Python Interview Questions and Answers for 10 years experience

1. What are the differences between lists and tuples in Python?

   • Answer: Lists are mutable (changeable), ordered sequences of items, while tuples are immutable (unchangeable), ordered sequences. Lists are defined using square brackets `[]`, while tuples use parentheses `()`. Lists are generally more flexible but tuples offer some performance advantages and are useful when data integrity is crucial.

2. Explain the concept of decorators in Python.

   • Answer: Decorators are a powerful and expressive feature in Python that allows you to modify or enhance functions and methods in a clean and readable way. They use the `@` symbol followed by the decorator function name, placed above the function definition. They essentially wrap another function, adding functionality before or after the original function's execution without modifying its core code. This promotes code reusability and improves readability.

3. What are generators in Python and how are they useful?

   • Answer: Generators are a special type of iterator that produces values on demand, one at a time, instead of generating the entire sequence at once. They are defined using functions with the `yield` keyword. This makes them memory-efficient when dealing with large datasets, as they don't need to store the entire sequence in memory. They are particularly useful for processing large files or streams of data.

4. Describe different ways to handle exceptions in Python.

   • Answer: Python uses `try...except` blocks to handle exceptions. You can specify specific exception types to catch (e.g., `try: ... except FileNotFoundError: ...`), use a general `except` block to catch all exceptions, or use `finally` to execute code regardless of whether an exception occurred. `else` blocks can be added to run code only if no exception was raised. Raising custom exceptions allows for more specific error handling.

5. Explain the concept of metaclasses in Python.

   • Answer: Metaclasses are classes that define the behavior of other classes. They control class creation and allow you to customize how classes are created and initialized. They are powerful but advanced features used for tasks like modifying class attributes, adding methods dynamically, or enforcing coding conventions.

6. What is monkey patching and when might you use it?

   • Answer: Monkey patching is a technique where you modify a class or module at runtime. This is typically used for testing, debugging, or extending existing libraries without modifying their source code directly. While it can be useful, it can also make code harder to maintain and debug if overused. It should be employed cautiously and documented clearly.

7. How do you achieve concurrency in Python?

   • Answer: Python offers several ways to achieve concurrency, including threading and multiprocessing. Threading utilizes multiple threads within a single process, suitable for I/O-bound tasks. Multiprocessing creates multiple processes, ideal for CPU-bound tasks, as it leverages multiple cores. Asynchronous programming using `asyncio` is also becoming increasingly popular for handling concurrent operations efficiently.

8. Explain the Global Interpreter Lock (GIL) in Python.

   • Answer: The GIL is a mechanism in CPython (the standard Python implementation) that allows only one native thread to hold control of the Python interpreter at any one time. This limits true parallelism for CPU-bound tasks in multithreaded programs. However, it simplifies the implementation and avoids complexities associated with managing shared resources across multiple threads simultaneously. Multiprocessing bypasses this limitation.

9. What are the different ways to create a class in Python?

   • Answer: You can create a class using the `class` keyword followed by the class name and a colon. You can define attributes and methods within the class body. You can also use inheritance to create subclasses that inherit attributes and methods from a parent class. Multiple inheritance is supported, but it can lead to complexities if not handled carefully.

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