You now know about O(n) data structures like Arrays LinkedLists, and O(1) data structures like Sets and HashMaps.
Hopefully you have a sense of why Arrays and LinkedLists are "slower" in general - they're storing and using more information! There's a 1st element, a 2nd element, etc, unlike Sets and HashMaps, where elements have no order. Another way of looking at this is that O(n) data structures have more "entropy" than O(1) ones.
In the Binary Search section, you'll learn about O(logn) data structures - the final type of data structure you need to know (and that really exists!).
TreeNode.of
function can be used to create an entire binary tree using 1 line of code. The input is a BFS traversal of the tree including nulls, and the output is the root node of the tree.TreeNode.of([1, None, 2, None, 3])
ListNode.of
function lets you create an entire Linked List using 1 line of code. The input is an array, and the output is the head of the Linked List.ListNode.of([1, 2, 3])
ListNode.of([1, 2, 3], 1)
GraphNode.of
function lets you create an entire Graph using 1 line of code. The input is an Adjacency Matrix, and the output is the first node in the matrix.GraphNode.of([ ['A', 1, 2], ['B', 2], ['C', 0] ])
[['__init__', 15], ['add', 16], ['get']]
c = MyClass(15) c.add(16) c.get()
TreeNode.of
function can be used to create an entire binary tree using 1 line of code. The input is a BFS traversal of the tree including nulls, and the output is the root node of the tree.TreeNode.of([1, None, 2, None, 3])
ListNode.of
function lets you create an entire Linked List using 1 line of code. The input is an array, and the output is the head of the Linked List.ListNode.of([1, 2, 3])
ListNode.of([1, 2, 3], 1)
GraphNode.of
function lets you create an entire Graph using 1 line of code. The input is an Adjacency Matrix, and the output is the first node in the matrix.GraphNode.of([ ['A', 1, 2], ['B', 2], ['C', 0] ])
[['__init__', 15], ['add', 16], ['get']]
c = MyClass(15) c.add(16) c.get()