Python Interview Q&A

01 What are Python's mutable and immutable data types? Python ▾

Immutable: int, float, str, tuple, frozenset, bool — cannot be changed after creation. Changing creates a new object.
Mutable: list, dict, set — can be modified in place.

Why it matters: Immutable objects are hashable (usable as dict keys). Mutable default function arguments are a common bug — use


          None

as default instead.

python

# Bug: mutable default argument
def bad(lst=[]): lst.append(1); return lst
# Fix:
def good(lst=None):
    if lst is None: lst = []
    lst.append(1); return lst

02 Explain Python decorators with an example. Python ▾

A decorator is a function that wraps another function to add behaviour without modifying its code — uses the higher-order function concept.

python

import time

def timer(func):
    def wrapper(*args, **kwargs):
        t = time.time()
        result = func(*args, **kwargs)
        print(f"Took {time.time()-t:.3f}s")
        return result
    return wrapper

@timer
def slow_fn(): time.sleep(0.5)

Common uses: logging, authentication, caching (


         @functools.lru_cache

), rate limiting.

03 What are generators in Python? How are they different from lists? Python ▾

Generators are functions that yield values one at a time using


         yield

, producing values lazily (on demand) instead of storing the whole sequence in memory.

python

def fibonacci():
    a, b = 0, 1
    while True:
        yield a
        a, b = b, a + b

gen = fibonacci()
print([next(gen) for _ in range(8)])  # [0,1,1,2,3,5,8,13]

Memory: Generator uses O(1) space regardless of sequence length. A list would use O(n). Perfect for large datasets, file reading, streaming.

04 What is the GIL in Python and how does it affect multithreading? Python ▾

The GIL (Global Interpreter Lock) is a mutex in CPython that allows only one thread to execute Python bytecode at a time, even on multi-core CPUs.

Problem: CPU-bound multithreaded code doesn't benefit from multiple cores
Not a problem for I/O-bound tasks — GIL is released during I/O operations (network, file, sleep)
Solution for CPU-bound: Use multiprocessing (separate processes, each with own GIL) or C extensions

Python 3.13+: Experimental "free-threaded" mode can disable the GIL.

05 Explain list comprehension vs map/filter vs for loop — when to use what? Python ▾

python

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

# List comprehension — Pythonic, readable, fast
evens = [x for x in nums if x%2==0]

# map/filter — functional, lazy, returns iterators
evens = list(filter(lambda x: x%2==0, nums))

# for loop — most readable for complex logic
evens = []
for x in nums:
    if x%2==0: evens.append(x)

Guideline: Prefer list comprehensions for simple transforms. Use

for

loops for complex logic. Use

map

/


         filter

when chaining with itertools or for lazy evaluation.

06 What are *args and **kwargs in Python? Python ▾


         *args

collects extra positional arguments as a tuple .


         **kwargs

collects extra keyword arguments as a dict .

python

def greet(name, *args, **kwargs):
    print(f"Hello {name}")
    print(f"Extra args: {args}")
    print(f"Extra kwargs: {kwargs}")

greet("Alice", 25, "NYC", city="Boston", active=True)

Use case: Writing flexible APIs, decorators, wrapper functions.

07 What is the difference between deep copy and shallow copy? Python ▾

Shallow copy creates a new object but inserts references to the original nested objects.
Deep copy creates a new object and recursively copies all nested objects.

python

import copy

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

shallow = copy.copy(lst)
deep = copy.deepcopy(lst)

lst[0][0] = 999
print(shallow)  # [[999, 2], [3, 4]] - affected!
print(deep)     # [[1, 2], [3, 4]] - independent

08 Explain the difference between == and is in Python. Python ▾

==

checks value equality (do they have the same content?).

is

checks reference equality (are they the same object in memory?).

python

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 reference)

09 What is the difference between list and tuple? When would you use each? Python ▾

Aspect	List	Tuple
Mutability	Mutable	Immutable
Syntax	`[1, 2, 3]`	`(1, 2, 3)`
Performance	Slower	Faster
Use case	Dynamic data	Fixed records, dict keys

10 What are context managers and the 'with' statement? Python ▾

Context managers handle resource setup and teardown automatically using


         __enter__

and


         __exit__

methods.

python

# Using with statement
with open("file.txt") as f:
    data = f.read()
# File automatically closed

# Custom context manager
from contextlib import contextmanager

@contextmanager
def timer():
    import time
    start = time.time()
    try:
        yield
    finally:
        print(f"Took {time.time()-start:.3f}s")

11 What is the difference between @classmethod, @staticmethod, and instance method? Python ▾

python

class MyClass:
    count = 0

    def instance_method(self):  # access self & class
        return self

    @classmethod
    def class_method(cls):  # access class, not instance
        return cls.count

    @staticmethod
    def static_method(x):  # no self or cls
        return x * 2

Use classmethod: Factory methods, alternative constructors. Use staticmethod: Utility functions logically belonging to the class.

12 What are dunder (magic) methods in Python? Python ▾

Dunder methods (double underscore) let you define how objects behave with built-in operators and functions.

__init__ — constructor
__str__ , __repr__ — string representation
__len__ — len(obj)
__eq__ , __lt__ , __gt__ — comparison operators
__add__ , __mul__ — arithmetic operators
__getitem__ , __setitem__ — indexing obj[key]
__iter__ , __next__ — make object iterable
__enter__ , __exit__ — context manager protocol

13 Explain inheritance and the MRO (Method Resolution Order) in Python. Python ▾

Python uses C3 linearization to determine MRO in multiple inheritance.

python

class A: pass
class B(A): pass
class C(A): pass
class D(B, C): pass

print(D.__mro__)
# D → B → C → A → object

Use


         help(Class)

or


         Class.__mro__

to inspect the order.

14 What is the difference between range() and xrange()? Python ▾

Python 2:

range() returns a list
xrange() returns a generator (lazy evaluation)

Python 3:

range() behaves like xrange() (returns a range object, lazy)
xrange() doesn't exist

Tip: In Python 3, range() is memory-efficient regardless of size.

15 How do you handle exceptions in Python? Explain try, except, else, finally. Python ▾

python

try:
    result = 10 / 0
except ZeroDivisionError:
    print("Cannot divide by zero")
else:
    print(f"Result: {result}")  # runs if no exception
finally:
    print("Cleanup complete")  # always runs

try: Code that might raise an exception
except: Handle specific exceptions
else: Runs if no exception occurred
finally: Always executes (cleanup code)

16 Find the maximum profit by buying and selling stock at different times. Python ▾

Problem: Given stock prices with timestamps, find the maximum profit by buying at one price and selling at a later higher price.

python

prices = [
    ("2026-03-29 09:30:00", 150.25),
    ("2026-03-29 09:31:00", 152.10),
    ("2026-03-29 09:32:00", 151.80),
    ("2026-03-29 09:33:00", 154.50)
]

max_profit = 0
min_price = prices[0][1]

for time, price in prices[1:]:
    profit = price - min_price
    max_profit = max(max_profit, profit)
    min_price = min(min_price, price)

print(f"{max_profit:.2f}")  # 4.25

Explanation:

Track running minimum price seen so far
Calculate profit if selling at current price
Update max_profit and min_price as we iterate

Complexity:

Time: O(n) — single pass through the array
Space: O(1) — only two variables tracked

Pattern: This is the classic "Best Time to Buy and Sell Stock" interview problem. The key insight is that you must buy before you sell, so we track the minimum price seen so far and calculate potential profit at each step.

Python Interview Questions