Python Technical Interview Questions and Answers

1.What are the key features of Python?

Python is popular because it is:

• Interpreted – No need for compilation, executed line by line.
• Dynamically Typed – No need to declare variable types explicitly.
• Object-Oriented – Supports classes, objects, and inheritance.
• High-Level – Easy to read and write.
• Extensive Libraries – Built-in modules for AI, ML, Data Science, etc.
• Cross-Platform – Runs on Windows, Linux, MacOS.

2.What is the difference between Python 2 and Python 3?

Feature	Python 2	Python 3
Print Statement	print "Hello" (no parentheses)	print("Hello") (parentheses required)
Division	5/2 = 2 (Integer division by default)	5/2 = 2.5 (True division)
Unicode Strings	Strings are ASCII by default	Strings are Unicode by default
Support	No longer maintained	Actively maintained

3.What are Python’s data types?

Python provides various built-in data types:

• Numeric – int, float, complex
• Sequence – list, tuple, range, str
• Set – set, frozenset
• Mapping – dict
• Boolean – True, False
• NoneType – None

Example:

x = 10         # int
y = 3.14       # float
z = "Python"   # str
lst = [1, 2, 3] # list
tpl = (4, 5, 6) # tuple
dct = {"key": "value"} # dict

4.What is the difference between a list and a tuple?

Feature	List	Tuple
Definition	Mutable, ordered collection	Immutable, ordered collection
Syntax	my_list = [1,2,3]	my_tuple = (1,2,3)
Performance	Slower due to mutability	Faster as it is immutable
Use Case	When modification is needed	When a fixed sequence is needed

Example:

my_list = [1, 2, 3]
my_list.append(4)  # Allowed

my_tuple = (1, 2, 3)
my_tuple[0] = 10  # TypeError (Tuples are immutable)

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

• Shallow Copy: Copies references to objects (changes affect both copies).
• Deep Copy: Creates a completely independent copy.

Example:

import copy

list1 = [[1, 2], [3, 4]]
shallow = copy.copy(list1)
deep = copy.deepcopy(list1)

list1[0][0] = 99

print(shallow)  # [[99, 2], [3, 4]] (Changed)
print(deep)     # [[1, 2], [3, 4]] (Unchanged)

6.What is Python’s lambda function?

A lambda function is an anonymous function defined with the lambda keyword.

Example:

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

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

• == compares values of objects.
• is compares memory locations (whether they are the same object).

Example:

a = [1, 2, 3]
b = [1, 2, 3]
c = a

print(a == b)  # True (Same values)
print(a is b)  # False (Different objects)
print(a is c)  # True (Same object)

8.What is Python’s garbage collection mechanism?

Python has automatic memory management using reference counting and garbage collection.

• Uses reference counting to track objects.
• If an object has zero references, it gets deleted.
• Garbage collector (gc module) removes circular references.

Example:

import gc
gc.collect()  # Manually trigger garbage collection

9.What is the difference between @staticmethod, @classmethod, and instance methods?

Type	Defined Using	Access	Use Case
Instance Method	def method(self)	self (instance)	Accesses instance data
Class Method	@classmethod def method(cls)	cls (class)	Modifies class attributes
Static Method	@staticmethod def method()	No self or cls	Utility function (no instance/class data needed)

Example:

class MyClass:
    def instance_method(self):
        return "Instance method called", self

    @classmethod
    def class_method(cls):
        return "Class method called", cls

    @staticmethod
    def static_method():
        return "Static method called"

obj = MyClass()
print(obj.instance_method())  # Instance method
print(MyClass.class_method())  # Class method
print(MyClass.static_method()) # Static method

10.What is the difference between append() and extend() in Python?

• append() adds one element to the list.
• extend() adds multiple elements (iterable) to the list.

Example:

lst = [1, 2, 3]
lst.append([4, 5])
print(lst)  # [1, 2, 3, [4, 5]] (Nested list)

lst = [1, 2, 3]
lst.extend([4, 5])
print(lst)  # [1, 2, 3, 4, 5] (Flattened)

11.What are Python generators?

A generator is a special function that returns an iterator using yield.

• Uses yield instead of return.
• Saves memory since it doesn’t store all values in memory.

Example:

def my_generator():
    yield 1
    yield 2
    yield 3

gen = my_generator()
print(next(gen))  # 1
print(next(gen))  # 2

12.What is the difference between map(), filter(), and reduce()?

Function	Purpose	Example
map()	Applies a function to all elements	map(lambda x: x*2, [1,2,3]) → [2,4,6]
filter()	Filters elements based on a condition	filter(lambda x: x>2, [1,2,3]) → [3]
reduce()	Applies cumulative operation	reduce(lambda x,y: x+y, [1,2,3]) → 6

Example:

from functools import reduce

nums = [1, 2, 3, 4]
print(list(map(lambda x: x*2, nums)))  # [2, 4, 6, 8]
print(list(filter(lambda x: x % 2 == 0, nums)))  # [2, 4]
print(reduce(lambda x, y: x + y, nums))  # 10