Here are some common Python interview questions that span a range of topics:
Basic Questions
General Python Knowledge
- Difference between List and Tuple: How do lists and tuples differ in Python, and when might you choose to use one over the other?
- Mutability: What does it mean for an object to be mutable? Can you give examples of mutable and immutable objects?
- List Comprehensions: Can you provide an example of a list comprehension and explain how it works?
- Memory Management: How does memory management work in Python? What is garbage collection?
- Global and Local Variables: Explain the difference between global and local variables in Python.
Data Structures
- Dictionaries: How do you merge two dictionaries in a single expression?
- Sets: How can you remove duplicate elements from a list using sets?
- Data Types: Can you name and describe the standard data types in Python?
- Lambda Functions: Provide an example where a lambda function can be useful.
Object-Oriented Programming
- Classes/Objects: How are classes and objects related?
- Inheritance: How can a subclass be derived from a base class in Python?
- Encapsulation: Explain how encapsulation is implemented in Python.
- Polymorphism: How is polymorphism implemented in Python?
Web Development
- Flask and Django: What are the main differences between Flask and Django?
- HTTP Methods: What is the difference between the GET and POST HTTP methods?
Testing
- Unit Testing: How is unit testing performed in Python?
- Mocking: How and why might you use mocking in testing Python applications?
Concurrency and Parallelism
- Threads: How is threading implemented in Python, and what are its limitations?
- AsyncIO: What is the
asynciomodule used for, and how does it differ from multi-threading?
File Handling
- Reading Files: How do you read from a file in Python?
- Writing to Files: How can you write data into a file?
Error and Exception Handling
- Try/Except: How do you catch exceptions in Python?
- Custom Exceptions: How can you define custom exception classes in Python?
Python Libraries and Frameworks
- NumPy: Why might you choose to use NumPy arrays instead of nested Python lists for numerical computation?
- Pandas: How would you handle missing data in a Pandas DataFrame?
- TensorFlow/PyTorch: Can you name some differences between TensorFlow and PyTorch?
Python 2 vs Python 3
- Differences: Name some key differences between Python 2 and Python 3.
- Migration: What are some challenges when migrating code from Python 2 to Python 3?
PEP 8 and Code Style
- PEP 8: What is PEP 8 and why is it important?
- Docstrings: How should docstrings be formatted according to PEP 257?
Advance Questions
Memory Management and Optimization
- Memory Leaks: How can you identify and prevent memory leaks in Python?
- Object Interning: What is object interning, and how does it work in Python?
Metaprogramming
- Descriptors: How are descriptors used in Python and why might you use them?
- Metaclasses: What is a metaclass, and how/why would you use one?
Concurrency and AsyncIO
- GIL: Explain the Global Interpreter Lock (GIL) and its impact on multi-threaded Python programs.
- Async/await: How does the
async/awaitsyntax work under the hood? - Event Loop: How does the event loop work in an async framework?
Decorators and Generators
- Decorators: How would you implement a decorator that measures the execution time of a function?
- Generators: How do generators work, and how are they different from functions?
Data Structures and Algorithms
- Algorithm Optimization: Can you optimize this algorithm further in terms of time and space complexity?
- Custom Data Structures: How would you implement [specific data structure] from scratch?
Testing
- Test Fixtures: How would you use fixtures in
pytest? - Mock: How do you use the
unittest.mocklibrary to mock objects in unit tests?
Web Development (Flask/Django)
- Middleware: How is middleware implemented in Django or Flask?
- ORM: How does the Django ORM work, and how can queries be optimized?
Database
- Database Connection Pooling: How do you manage database connections and implement connection pooling?
- Normalization: Discuss database normalization and denormalization, and where might denormalization be useful.
Design Principles and Patterns
- Singleton Pattern: How would you implement a singleton pattern in Python?
- Factory Pattern: Can you provide an example of using the Factory design pattern in Python?
Distributed Systems and Scalability
- Scalability: How would you scale a Python web application?
- Caching Strategies: How would you implement caching to improve the performance of a Python application?
Security
- Secure Data Storage: How would you securely store sensitive information in a Python application?
- Input Sanitization: What steps would you take to validate and sanitize user input in a web application?
Python C-API and Extensions
- Cython: How would you use Cython to speed up Python code?
- C Extensions: How can Python be extended with C code, and why might you do this?
Cloud and DevOps
- Docker: How would you containerize a Python application using Docker?
- CI/CD: How would you set up a CI/CD pipeline for a Python application?
Machine Learning
- Model Deployment: How would you deploy a machine learning model developed with Python into production?
- Data Pipelines: How would you design a robust and scalable data processing pipeline?
Remember that advanced questions may also require a demonstration of hands-on coding skills, problem-solving abilities, and a deep understanding of system design principles. Always be prepared to back up your answers with practical examples and experiences.
Bonus: System Design and Algorithms
- Algorithm Complexity: How do you determine and communicate the time and space complexity of an algorithm?
- System Design: How might you design a scalable and robust system using Python (e.g., a web API, a data pipeline, etc.)?
Feel free to adapt these questions to your needs and always be ready to provide or explore practical examples to showcase or enhance understanding!
