Python Fundamentals
1. What is Python and why is it popular?
Python is a high-level, interpreted, general-purpose programming language known for its simplicity, readability, and versatility. It is widely used in data science, web development, AI, and automation.
Example: Startups prefer Python to rapidly build MVPs, reducing development time.
2. What are Python’s key features?
Python is interpreted, dynamically typed, object-oriented, portable, and supported by a huge ecosystem of libraries.
Example: NASA uses Python for scientific programming due to its extensive libraries.
3. What are Python’s applications?
Python is used in web apps (Django, Flask), Data Science (NumPy, Pandas), AI/ML (scikit-learn, TensorFlow), automation, scripting, and cloud apps.
Example: Instagram is powered by Django (Python framework).
4. What are Python’s pros and cons?
Pros: Easy to learn, cross-platform, extensive libraries.
Cons: Slower than C++/Java, not ideal for mobile apps.
Example: Dropbox migrated core logic to Python due to rapid scalability.
5. What are Python data types?
Python data types include int, float, str, bool, list, tuple, set, dict, and NoneType.
Example: A customer record stored in a dictionary with keys for name, email, and phone.
6. Difference between list, tuple, set, and dict?
- List: Ordered, mutable
- Tuple: Ordered, immutable
- Set: Unordered, unique values
- Dict: Key-value pairs
Example: E-commerce apps use lists for cart items, tuples for product dimensions, sets for categories, and dicts for customer profiles.
7. What are conditional statements in Python?
Conditional statements include if, elif, and else.
Example: Assign grades based on marks using conditions.
8. What are loops in Python?
Python has for and while loops.
Example: A for loop iterates over orders; a while loop runs until a payment succeeds.
9. What are Python functions?
Functions are reusable code blocks defined using def.
Example:
def calculate_discount(price, rate):
return price - (price * rate)
This can be reused across product categories.
10. Why is indentation important in Python?
Python uses indentation (spaces or tabs) to define code blocks instead of braces.
Example: Misaligned indentation leads to an IndentationError.
Python OOP Concepts
11. What is OOP in Python?
Object-oriented programming models real-world entities using classes and objects.
Example: A Car class with attributes and methods like drive().
12. What are classes and objects?
A Class is a blueprint, and an Object is an instance of that class.
Example:
class Student:
pass
s1 = Student()
13. What is inheritance?
Inheritance allows a class to derive features from another class.
Example: A Dog class inherits from an Animal class.
14. What is polymorphism in Python?
Polymorphism allows the same method to work differently for different objects.
Example: len() works for lists, strings, and dicts.
15. What is encapsulation?
Encapsulation restricts direct access to variables using private/protected members.
Example: A bank account balance is marked as private.
16. What is abstraction?
Abstraction hides implementation details while exposing only the necessary functionality.
Example: A user calls .fit() in scikit-learn without seeing the internal algorithm.
17. What is method overriding?
When a child class redefines a method of the parent class.
Example: SavingsAccount overrides calculate_interest().
18. What are constructors in Python?
Constructors (__init__()) initialize object attributes.
Example: Initialize employee details at object creation.
19. What are destructors in Python?
Destructors (__del__()) clean up resources when an object is deleted.
Example: Closing file connections automatically.
20. What are dunder (magic) methods?
Special methods like __str__, __add__, and __len__.
Example: __str__() customizes how an object is printed.
Data Handling (File I/O, Pandas, NumPy)
21. How do you read and write files in Python?
Use open(), read(), write(), and with statements.
Example:
with open("log.txt", "w") as f:
f.write("Log entry")
22. What is Pandas in Python?
A library for data analysis and manipulation.
Example: Load a CSV file into a DataFrame for analysis.
23. What is NumPy used for?
NumPy is used for numerical computing with arrays.
Example: Vector and matrix operations in machine learning.
24. Difference between Python list and NumPy array?
- List: General-purpose, slower
- NumPy Array: Optimized, supports vectorized operations
Example: NumPy array multiplied by 2 is faster than a list comprehension.
25. How do you handle missing values in Pandas?
Use dropna() and fillna().
Example: Replace missing ages with the median value.
26. What are DataFrames in Pandas?
A DataFrame is a 2D tabular data structure with labeled axes.
Example: Customer data stored in rows/columns.
27. What is groupby in Pandas?
Groups data for aggregation.
Example: Group sales data by region to calculate totals.
28. How do you merge DataFrames in Pandas?
Use merge(), concat(), or join().
Example: Combine website analytics with CRM data.
29. What is broadcasting in NumPy?
Applying operations between arrays of different shapes.
Example: Adding a scalar to all elements of an array.
