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200+ Python Interview Questions
Instructor: Richa Sinha
Language: English
Validity Period: 365 days
₹1699 52% OFF
₹799
This is the ultimate resource for developers looking to go beyond syntax and truly understand how Python works in real-world systems and interviews. It's perfect for mid-to-senior developers preparing for challenging roles in backend, data engineering, cloud, and systems design—or for interviewers building a top-tier question bank.
Key Highlights
- Extensive collection of Python interview questions: Over 200 meticulously curated questions spanning fundamental to highly advanced concepts. We cover edge cases, common pitfalls, and challenging real-world scenarios.
- Expert tips on how to approach interview questions: Learn battle-tested strategies for dissecting complex problems, brainstorming efficient solutions, optimizing for performance, and articulating your thought process clearly and confidently to interviewers.
- In-depth explanations and optimal solutions: Every question comes with detailed explanations that clarify the underlying concepts and demonstrate Pythonic, efficient, and robust solutions. Understand why a solution works, not just how.
- Focus on real-world applicability: Questions are designed to simulate actual interview challenges and practical development problems you'll encounter in modern software engineering roles.
- Boost your confidence: Practice with a wide range of questions and solidify your understanding, reducing interview anxiety and significantly enhancing your performance.
- Flexible Learning Formats: Access the content in multiple convenient formats, including PDF for offline study, interactive HTML, a structured Notion database, or LMS-ready files for seamless integration into your preferred learning environment.
What You’ll Learn
This resource meticulously covers critical areas of advanced Python development, ensuring you're prepared for any technical challenge:
🐍 Core Python Mastery Dive deep into the intricacies of closures, decorators, descriptors, and gain a profound understanding of Python's memory model and the impact of __slots__. Explore the Python data model and its internals, including the lifecycle methods like __new__ and __init__.
🧱 Object-Oriented & Functional Programming Master advanced concepts like inheritance, composition, metaclasses, and the Method Resolution Order (MRO). Explore functional programming paradigms, including lambdas, higher-order functions, and the principles of immutability.
⚙️ Concurrency & Async Unravel the complexities of asyncio, multithreading, and multiprocessing. Get a clear understanding of the Global Interpreter Lock (GIL), event loops, futures, coroutines, and how to build responsive applications.
🛠️ Debugging & Performance Learn to leverage powerful profiling tools like cProfile, tracemalloc, and line_profiler to identify and eliminate performance bottlenecks. Understand common performance anti-patterns and how to write highly optimized Python code.
☁️ Cloud, DevOps & Packaging Explore Python's crucial role in cloud environments, including serverless functions with AWS Lambda, containerization with Docker, and establishing robust CI/CD pipelines. Grasp modern dependency management with pip-tools and Poetry, and learn the process of publishing packages to PyPI.
📦 Real-World System Design in Python Tackle advanced topics in designing scalable and resilient Python applications, including architecting microservices, implementing task queues, developing effective caching strategies, and building streaming pipelines. Master best practices for logging, monitoring, scaling, and ensuring fault tolerance in production systems.
Who This Is For
- Mid-to-senior Python developers preparing for top-level interviews at leading tech companies.
- Backend and DevOps engineers who need to solve real-world scale challenges and build robust systems.
- Hiring managers and interviewers looking to create comprehensive and effective technical assessments.
- Advanced learners who are serious about deepening their practical Python expertise and understanding the language's nuances.
What You’ll Get
- 200+ thoughtfully grouped questions across 30+ key topics, organized for logical progression and efficient learning.
- Real-world scenarios, challenging edge cases, and comprehensive system-level problem sets to test your practical application of knowledge.
- Structured and scalable format that's perfect for both individual study and team-based interview preparation.
Serious About Python?
This isn't just interview prep—it's a deep dive into the skills that matter most in production and will set you apart as a truly proficient Python developer. Invest in your career and elevate your Python expertise today.
