CodeBlanks Logo Icon CodeBlanks
Login Register

What is a tree?

A hierarchical structure of root and child nodes.

What is a tree?

A tree is a hierarchical, acyclic data structure of nodes and edges. There is a root node; each node can have zero or more children.

Nodes close to the root are internal; nodes with no children are leaves. Trees are ideal for representing hierarchical data (file systems, org structures).

A binary tree is a special tree where each node has at most two children.

Node and edge

Each node holds a value and child pointers. In a binary tree there are left and right pointers. An edge is a parent-child link.

A tree with n nodes has n-1 edges (every node except the root has one parent). The height is the number of edges on the longest root-to-leaf path.

In Python a node is usually represented with a class.

Practice Create a node

Write a Node class with val, left, right fields. Print 5 with print(Node(5).val).

Starter code

solution.py
class Node:
    def __init__(self, val):
    # Init node

Sample solution

solution.py
class Node:
    def __init__(self, val):
        # Init node
        self.val = val
        self.left = None
        self.right = None
print(Node(5).val)

Expected output

5

Questions and answers

Review the lesson questions together with their answers. To test yourself, solve the lesson interactively.

1 What is a leaf node?

  • The root node
  • A node with no children Correct answer
  • One with two children
  • The topmost

Explanation: A node with no children

2 Node class

Question 
class Node:
    def __init__(self, val):
        self.val = val
        self.left = ____
        self.right = None
Answer 
class Node:
    def __init__(self, val):
        self.val = val
        self.left = None
        self.right = None

Explanation: None is right.

3 What is a tree: match the terms

Term Meaning
Root Topmost
Leaf No children
Internal Has children
Edge Link

All lessons in Intermediate

1 Merge sort

  1. Divide and conquer
  2. Merge operation
  3. Full merge sort
  4. Summary - Merge sort

2 Quick sort

  1. Pivot selection
  2. Partitioning
  3. Recursive quick sort
  4. Summary - Quick sort

3 Heap sort

  1. What is a heap?
  2. Heapify
  3. Build heap and sort
  4. Summary - Heap sort

4 Counting sort

  1. Counting idea
  2. Count array
  3. Output array
  4. Summary - Counting sort

5 Radix sort

  1. Radix idea
  2. Digit pass
  3. Stable sub-sort
  4. Summary - Radix sort

6 Sorting project

  1. Project: Overview
  2. Score array
  3. Apply merge sort
  4. Print statistics

7 Tree

  1. What is a tree?
  2. Node and edge
  3. Binary tree
  4. Summary - Trees

8 Binary search tree

  1. BST rule
  2. BST insert
  3. BST search
  4. Summary - BST

9 AVL tree

  1. Balanced tree
  2. Rotation
  3. Balance after insert
  4. Summary - AVL tree

10 Heap

  1. Min and max heap
  2. Insert
  3. Extract
  4. Summary - Heap

11 Priority queue

  1. What is a priority queue?
  2. Heap-based implementation
  3. Push and pop
  4. Summary - Priority queue

12 Data structures project

  1. Project: Overview
  2. Undo stack
  3. Pending queue
  4. Print the state

13 Graph basics

  1. What is a graph?
  2. Adjacency list
  3. Adjacency matrix
  4. Summary - Graph

14 Breadth-first search

  1. BFS idea
  2. Using a queue
  3. Marking visited
  4. Summary - BFS

15 Depth-first search

  1. DFS idea
  2. Stack or recursion
  3. Backtracking
  4. Summary - DFS

16 Greedy algorithms

  1. Greedy approach
  2. Coin change
  3. Greedy limits
  4. Summary - Greedy

17 Divide and conquer

  1. Three steps
  2. Recursive structure
  3. Master theorem
  4. Summary - Divide and conquer

18 Backtracking

  1. What is backtracking?
  2. State tree
  3. Pruning
  4. Summary - Backtracking

19 Graph project

  1. Project: Overview
  2. City graph
  3. BFS for reachability
  4. Print the result

20 Intermediate final

  1. Challenge 1
  2. Challenge 2
  3. Challenge 3
  4. Challenge 4