63 Python Interview Questions and Answers PDF 2025

Python has become essential in modern job markets, particularly in software development, data science, and automation roles. This versatile language handles web development, data analysis, machine learning, and scripting tasks efficiently.

Python developers need technical knowledge in object-oriented programming, data structures, libraries like pandas and NumPy, database integration, and framework expertise. Strong problem-solving skills and algorithmic thinking are equally important.

Interview preparation is crucial as it builds confidence and helps candidates demonstrate their Python proficiency effectively. Proper preparation enables developers to tackle coding challenges, explain concepts clearly, and showcase practical experience.

Here we share popular Python interview questions and answers covering fresher to experienced levels, including technical and real-life scenario-based questions. This comprehensive guide helps you prepare thoroughly for your next Python interview. We also provide a downloadable PDF for offline preparation convenience.

Basic Python Interview Questions and Answers for Fresher

Here are Basic Python Interview Questions and Answers for Fresher. These questions are designed to help freshers prepare for real-world Python coding interviews.

1. What are the key features of Python?

Answer:

• Easy-to-read syntax
• Interpreted language
• Dynamically typed
• Large standard library
• Supports OOP and functional programming

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

Answer:

• List is mutable (can be changed)
• Tuple is immutable (cannot be changed)

Example:

my_list = [1, 2, 3]
my_tuple = (1, 2, 3)

3. How do you write comments in Python?

Answer:
Single-line comments use #.
Multi-line comments can use triple quotes.

# This is a comment
"""
This is a 
multi-line comment
"""

4. How do you define a function in Python?

Answer:
Using the def keyword.

def greet(name):
    return "Hello " + name

What is the use of the len() function?

Answer:
It returns the number of elements in a sequence like list, tuple, or string.

len("Python")  # Output: 6

6. What is a dictionary in Python?

Answer:
A dictionary is a collection of key-value pairs.

my_dict = {"name": "John", "age": 25}

7. What is the use of the type() function?

Answer:
It returns the data type of an object.

type(5)       # Output: <class 'int'>
type("Hi")    # Output: <class 'str'>

8. What is list comprehension?

Answer:
A concise way to create a list using a single line.

squares = [x**2 for x in range(5)]

9. How do you handle exceptions in Python?

Answer:
Using try and except blocks.

try:
    print(1 / 0)
except ZeroDivisionError:
    print("Cannot divide by zero")

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

Answer:

• == checks if values are equal
• is checks if two variables point to the same object

11. What is a module in Python?

Answer:
A file containing Python definitions and functions, which can be imported using the import keyword.

12. How can you get user input in Python?

Answer:
Using the input() function.

name = input("Enter your name: ")

13. How do you write a for loop in Python?

Answer:

for i in range(5):
    print(i)

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

Answer:

• append() adds a single element
• extend() adds multiple elements from another iterable

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

15. What are the Boolean values in Python?

Answer:
True and False, used in conditions and logical operations.

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

Answer:
Using the in keyword.

if 5 in [1, 2, 3, 4, 5]:
    print("Found")

17. What is the use of the strip() function?

Answer:
It removes leading and trailing whitespaces from a string.

" hello ".strip()  # Output: "hello"

18. What is a set in Python?

Answer:
A collection of unique elements.

my_set = {1, 2, 3, 3}  # Output: {1, 2, 3}

19. How do you concatenate two strings?

Answer:
Using the + operator.

"Hello" + " " + "World"

20. What is the output of bool([])?

Answer:
False, because empty lists are considered false in a Boolean context.

Also Check: 57 Technical Interview Questions and Answers PDF 2025

Advanced Python Interview Questions and Answers for Experienced

These questions gradually increase in complexity and focus on deeper Python concepts, tools, and practices.

21. What are Python decorators and how are they used?

Answer:
A decorator is a function that modifies another function without changing its source code. Used for logging, authorization, caching, etc.

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

@my_decorator
def greet():
    print("Hello")

greet()

22. What is a generator in Python and how is it different from a normal function?

Answer:
Generators return iterators using yield instead of return. They produce values lazily, one at a time, which makes them memory-efficient.

def count_up_to(n):
    i = 1
    while i <= n:
        yield i
        i += 1

23. What is the Global Interpreter Lock (GIL) in Python?

Answer:
The GIL ensures only one thread executes Python bytecode at a time in CPython. This limits multi-threaded performance in CPU-bound tasks.

