, effectively equipping candidates for technical interviews.

50 Python Interview Questions and Answers

1. What is Python, and why is it popular?

Answer: Python stands out as an exceptionally versatile programming language, widely recognized for its clear, accessible syntax. Its widespread adoption stems from its relatively gentle learning curve and support for various programming paradigms. Furthermore, Python’s robust ecosystem—including libraries such as NumPy, Pandas, and Django—enables its application across diverse domains like data analysis, web development, and artificial intelligence. This breadth of functionality has solidified Python’s reputation as a foundational tool within both academic and professional programming communities.

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

Answer: Lists, denoted by square brackets [ ], are mutable—meaning you can modify their contents after creation. In contrast, tuples are defined with parentheses ( ) and are immutable, so their contents remain fixed once set. Due to their mutability, lists often incur additional overhead and operate more slowly than tuples.

# List example
my_list = [1, 2, 3]
my_list[0] = 10
print(my_list)  # Output: [10, 2, 3]
# Tuple example
my_tuple = (1, 2, 3)
print(my_tuple)  # Output: (1, 2, 3)

3. How do you handle exceptions in Python?

Answer: Use try, except, else, and finally blocks to manage errors gracefully.

try:
    num = int(input("Enter a number: "))
    result = 10 / num
except ZeroDivisionError:
    print("Cannot divide by zero!")
finally:
    print("Execution completed.")

4. Write a program to reverse a string.

Answer: Use slicing to reverse a string efficiently.

def reverse_string(s):
    return s[::-1]
text = "Python"
print(reverse_string(text))  # Output: nohtyP

5. What is the difference between append() and extend()?

Answer: append() adds a single element to a list; extend() adds elements of an iterable individually.

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

6. What is a dictionary in Python?

Answer: A dictionary is a mutable, unordered collection of key-value pairs, defined with {}. Keys must be unique and immutable.

my_dict = {"name": "Alice", "age": 25}
print(my_dict["name"])  # Output: Alice

7. How do you swap two variables in Python?

Answer: Use multiple assignment to swap variables without a temporary variable.

a, b = 5, 10
a, b = b, a
print(a, b)  # Output: 10 5

8. What are Python’s built-in data types?

Answer: Common built-in data types include integers, floats, strings, lists, tuples, dictionaries, sets, and booleans.

9. What is the difference between == and is?

Answer: == checks for value equality; is checks for identity (same memory location).

a = [1, 2]
b = [1, 2]
print(a == b)  # Output: True
print(a is b)  # Output: False

10. What is a list comprehension?

Answer: A concise way to create lists using a single line of code.

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

11. What are *args and **kwargs?

Answer: In Python, *args enables a function to accept an arbitrary number of positional arguments, allowing for flexible input without specifying the exact number in advance. Conversely, **kwargs gathers any additional named or keyword arguments into a dictionary, providing the function access to argument names and their corresponding values. This approach offers significant adaptability when designing functions to handle varied input scenarios.

def func(*args, **kwargs):
    print(args, kwargs)
func(1, 2, name="Alice")  # Output: (1, 2) {'name': 'Alice'}

12. How do you check if a number is prime?

Answer: Check divisibility up to the square root of the number.

def is_prime(n):
    if n < 2:
        return False
    for i in range(2, int(n**0.5) + 1):
        if n % i == 0:
            return False
    return True
print(is_prime(7))  # Output: True

13. What is a lambda function?

Answer: A lambda function is an anonymous, single-expression function defined with lambda.

square = lambda x: x**2
print(square(5))  # Output: 25

14. How do you find the factorial of a number?

Answer: Use recursion or iteration to calculate factorial.

def factorial(n):
    if n == 0:
        return 1
    return n * factorial(n - 1)
print(factorial(5))  # Output: 120

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

Answer: Shallow copy creates a new object but references nested objects; deep copy creates a fully independent copy.

import copy
a = [[1, 2]]
b = copy.copy(a)  # Shallow copy
b[0][0] = 10
print(a)  # Output: [[10, 2]]

16. What is PEP 8?

Answer: PEP 8 essentially serves as the authoritative guide for Python code formatting. Adhering to its conventions—such as using four spaces for indentation (not tabs) and limiting each line to a maximum of 79 characters—ensures code remains readable and maintainable. Neglecting these guidelines can result in inconsistencies that hinder collaboration and future code review.