30. What is vectorization in NumPy?
Replacing loops with array operations.
Example: Squaring elements of an array using array**2.
Python Libraries & Visualization
31. What is Matplotlib used for?
Matplotlib is a data visualization library for creating charts and plots.
Example: A line chart of monthly sales.
32. What is Seaborn?
Seaborn is a statistical visualization library built on top of Matplotlib.
Example: A heatmap for a correlation matrix.
33. What is scikit-learn?
A machine learning library in Python.
Example: Logistic regression for churn prediction.
34. What is TensorFlow?
A deep learning framework.
Example: Image classification using neural networks.
35. What is the difference between NumPy and Pandas?
- NumPy: Numerical computing
- Pandas: Tabular data analysis
Example: Use NumPy for matrix operations, Pandas for sales reports.
36. What are Python virtual environments?
Isolated environments to manage dependencies.
Example: Use venv for project-specific packages.
37. What is pip in Python?
A package installer for Python libraries.
Example: pip install pandas.
38. What is Jupyter Notebook?
An interactive coding/documentation environment.
Example: Used for exploratory data analysis with live charts.
39. What is PySpark?
Python API for Apache Spark, used for big data processing.
Example: Analyze terabytes of logs with PySpark.
40. What is Statsmodels?
A library for statistical modeling.
Example: Regression analysis for price forecasting.
Python Web Development & Frameworks
41. What is Flask?
Flask is a lightweight Python web framework.
Example: Building a REST API for a blog.
42. What is Django?
Django is a high-level Python web framework with an ORM and built-in admin panel.
Example: Instagram runs on Django.
43. What is FastAPI?
A modern, high-performance Python API framework.
Example: Used for real-time microservices.
44. Difference between Flask and Django?
- Flask = lightweight, flexible
- Django = full-stack, batteries included
Example: Small project → Flask; Enterprise app → Django.
45. What are REST APIs in Python?
APIs that allow systems to exchange data using endpoints.
Example: A weather API built with Flask.
46. What is ORM in Django?
Object-Relational Mapping (ORM) maps Python objects to database tables.
Example: User.objects.all() fetches all user records.47. What is middleware in Django?
A processing layer for requests and responses.
Example: Authentication middleware.
48. What is URL routing in Flask?
Mapping URLs to Python functions.
Example: /home route linked to homepage function.49. What are templates in Django?
HTML files with placeholders for dynamic content.
Example: Display a product catalog dynamically.
50. What is WSGI in Python web apps?
Web Server Gateway Interface for communication between web servers and apps.
Example: Gunicorn serving Django apps.
Database & SQL with Python
51. How do you connect Python to a database?
Use libraries like sqlite3, PyMySQL, or SQLAlchemy.
Example: Fetch sales data from MySQL.
52. What is SQLAlchemy?
An ORM for managing databases in Python.
Example: Store user data without writing SQL manually.
53. How do you execute SQL queries in Python?
Use cursor.execute() with a database connection.
Example: Select the top 10 products by sales.
54. How do you handle transactions in Python DB?
Use commit and rollback operations.
Example: Rollback on failed payment transaction.
55. Difference between SQL and NoSQL in Python?
- SQL = structured data
- NoSQL = flexible/unstructured data
Example: MongoDB for product reviews.
56. What is SQLite in Python?
A lightweight embedded database.
Example: Mobile apps use SQLite for local storage.
57. How do you prevent SQL injection in Python?
Use parameterized queries.
Example:
cursor.execute("SELECT * FROM users WHERE id=?", (id,))
58. What is a cursor in DB operations?
A pointer for fetching query results.
Example: Iterate rows with cursor.fetchall().
59. What is connection pooling?
Reusing database connections for efficiency.
Example: Django manages connection pooling automatically.
60. What is MongoDB with Python (PyMongo)?
A library for interacting with MongoDB, a NoSQL database.
Example: Store JSON-like documents in MongoDB.
Python for Automation & Scripting
61. How do you automate tasks in Python?
Write scripts using libraries like os, shutil, and schedule.
Example: Automating daily backups.
62. What is Python scripting used for?
Automating repetitive tasks.
Example: Bulk renaming files.
63. What is Selenium with Python?
A web automation and testing library.
Example: Auto-login to websites.
64. What is BeautifulSoup?
A library for web scraping.
Example: Extract product reviews from an e-commerce site.
65. What is Requests in Python?
A library for making HTTP requests.
Example: Fetching JSON data from an API.
66. What is Paramiko?
A library for SSH automation.
Example: Automating server file transfers.
67. What is Python’s subprocess module?
A module to run system commands.
