Swati Saxena

Memory management is the process of efficiently allocating, de-allocating, and coordinating memory so that all the different processes run smoothly and can optimally access different system resources.

This means that the memory manager keeps track of the number of references to each object in the program.

The allocation of Python heap space for Python objects is done by the Python memory manager. The core API gives access to some tools for the programmer to code.

The Python memory manager manages chunks of memory called “Blocks”. A collection of blocks of the same size makes up the “Pool”. Pools are created on Arenas, chunks of 256kB memory allocated on heap=64 pools.

Global variables are defined outside of any module and function. These variables can be accessed by any function in the program. Local variables are defined inside the function where it is used.

The values stored in a list can be accessed using the slice operator ([] and [:]) with indexes starting at 0 at the beginning of the list and working their way to end -1.

The zip() returns an iterator and takes iterable as argument. These iterables can be list, tuple, dictionary etc. It maps similar index of every iterable to make a single entity.

Ans.Python has no inbuilt main function to start the execution of the program. Python has special variable __name__; it provides the functionality of the main function.

The __del__() method is known as a destructor method in Python. It is called when all references to the object have been deleted.

Pillars of OOPs:
Abstraction: To hide complexity and show which is necessary to a current problem scenario.
Encapsulation: Combine data of the similar type of objects into a single unit.