17. How do you remove duplicates from a list?

Answer: Use a set or list comprehension to remove duplicates.

my_list = [1, 2, 2, 3]
unique_list = list(set(my_list))
print(unique_list)  # Output: [1, 2, 3]

18. What is a set in Python?

Answer: A set is an unordered collection of unique elements, defined with {} or set().

my_set = {1, 2, 2}
print(my_set)  # Output: {1, 2}

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

Answer:In Python 2, invoking range() results in the construction of a list containing the specified sequence of numbers. Conversely, xrange() serves as a generator, producing values on demand without allocating memory for the entire sequence. In Python 3, the behavior of range() has been modified to function similarly to the previous xrange(); it yields values as needed and does not generate a list by default. Notably, the xrange() function has been removed in Python 3, and only range() remains available for creating sequences of numbers.

20. How do you merge two dictionaries?

Answer: Use the | operator (Python 3.9+) or update() method.

dict1 = {"a": 1}
dict2 = {"b": 2}
merged = dict1 | dict2
print(merged)  # Output: {'a': 1, 'b': 2}

21. What is a generator in Python?

Answer: A generator yields values one at a time, saving memory.

def my_gen():
    yield 1
    yield 2
g = my_gen()
print(next(g))  # Output: 1

22. How do you sort a list in Python?

Answer: Use sort() for in-place sorting or sorted() for a new sorted list.

my_list = [3, 1, 2]
my_list.sort()
print(my_list)  # Output: [1, 2, 3]

23. What is the purpose of the if __name__ == "__main__" statement?

Answer: It ensures code runs only when the script is executed directly, not when imported as a module.

if __name__ == "__main__":
    print("Running directly")

24. How do you find the length of a list?

Answer: Use the len() function.

my_list = [1, 2, 3]
print(len(my_list))  # Output: 3

25. What is a module in Python?

Answer: A module is a file containing Python code (functions, classes, variables) that can be imported and reused.

import math
print(math.sqrt(16))  # Output: 4.0

26. How do you read a file in Python?

Answer: Use the open() function with a context manager.

with open("file.txt", "r") as file:
    content = file.read()

27. What is the purpose of pass?

Answer: pass is a placeholder for empty code blocks.

def func():
    pass

28. How do you check if an element exists in a list?

Answer: Use the in operator.

my_list = [1, 2, 3]
print(2 in my_list)  # Output: True

29. What is a decorator?

Answer: A decorator is a function that wraps another function to extend its behavior.

def decorator(func):
    def wrapper():
        print("Before")
        func()
    return wrapper

30. How do you concatenate two lists?

Answer: Use the + operator or extend().

list1 = [1, 2]
list2 = [3, 4]
print(list1 + list2)  # Output: [1, 2, 3, 4]

31. What is the purpose of break and continue?

Answer: break exits a loop; continue skips to the next iteration.

for i in range(5):
    if i == 3:
        break
    print(i)  # Output: 0, 1, 2

32. How do you find the maximum element in a list?

Answer: Use the max() function.

my_list = [1, 5, 3]
print(max(my_list))  # Output: 5

33. What is string slicing?

Answer: String slicing extracts a portion of a string using [start:stop:step].

text = "Python"
print(text[1:4])  # Output: yth

34. How do you convert a string to an integer?

Answer: Use the int() function.

text = "123"
num = int(text)
print(num)  # Output: 123

35. What is a class in Python?

Answer: A class is a blueprint for creating objects, defining attributes and methods.