24. What are context managers in Python?

Answer:
Context managers manage resource allocation using with statements (e.g., file handling). They implement __enter__ and __exit__.

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

25. How do you handle memory management in Python?

Answer:
Python uses reference counting and garbage collection for memory management. The gc module can manually interact with the garbage collector.

26. What is the purpose of slots in Python classes?

Answer:
__slots__ limits the attributes of instances and reduces memory overhead.

class MyClass:
    __slots__ = ['name', 'age']

27. Explain metaclasses in Python.

Answer:
A metaclass controls the creation of classes. It is a class of a class, defined using type.

class Meta(type):
    def __new__(cls, name, bases, dct):
        print("Creating class:", name)
        return super().__new__(cls, name, bases, dct)

28. What is monkey patching?

Answer:
Monkey patching means modifying or extending code at runtime, usually to replace methods or attributes.

import datetime
datetime.datetime.now = lambda: "2025-01-01"

29. What are Python’s magic methods?

Answer:
Also known as dunder methods, they include methods like __init__, __str__, __len__, __eq__, and define class behaviors.

30. How do you use memoization in Python?

Answer:
By storing the results of expensive function calls using functools.lru_cache.

from functools import lru_cache

@lru_cache(maxsize=None)
def fib(n):
    return n if n < 2 else fib(n-1) + fib(n-2)

31. How does Python’s property() function work?

Answer:
It turns class methods into managed attributes using @property decorator.

class Person:
    def __init__(self, name):
        self._name = name

    @property
    def name(self):
        return self._name

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

Answer:
Shallow copy copies references, deep copy duplicates objects recursively.

import copy
shallow = copy.copy(obj)
deep = copy.deepcopy(obj)

33. How do you create a custom iterator in Python?

Answer:
By defining __iter__() and __next__() methods in a class.

class Counter:
    def __init__(self, max):
        self.max = max
        self.n = 0

    def __iter__(self):
        return self

    def __next__(self):
        if self.n < self.max:
            self.n += 1
            return self.n
        raise StopIteration

34. What are Python coroutines and how do they differ from generators?

Answer:
Coroutines are like generators but support bidirectional communication with send() and await.

def coroutine():
    while True:
        x = yield
        print(f"Received: {x}")

35. How can you make your Python code thread-safe?

Answer:
Use locks from the threading module to protect shared resources.

import threading

lock = threading.Lock()

def safe_increment():
    with lock:
        # modify shared variable
        pass

Python Interview Questions and Answers for Data Analyst

Here are python questions focused for data analyst roles.

36. How do you read a CSV file using Python?

Answer:
You can read a CSV file using the Pandas library.

import pandas as pd
df = pd.read_csv("data.csv")

37. How do you handle missing data in a DataFrame?

Answer:
You can use dropna() to remove missing values or fillna() to replace them.

df.dropna()        # Drop rows with missing values
df.fillna(0)       # Replace missing values with 0

38. How do you filter rows based on a condition?

Answer:
Use boolean indexing.

filtered_df = df[df["sales"] > 1000]

39. What does “Groupby()” do in pandas?

Answer:
groupby() groups rows based on one or more columns and allows aggregation.

df.groupby("region")["sales"].sum()

40. How do you merge two DataFrames?

Answer:
Use the merge() function in pandas.

merged_df = pd.merge(df1, df2, on="customer_id", how="inner")

41. How do you create a pivot table in pandas?

Answer:
Use pivot_table() to summarize data.

df.pivot_table(values="sales", index="region", columns="month", aggfunc="sum")

42. How do you calculate correlation between variables?

Answer:
Use the corr() method to calculate pairwise correlations.

df.corr()

43. How do you find the top 5 rows with the highest values in a column?

Answer:
Use nlargest().

df.nlargest(5, "sales")

44. How do you rename columns in a DataFrame?

Answer:
Use rename() method with a dictionary of old and new names.

df.rename(columns={"old_name": "new_name"}, inplace=True)

45. How do you visualize data in Python?

Answer:
Use libraries like matplotlib or seaborn.

import seaborn as sns
sns.barplot(x="region", y="sales", data=df)

Need more? you can check here: Data Analyst Interview Questions and Answers

Python Interview Questions and Answers for Data Engineer

These questions cover essential Python skills required in data engineering roles, progressing from basic to slightly advanced.

