Ultimate Python interview questions for Intermediate Level Python Programmer.

1. Question: What is metaprogramming in Python? Answer: Writing programs that treat other programs as data, using metaclasses, decorators, and the type() function.
2. Question: How does the Global Interpreter Lock (GIL) affect multi-threaded programs in Python? Answer: Limits execution to one thread at a time, hindering multi-threading performance on multi-core systems.
3. Question: Difference between deepcopy() and copy() in Python? Answer: deepcopy() creates independent copies, while copy() makes a shallow copy, sharing nested objects.
4. Question: How to implement a Singleton pattern in Python? Answer: Use a metaclass or modify the class’s __new__ method.
5. Question: What are descriptors in Python? Answer: Objects that define attribute access behavior via methods like __get__(), __set__(), and __delete__().
6. Question: Explain closures in Python. Answer: Functions that retain access to their environment variables after the outer function has finished executing.
7. Question: Purpose of the yield keyword in Python? Answer: Creates generator functions that yield items one at a time, maintaining state between iterations.
8. Question: Difference in memory management between Python and C/Java? Answer: Python uses reference counting and garbage collection, while C requires manual management, and Java relies solely on garbage collection.
9. Question: How to optimize Python program performance? Answer: Use built-in libraries, list comprehensions, minimize globals, multi-threading/multi-processing, and profiling tools.
10. Question: What is the __slots__ attribute? Answer: Limits attributes of a class to reduce memory overhead by avoiding a __dict__ for each instance.
11. Question: How does the asyncio library work? Answer: Provides a framework for writing concurrent code with coroutines, enabling asynchronous I/O operations.
12. Question: Explain method resolution order (MRO). Answer: Determines the order of base class search during method execution, using the C3 linearization algorithm.
13. Question: How to handle circular imports in Python? Answer: Avoid circular dependencies, use import statements inside functions, or lazy imports.
14. Question: What are context managers? Answer: Manage resource allocation and release with with statement, defining __enter__ and __exit__ methods.
15. Question: Difference between threading and multiprocessing? Answer: Threading shares memory within a process; multiprocessing uses separate memory spaces for each process.
16. Question: How does the inspect module work? Answer: Provides functions to get information about live objects like modules, classes, and methods.
17. Question: How to ensure thread safety in Python? Answer: Use synchronization primitives like locks, semaphores, and thread-safe data structures.
18. Question: What is monkey patching? Answer: Modifying or extending a module/class at runtime, usually for testing or quick fixes.
19. Question: Explain duck typing in Python. Answer: Type determined by the presence of methods/properties, not actual type. "If it looks like a duck..."
20. Question: How does the property decorator work? Answer: Defines methods that act like attributes, enabling getter, setter, and deleter functions.
21. Question: What are weak references? Answer: References that do not prevent garbage collection, useful for memory management in certain scenarios.
22. Question: Explain memoization. Answer: Caches the results of expensive function calls, returning the cached result for repeated inputs.
23. Question: How to use the subprocess module? Answer: Spawns new processes, connects to their I/O pipes, and manages return codes for system commands.
24. Question: How does the pickle module work? Answer: Serializes and deserializes Python objects for saving and loading from files or byte streams.
25. Question: Use of metaclasses? Answer: Classes of classes that define class behavior, allowing customization of class creation.
26. Question: Difference between is and ==? Answer: is checks object identity; == checks value equality.
27. Question: How to implement a coroutine? Answer: Use async def to define and await to handle asynchronous functions.
28. Question: Purpose of async and await? Answer: Define and manage asynchronous functions and operations for concurrent execution.
29. Question: How to use the heapq module? Answer: Maintains a heap-based priority queue, with functions for pushing/popping elements and merging heaps.
30. Question: How does the __call__ method work? Answer: Allows class instances to be called like functions by defining this method.
31. Question: Use of the functools module? Answer: Provides higher-order functions that act on/return other functions, like partial and reduce.
32. Question: Explain Answer: Creates a new function with partial application of the given arguments and keywords.
33. Question: What are Python decorators? Answer: Functions or classes that modify the behavior of other functions or methods.
34. Question: How does method overloading work in Python? Answer: Python does not support method overloading; use default arguments or variable arguments instead.
35. Question: Explain the use of super() function. Answer: Calls a method from the parent class, used to access inherited methods that have been overridden.
36. Question: What is the use of the __main__ module? Answer: Allows a module to be run as a standalone program by checking if __name__ == '__main__':.
37. Question: How does garbage collection work in Python? Answer: Automatically reclaims memory by destroying objects that are no longer in use.
38. Question: Explain the purpose of __repr__ and __str__. Answer: __repr__ provides an official string representation; __str__ provides a readable string representation.
39. Question: How does type hinting work in Python? Answer: Provides optional type information using annotations, improving code readability and assisting with static analysis tools.
40. Question: What are the benefits of using dataclasses? Answer: Simplifies the creation of classes by generating special methods like __init__(), __repr__(), and __eq__().
41. Question: What is the collections module? Answer: Provides specialized container datatypes like namedtuples, deque, Counter, OrderedDict, and defaultdict.
42. Question: How to handle large datasets efficiently in Python? Answer: Use generators, memory-mapped files, or libraries like NumPy and pandas for efficient data handling.
43. Question: What is the itertools module? Answer: Provides functions for creating iterators for efficient looping, like count, cycle, repeat, and more.
44. Question: Explain the purpose of the abc module. Answer: Defines abstract base classes, providing a way to define interfaces when creating object-oriented programs.
45. Question: What is the use of the enum module? Answer: Provides a way to define enumerations, which are symbolic names bound to unique, constant values.
46. Question: How does the timeit module work? Answer: Measures the execution time of small code snippets for performance testing.
47. Question: What is the purpose of the logging module? Answer: Provides a flexible framework for emitting log messages from Python programs.
48. Question: How does the argparse module work? Answer: Parses command-line arguments and options, providing a user-friendly interface for script configuration.
49. Question: What is the __future__ module? Answer: Imports features from future versions of Python, allowing compatibility and gradual transitions.
50. Question: How to work with JSON data in Python? Answer: Use the json module to parse JSON strings into Python dictionaries or lists with json.loads(), and to convert Python objects into JSON strings with json.dumps(). To read and write JSON files, use json.load() and json.dump().