Refer to the previous code in which we added an element to the list using append() This is how we can visualize the over-allocation concept of CPython. Looking for info on Python's memory allocation - Python Python uses a lot of small objects that get created and destroyed frequently, and calling malloc () and free () for each one introduces significant overhead. Python List In arrays, memory is continuous. Python’s PVM will take care of such issues. The following code creates a list of large integers: [code] lst = [1000000] * 200. for i in range (0,200): lst [i] = i + 1000000. print (lst [0]) [/code] and this code requires 1200 bytes of heap memory, which means the 200-element list uses only 800 bytes (4 bytes per element). If a tuple no longer needed and has less than 20 items instead of deleting it permanently Python moves it to a free list.. A free list is divided into 20 groups, where each group represents a list of tuples of length n between 0 and 20. Improving Python's Memory Allocator - Evan Jones Memory Allocation — Cython 3.0.0a10 documentation Instead, the Python interpreter holds on to it, and will reuse it as needed. ls = [] takes 72 bytes For these objects to be useful, they need to be stored in the memory to be accessed. As I have mentioned, I don't know final length of the list, but Python Memory Management: The Essential Guide - Scout APM We can delete that memory whenever we have an unused variable, list, or array using these two methods. Sets are the unordered collection of data types in Python, which are mutable and iterable. The list object consists of two internal parts; one object he...