46. How do you read and write data from a text file in Python?

Answer:

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

with open("file.txt", "w") as f:
    f.write("New data")

47. How do you connect Python to a relational database?

Answer:
You can use libraries like sqlite3, psycopg2, or SQLAlchemy.

import sqlite3
conn = sqlite3.connect("example.db")
cursor = conn.cursor()
cursor.execute("SELECT * FROM users")

48. How do you handle large datasets in Python?

Answer:
Use chunking with pandas, or scalable libraries like Dask for parallel processing.

for chunk in pd.read_csv("large_file.csv", chunksize=10000):
    process(chunk)

49. How do you schedule data pipelines in Python?

Answer:
You can use tools like Airflow, Luigi, or system tools like cron to run Python scripts on schedule.

50. What is the use of the “os” module in file operations?

Answer:
os helps in interacting with the operating system for file and directory handling.

import os
os.listdir(".")
os.remove("data.txt")

51. How do you use environment variables in Python scripts?

Answer:
Use the os.environ dictionary to access environment variables.

import os
db_user = os.environ.get("DB_USER")

52. How do you serialize and deserialize data in Python?

Answer:
Use the pickle or json modules for serialization.

import json
data = {"name": "John"}
with open("data.json", "w") as f:
    json.dump(data, f)

53. How do you process streaming data in Python?

Answer:
Use frameworks like Apache Kafka with confluent-kafka-python, or PySpark Streaming.

54. What is the purpose of the “Multiprocessing” module?

Answer:
It allows you to run multiple processes in parallel to utilize multiple CPU cores.

from multiprocessing import Pool

def square(n):
    return n * n

with Pool(4) as p:
    results = p.map(square, [1, 2, 3, 4])

55. How do you interact with AWS S3 in Python?

Answer:
Use the boto3 library to upload, download, or list objects in S3.

import boto3
s3 = boto3.client("s3")
s3.download_file("my-bucket", "data.csv", "data.csv")

Need more? you can check here: Data Engineer Interview Questions and Answers

Most Common Python Interview Questions

56. What is the difference between is and == in Python?

Answer:

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

a = [1, 2]
b = [1, 2]
a == b     # True
a is b     # False

57. What is the difference between append() and extend() in lists?

Answer:

• append() adds a single item to the list.
• extend() adds elements from another iterable.

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

58. What is the use of zip() in Python?

Answer:
zip() combines multiple iterables element-wise into tuples.

a = [1, 2]
b = ['a', 'b']
list(zip(a, b))  # [(1, 'a'), (2, 'b')]

59. How do you reverse a list or a string in Python?

Answer:
Use slicing or built-in functions.

lst = [1, 2, 3]
lst[::-1]  # [3, 2, 1]

s = "Python"
s[::-1]    # "nohtyP"

60. What is the difference between mutable and immutable types?

Answer:

• Mutable objects can be changed (like list, dict).
• Immutable objects cannot be changed (like int, str, tuple).

61. What are Python’s lambda functions?

Answer:
A lambda function is an anonymous one-line function.

square = lambda x: x * x
square(4)  # 16

62. What is the difference between deepcopy() and copy()?

Answer:

• copy() creates a shallow copy (nested objects are still shared).
• deepcopy() creates a full independent copy.

import copy
shallow = copy.copy(obj)
deep = copy.deepcopy(obj)

63. What is the use of enumerate() in Python?

Answer:
enumerate() returns both the index and value when looping through a list.

for index, value in enumerate(['a', 'b', 'c']):
    print(index, value)

Python Interview Questions and Answers PDF

We are adding this pdf file of python questions so you can prepare anytime easily.

FAQs: Python Interview Questions

Conclusion

We have shared various types of Python interview questions and answers, covering roles from freshers to experienced professionals. A PDF download is also available, allowing you to prepare offline easily.