| Core Python Concepts | |||
| Difference between == and is in Python | |||
| Explain Python’s memory management and garbage collection | |||
| What is the LEGB rule in Python? | |||
| Explain the difference between deep copy and shallow copy | |||
| What are Python’s data model (dunder) methods? | |||
| What are generators and how do they differ from iterators? | |||
| What is the Global Interpreter Lock (GIL)? | |||
| What is the purpose of the __new__() method? | |||
| Explain Python's with statement | |||
| What are closures in Python? | |||
| Object-Oriented Programming (OOP) | |||
| What is the difference between a class method and a static method? | |||
| How is inheritance implemented in Python? | |||
| How does multiple inheritance work? | |||
| What is method resolution order (MRO)? | |||
| What is encapsulation and abstraction? | |||
| How is polymorphism implemented in Python? | |||
| What are metaclasses? | |||
| What are descriptors in Python? | |||
| What is monkey patching? | |||
| What is __slots__ and when should it be used? | |||
| Functional Programming | |||
| Explain map(), filter(), and reduce() | |||
| What are lambda functions and their limitations? | |||
| What are *args and **kwargs used for? | |||
| What is functools.lru_cache and where is it used? | |||
| What is a closure? | |||
| How do decorators work? | |||
| What is the difference between a decorator function and a Decorator Pattern? | |||
| What are first-class and higher-order functions? | |||
| Modules, Packaging, and Imports | |||
| Difference between module and package in Python | |||
| What is __init__.py used for? | |||
| What is __main__.py used for? | |||
| What is the purpose of __all__? | |||
| How does Python's import mechanism work? | |||
| How do you structure a large Python project? | |||
| How do you publish a package to PyPI? | |||
| What’s the difference between setup.py, pyproject.toml, and requirements.txt? | |||
| What is tox used for? | |||
| File Handling and I/O | |||
| How do you read a file line-by-line? | |||
| How do you read/write CSV and JSON files? | |||
| What’s the difference between binary and text mode? | |||
| How do you handle large files in Python? | |||
| What are common file I/O exceptions? | |||
| What are context managers? | |||
| Error Handling | |||
| How does Python handle exceptions? | |||
| Difference between raise, try, and assert | |||
| How do you create custom exceptions? | |||
| What is the use of finally? | |||
| What are context managers and how are they implemented? | |||
| Data Structures | |||
| Differences: list vs tuple vs set vs dict | |||
| How do you implement a stack/queue in Python? | |||
| What are namedtuples? | |||
| How do you sort a dictionary by values? | |||
| What’s in the collections module? | |||
| When should you use a defaultdict or Counter? | |||
| Concurrency and Parallelism | |||
| Differences: threading, multiprocessing, asyncio | |||
| How does the GIL affect multithreading? | |||
| What is an event loop? | |||
| How do you prevent race conditions? | |||
| How do asyncio.gather() and asyncio.create_task() differ? | |||
| Difference between coroutine and generator | |||
| How do you use concurrent.futures? | |||
| Advanced Topics & Internals | |||
| How does Python compile and run code? | |||
| What are .pyc files? | |||
| How do you inspect bytecode in Python? | |||
| What is the dis module? | |||
| What are interned strings? | |||
| What is __dict__ in Python objects? | |||
| How do you dynamically create a class? | |||
| What are weak references? | |||
| How does memory allocation work in Python? | |||
| Performance and Optimization | |||
| How do you identify bottlenecks in code? | |||
| When should you use NumPy or Cython? | |||
| What is lazy evaluation? | |||
| What is timeit and when to use it? | |||
| How do you reduce memory usage in Python? | |||
| What are memory profiling tools (tracemalloc, memory_profiler)? | |||
| How does caching work (lru_cache, custom caching)? | |||
| How does garbage collection work in Python? | |||
| Testing and Debugging | |||
| What is unit testing? | |||
| Difference between unittest and pytest | |||
| How do you mock dependencies? | |||
| How do you test async functions? | |||
| How do you do test coverage analysis? | |||
| What are assertions in testing? | |||
| How do you use pdb for debugging? | |||
| Static Typing and Linting | |||
| What is type hinting in Python? | |||
| What are Protocols (PEP 544)? | |||
| How do you use mypy? | |||
| What is the difference between flake8, black, pylint, and isort? | |||
| How do linters and formatters differ? | |||
| How do you type hint a dictionary with fixed structure? | |||
| Design Patterns in Python | |||
| Implement Singleton pattern | |||
| What is the Factory pattern? | |||
| Strategy pattern using functions | |||
| Observer pattern implementation | |||
| What are common Pythonic patterns? | |||
| Web and APIs | |||
| How do you make HTTP requests? | |||
| Difference between requests, httpx, and urllib | |||
| How to handle retries and timeouts? | |||
| How do you build an API with Flask or FastAPI? | |||
| How do you parse JSON and XML in Python? | |||
| Databases and ORMs | |||
| How do you connect to a SQL database? | |||
| What is an ORM? Use SQLAlchemy/Django ORM | |||
| How do you avoid SQL injection? | |||
| How do you bulk insert millions of records? | |||
| How to handle transactions in Python? | |||
| Security in Python | |||
| How do you store passwords securely? | |||
| Common web security issues in Python apps | |||
| How do you use hashlib or bcrypt? | |||
| How do you encrypt/decrypt data in Python? | |||
| How do you manage secrets in production apps? | |||
