Q1: How does Python manage memory?

Python uses a Private Heap space for all its objects and data structures. It employs two primary mechanisms:

• Reference Counting: Increments when an object is referenced and decrements when dereferenced.
• Generational Garbage Collection: Scans for circular references that reference counting misses.

Q2: Explain the Global Interpreter Lock (GIL).

The GIL is a mutex that allows only one thread to execute Python bytecode at a time. This simplifies memory management but limits true parallelism in CPU-bound multithreaded tasks.

Q3: What are Decorators and how do they work?

Decorators are a tool for wrapping a function with another function to extend its behavior without modifying the source code.

Q4: Deep Copy vs Shallow Copy?

A Shallow Copy creates a new object but inserts references to the original nested objects. A Deep Copy creates a new object and recursively clones all nested objects.

Q5: What is Method Resolution Order (MRO)?

MRO defines the order in which Python searches for a method in a hierarchy of classes, using the C3 Linearization algorithm.

Q6: Why use `__slots__`?

Using `__slots__` prevents the creation of `__dict__` for each instance, drastically reducing memory usage for classes with millions of instances.