In Python,

A binary heap is conceptually thought of as a tree with two special properties: 1. A shape property - the binary heap is an almost complete binary tree (where each level of the tree has the maximum number of nodes possible, with the exception of the lowest level which is filled with nodes from left to right 2. An order property - a partial ordering over the nodes where the key at every parent node is less than or equal to both of its children An effective way to implement a binary heap is to use an underlying array. An advantage of this approach is that for any value in the array (at index x) we can very quickly compute the index of both of its children (x 2 and x * 2 +1) and its parent (x // 2). An example is illustrated below: parent 0 123 456 789 10 11 children Define a function called min_child0 which takes an index value and a Python list as input. The function should return the index position of the smaller of the two children of the value at position index in the list. If the index position provided represents a value that does not have any children, then the function should return None. For example: Test Result print(minchild(4, [0, 6, 7, 8, 9, 22, 45, 12, 16, 27, 36, 35])) 8 print(min_child(1, [0, 6, 7, 8, 9, 22, 45, 12, 16, 27, 36, 35])) 2 print(min_child(2, [0, 6, 7, 8, 9, 22, 45, 12, 16, 27, 36, 35])) 4 print(min child(3, [0, 6, 7, 8, 9, 22, 45, 12, 16, 27, 36, 35])) 7