| Deployment and Production | |||
| How do you use Docker with Python? | |||
| How do you monitor a Python application in production? | |||
| What are common logging practices? | |||
| How do you configure a production-ready FastAPI app? | |||
| What are the benefits of using gunicorn or uvicorn? | |||
| Metaprogramming and Reflection | |||
| What is metaprogramming? | |||
| Use of getattr, setattr, hasattr | |||
| What is the inspect module used for? | |||
| How do you modify a class at runtime? | |||
| Use of reflection and introspection | |||
| When to use metaclasses? | |||
| Interfacing with Other Languages | |||
| How to use ctypes or cffi for C/C++? | |||
| What is Cython? | |||
| How to embed Python in another application? | |||
| How do you run shell commands in Python? | |||
| Difference between os.system, subprocess.run, and shlex? | |||
| Architecture and Large-Scale Systems | |||
| How to design a background task queue? | |||
| Tools for handling high-throughput APIs in Python | |||
| How do you implement caching (Redis/Memcached)? | |||
| How to scale Python microservices? | |||
| How do you handle configuration across environments? | |||
| Data Engineering and ML Integration | |||
| How do you preprocess large datasets in Pandas? | |||
| How do you handle missing data efficiently? | |||
| Use of joblib in ML pipelines | |||
| Difference between NumPy and Pandas memory models | |||
| How to deploy ML models with FastAPI? | |||
| Miscellaneous and Tricky Questions | |||
| What happens if you use a mutable default argument in a function? | |||
| Explain __eq__() and when to override it | |||
| What is duck typing? | |||
| What are Python anti-patterns to avoid? | |||
| How do you dynamically import a module or function? | |||
| How do you handle circular imports? | |||
| How do you create plugin-based systems in Python? | |||
| What is the role of the signal module? | |||
| How do contextvars differ from thread-locals? | |||
| What are abstract base classes? | |||
| Real-World System Design with Python | |||
| How would you build a distributed task queue in Python? | |||
| What Python libraries are suitable for pub/sub systems? | |||
| How would you design a real-time chat application in Python? | |||
| How would you integrate a message broker (RabbitMQ/Kafka) in Python? | |||
| What’s your approach to scaling Python services horizontally? | |||
| Python in the Cloud and DevOps | |||
| How do you write Python code for AWS Lambda? | |||
| What are cold starts in serverless Python functions? | |||
| How do you manage secrets in AWS/GCP with Python? | |||
| How do you deploy a FastAPI app with Docker + ECS or Kubernetes? | |||
| How do you schedule and monitor Python cron jobs in production? | |||
| What’s the best way to log from Python apps running in containers? | |||
| How can Python be used for infrastructure-as-code (e.g. Pulumi)? | |||
| How do you monitor memory/cpu/network of a Python app in the cloud? | |||
| Data Pipelines and Streaming in Python | |||
| How do you handle backpressure in data pipelines with Python? | |||
| What are some libraries for stream processing in Python? | |||
| How do you process real-time logs with Python? | |||
| What’s your strategy to handle schema evolution in Python ETL jobs? | |||
| How do you checkpoint or recover a failed ETL job in Python? | |||
| Edge Cases and Debugging Nightmares | |||
| Why can comparing two NaN values be tricky in Python? | |||
| What happens when you mutate a set while iterating over it? | |||
| What’s the output of [] is [], and why? | |||
| Why might a generator be exhausted unexpectedly? | |||
| What causes a RuntimeError: dictionary changed size during iteration? | |||
| Python Ecosystem Tools | |||
| What’s the role of pip-tools? | |||
| How do you freeze a requirements file for exact reproducibility? | |||
| Difference between virtualenv, venv, and conda? | |||
| What is Poetry and how is it better than pipenv? | |||
| How do you manage dependency conflicts in Python projects? | |||
| Packaging for Distribution | |||
| How do you bundle a Python CLI tool? | |||
| What is zipapp and how can it help? | |||
| How do you package and publish Python wheels? | |||
| What is a namespace package in Python? | |||
| What is twine used for? | |||
| APIs, Serialization, and Data Contracts | |||
| Difference between pydantic and marshmallow | |||
| How do you define a schema in FastAPI using Pydantic? | |||
| How do you validate nested schemas in Python? | |||
| How do you serialize and deserialize with pickle safely? | |||
| Why should pickle not be used over a network? | |||
| Soft Skills & Python Coding Practices | |||
| How do you write Python code that is easy to test? | |||
| How do you structure modules in a maintainable way? | |||
| What is Pythonic code? | |||
| How do you write documentation that scales with a Python project? | |||
| What are good code review practices for Python teams? | |||
| Python with AI/ML/DL Ecosystem | |||
| How do you serve a PyTorch or TensorFlow model via REST API? | |||
| What is the difference between joblib and pickle for model persistence? | |||
| What is ONNX and how do you use it in Python? | |||
| How do you write custom data loaders in PyTorch? | |||
| What’s your strategy for hyperparameter tuning with Python? | |||
| Python Security Deep Dive | |||
| How do you securely deserialize Python objects? | |||
| What are common Python vulnerabilities in web apps? | |||
| What is SSRF and how can it affect Python APIs? | |||
| How do you validate user inputs in Python web backends? | |||
| How do you prevent DoS attacks in Python-powered endpoints? | |||
| Download PDF | |||
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