Example: Automating shell scripts with Python.
68. What is logging in Python?
Capturing logs for debugging and monitoring.
Example: Record API call errors.
69. What is Python’s os module?
A module for interacting with the operating system.
Example: Creating directories programmatically.
70. What is multithreading in Python?
Running multiple tasks simultaneously within a process.
Example: Downloading multiple files in parallel.
Python Advanced Concepts & ML
71. What is Python’s GIL?
The Global Interpreter Lock (GIL) prevents true parallel threads in CPython.
Example: Use multiprocessing for CPU-bound tasks instead of threading.
72. What is multiprocessing in Python?
A way to run tasks across multiple CPU cores.
Example: Speed up image processing using multiple processes.
73. What is a Python decorator?
A function that modifies another function’s behavior.
Example: Logging execution time of functions with a decorator.
74. What are Python generators?
Functions that use yield for lazy iteration.
Example: Generate Fibonacci numbers on demand.
75. What is Python’s iterator protocol?
Objects that implement __iter__() and __next__().
Example: Looping over custom classes.
76. What are Python context managers?
Manage resources using the with statement.
Example: Files close automatically after reading/writing.
77. What is a Python metaclass?
A class of a class that controls class creation.
Example: Used in ORMs to define custom model behaviors.
78. What is unit testing in Python?
Testing individual components of code.
Example: Testing a login function with unittest.
79. What is pytest?
A popular Python testing framework.
Example: Automating API test cases.
80. What is Python’s asyncio?
A library for asynchronous programming to handle concurrency.
Example: Handling thousands of concurrent web requests.
Scenario-Based & Curveball Python Questions
81. Your Python script is slow. How do you optimize it?
Profile the code, use NumPy, multiprocessing, or caching.
Example: Replace loops with NumPy vectorization.
82. Your code breaks due to version conflicts. Solution?
Use virtual environments and requirements.txt.
Example: Fixed Pandas version mismatch.
83. Your Python script crashes with memory errors. What do you do?
Use generators, chunk processing, or Dask.
Example: Processed a 1GB CSV in smaller chunks.
84. Python web app is slow. How do you fix it?
Optimize database queries, caching, and async processing.
Example: Used Redis caching to reduce load time.
85. Your ML model overfits. How do you fix it?
Apply regularization, dropout, and cross-validation.
Example: Used k-fold cross-validation for model evaluation.
86. API call fails in Python script. What do you do?
Implement retry logic and exception handling.
Example: Exponential backoff retries for unstable APIs.
87. How do you debug Python errors?
Use logging or print statements.
Example: Debugged API issues with pdb.set_trace().
88. How do you deploy a Python app?
Use Docker and cloud platforms like AWS or Heroku.
Example: Deployed a Flask app on AWS Elastic Beanstalk.
89. You need to analyze 1B rows in Python. What’s your approach?
Use PySpark, Dask, or Google BigQuery.
Example: Processed terabytes of clickstream data with PySpark.
90. Your Python script must run daily. How do you schedule it?
Use cron (Linux) or Task Scheduler (Windows).
Example: Automated daily report generation via cron job.
Python Interview Curveballs
91. Why is Python slower than C?
Because it’s interpreted, dynamically typed, and has GIL overhead.
Example: Speed-critical code is moved to Cython.
92. Can Python run on mobile devices?
Yes, but with limited support (not native).
Example: Kivy framework used for mobile apps.
93. Why does Python use dynamic typing?
It allows flexibility and faster prototyping but can cause runtime errors.
Example: A bug occurs if a string is passed instead of a number.
94. Why is Python good for AI/ML?
Simple syntax plus a vast ecosystem of ML libraries.
Example: TensorFlow and scikit-learn are widely used.
95. What is pickling in Python?
Serializing objects using the pickle module.
Example: Save ML models for later reuse.
96. What is monkey patching in Python?
Modifying classes or methods at runtime.
Example: Adding a method dynamically to a library class.
97. What is duck typing in Python?
Type depends on behavior, not inheritance.
Example: If it walks and quacks like a duck, it’s treated as a duck.
98. What is the difference between shallow copy and deep copy?
- Shallow Copy: Copies references
- Deep Copy: Copies entire objects
Example: Duplicating nested lists requires deepcopy().
99. What is Python’s garbage collection?
Automatic memory management using reference counting and cyclic GC.
Example: Unused objects are deleted automatically.
100. Describe a challenging Python project you handled.
Explain the project context, challenges, solutions, and outcomes.
Example: Migrated legacy ETL scripts to Python-based pipelines, reducing runtime from 5 hours to 30 minutes.
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