class Person:
    def __init__(self, name):
        self.name = name
p = Person("Alice")
print(p.name)  # Output: Alice

36. What is inheritance?

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

class Child(Person):
    pass
c = Child("Bob")
print(c.name)  # Output: Bob

37. How do you check the type of a variable?

Answer: Use the type() function.

x = 5
print(type(x))  # Output: 

38. What is the global keyword?

Answer: The global keyword allows modifying a global variable inside a function.

x = 10
def func():
    global x
    x = 20
func()
print(x)  # Output: 20

39. How do you reverse a list in place?

Answer: Use the reverse() method.

my_list = [1, 2, 3]
my_list.reverse()
print(my_list)  # Output: [3, 2, 1]

40. What is the map() function?

Answer: map() applies a function to all items in an iterable.

numbers = [1, 2, 3]
squares = list(map(lambda x: x**2, numbers))
print(squares)  # Output: [1, 4, 9]

41. What is the filter() function?

Answer: filter() selects elements from an iterable based on a function’s condition.

numbers = [1, 2, 3, 4]
evens = list(filter(lambda x: x % 2 == 0, numbers))
print(evens)  # Output: [2, 4]

42. How do you find the GCD of two numbers?

Answer: Use the Euclidean algorithm.

def gcd(a, b):
    while b:
        a, b = b, a % b
    return a
print(gcd(48, 18))  # Output: 6

43. What is a docstring?

Answer: A docstring is a string literal used to document a function, class, or module, enclosed in triple quotes.

def func():
    """This is a docstring."""
    pass

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

Answer: Compare the string with its reverse.

def is_palindrome(s):
    return s == s[::-1]
print(is_palindrome("racecar"))  # Output: True

45. What is the difference between list and array?

Answer: Lists in Python are highly flexible; they allow elements of differing data types and can be resized at will. In contrast, arrays—such as those from the array module or NumPy—enforce a single data type and are generally more efficient in terms of memory usage. Essentially, lists are dynamic and heterogeneous, while arrays are fixed-type and optimized for performance

46. How do you count occurrences in a list?

Answer: Use the count() method.

my_list = [1, 2, 2, 3]
print(my_list.count(2))  # Output: 2

47. What is the zip() function?

Answer: The zip() function combines multiple iterables into tuples, useful for iterating over multiple sequences simultaneously.

list1 = [1, 2]
list2 = ["a", "b"]
zipped = list(zip(list1, list2))
print(zipped)  # Output: [(1, 'a'), (2, 'b')]

48. How do you find the second largest element in a list?

Answer: Sort the list in descending order and access the second element, or use a single pass to track the largest and second largest.

def second_largest(lst):
    if len(lst) < 2:
        return None
    largest = second = float('-inf')
    for num in lst:
        if num > largest:
            second = largest
            largest = num
elif largest > num > second:
       
 
           second = num
     return second
print(second_largest([10, 5, 8, 12]))  # Output: 10

49. What is the difference between pop() and remove() in a list?

Answer: pop() removes and returns an element by index (default: last element); remove() removes the first occurrence of a specified value.

my_list = [1, 2, 3]
print(my_list.pop(1))  # Output: 2
print(my_list)  # Output: [1, 3]
my_list = [1, 2, 3]
my_list.remove(2)
print(my_list)  # Output: [1, 3]

50. How do you split a string into a list?

Answer: Use the split() method to split a string into a list based on a delimiter (default: whitespace).

text = "Hello World Python"
words = text.split()
print(words)  # Output: ['Hello', 'World', 'Python']

Conclusion

This guide presents 50 foundational Python interview questions, spanning topics from fundamental syntax to applied problem-solving. Whether your focus is software engineering or the expanding field of data science, these questions provide a solid framework for your preparation. For convenience, a downloadable PDF is available below, enabling offline review. Additionally, it is advisable to reinforce your understanding by practicing these concepts on coding platforms such as LeetCode or HackerRank. Mastering these areas will significantly enhance your confidence and performance in Python interviews.

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