Store numeric key and string value in the data structure.

• Time complexity O(1) in most the cases (configurable) worst-case time complexity O(length(Key))

• To retrieve any key's value in O(1) we can directly store the key in the index of the list because our key is numeric so if the key is 10 then we can store it to index number 10. By this implementation, we can get any value in O(1). for example, we have a list of 10 lengths, bucket = [None,None,None,None,None,None,None,None,None,None] initially they all are none if we want to store key=9 and value = "Maserati" we can store directly to 9 index. bucket[9] = "Maserati" so list after inserting 9 key is [None, None,None, None,None, None,None, None,"Maserati", None] and if just get 9th index bucket[9] we can get value Maserati in O(1).
• Trade off this implementation is that we have to create a list before inserting value so if we create a list of 100 length then we can only store keys less than 100 we cant store keys greater than 100 because of fixed list size. to tackle this problem we can create a big list but then this way maybe our storage not be get fully utilized like suppose we create a list of 1 Million of length and if we only storing keys less than 100 and one of key is 5 million then for only 1 key we created 1 million storage our lots of storage get waisted for that key.
• To solve this problem we can compromise some time complexity and save some space, another option is that we can store the keys that are greater than 100(length of the list) in another data structure have decided to store it in trie data structure so we can retrieve and store any key in O(length(Key)) it's more near to O(1) that we want to archive other option is to balanced binary search tree but it has a time complexity of O(log(N)) for insertion and retrieval so have decided to store it to the trie data structure.But if want more space optimised then we can go with BST in trie implementation if any key is greater than list size its get stored in trie. by this we can get most of the keys in O(1) and the remaining keys can we get in O(length(key))
• Have made this list size configurable in makefile if your sure your keys less than some number then you can initialize that size of list there by default it's 100000 if any key is less than 100000 its retrieval and store time complexity is O(1) and keys greater than 100000 retrievals and store time complexity is O(length(key)). so end-user has the choice to configure his list by this he is ready to get everything in O(1) by compromising space and vice-versa
• Assumptions - key will be postive integer

• Make sure you have python2.7 installed
• git clone https://github.com/vaibhav2ghadge/K-V-Data-Structure.git clone the repo
• cd K-V-Data-Structure/
• make run for run program
• Another way is to run program python2.7 main.py 100000
• for insert always enter key in numeric form like 1232 and value be in double quotes like "Mango"