Python Expertise: Senior Developer Questions and Answers

Core Python Concepts

What is the main difference between
1. deep copy and shallow copy?
2. ExplanationPython’s memory management model.
3. How do Python’s data structures (lists, tuples, sets, dictionaries) differ in terms of performance and usefulness?
4. What is the difference between is and == in Python?
5. ExplanationGlobal Interpreter Lock (GIL)and its effects.
6. How to implement Multiple inheritance in Python?
7. What are metaclasses and when would you use them?
8. Explains the decorator and provides examples of its usage.
What is the difference between
9. Iterable Object and Iterator?
10. How does Python's garbage collector work?

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Advanced Programming

1. Explanation of Context managers and how to create a custom context manager.
2. How do you implement the Singleton pattern in Python?
3. What are coroutines and how do they differ from generators?
4. Explain the concept of monkey patching in Python.
5. How do you optimize the performance of your Python code?
6. What is duck typing and how is it used in Python?
7. ExplanationAbstract Base Class (ABC)and its purpose.
What is the difference between
8. @staticmethod, @classmethod and instance methods?
9. How do you create thread-safe code in Python?
10. What are slots and how do they improve memory usage?

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Performance optimization

1. How do you identify and fix bottlenecks in Python code?
2. What tools do you use to analyze Python code?
3. Explains the trade-offs between NumPy and pure Python.
4. How do you use list comprehensions to optimize your code?
5. What is Cython and how does it improve performance?
6. How do you handle large data processing in Python?
7. What is lazy evaluation and how does it improve performance?
8. Explain the impact of mutable objects and immutable objects on performance.
9. How do you optimize I/O bound tasks in Python?
10. What is vectorization and how does it improve computational efficiency?

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Concurrency and Parallelism

What is the difference between
1. thread, multi-process and asyncio?
2. How do you avoid race conditions in multi-threaded Python programs?
3. Explanationasync/await and its use cases.
4. What is the role of queue module in concurrency?
5. How do you implement the producer-consumer pattern in Python?
6. concurrent.futuresHow do modules simplify concurrent programming?
7. Explain the concept of event loop in Python.
8. What are the limitations of GIL and how do you overcome them?
9. How do you use semaphores to manage resources?
10. Explain the concept of task scheduling in asyncio.

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Data Science and Libraries

What is the difference between
1. Pandas Series and DataFrame?
2. How do you handle missing data in Pandas?
3. What is the core difference between NumPy arrays and Python lists?
What is the difference between
4. matplotlib and seaborn?
5. What are the main benefits of using SciPy instead of NumPy?
6. ExplanationHow Scikit-learn handles feature scaling.
7. How does Python handle large-scale machine learning tasks?
8. What are TensorFlow and PyTorch, and when would you use them?
9. ExplanationDask and its role in parallel computing.
10. How do you implement a data pipeline in Python?

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Security and Best Practices

1. How do you prevent SQL injection in Python?
2. hashlibWhat is the role of hashlib in data security?
3. How do you securely store API keys in a Python application?
4. What is the purpose of the secrets module ?
5. How do you mitigate buffer overflows in Python?
6. What is Input Validation and how do you implement it?
7. Explains the role of SSL/TLS in securing Python applications.
8. How do you prevent injection attacks in Python web applications?
9. What is CSRF and how to prevent it in Python web framework?
10. How do you handle data encryption in Python?

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Testing and Debugging

What are the main differences between
1. unittest and pytest?
2. How do you write parameterized tests in Python?
3. Explain the purpose of mock in unit testing.
4. pdbHow to simplify debugging in Python?
5. What is the role of doctests in Python testing?
6. How do you measure code coverage in Python?
7. assertWhat is the role of keywords in debugging?
8. How do you use Profiling Tools to debug performance issues?
9. What is Unstable Testing and how do you mitigate it?
10. How do you debug memory leaks in a Python application?

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Real world challenges and scenarios

1. How do you design a Python microservices architecture?
2. What are the challenges of processing real-time data in Python?
3. How do you deploy Python applications in a serverless environment?
4. What are the best practices for handling large-scale logging in Python?
5. How do you manage dependency conflicts in a Python project?
6. How do you scale Python applications in a containerized environment?
7. How do you handle dynamic configuration in Python?
8. What are the best practices for CI/CD pipelines in Python projects?
9. How do you manage data consistency in a distributed system in Python?
10. How do you implement fault-tolerant applications using Python?

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