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Challenge 3

Run BFS on a graph and print the order.

Challenge 3: BFS

In this challenge you will run BFS on a graph and print the visit order.

Graph: {0: [1, 2], 1: [0, 3], 2: [0, 3], 3: [1, 2]}. Source: 0. Output: [0, 1, 2, 3].

BFS walks layer by layer with a queue and visited set; it gives the shortest step count.

Practice Print BFS

Write bfs_order(graph, start). Print the BFS visit order. Output: [0, 1, 2, 3].

Starter code

solution.py
def bfs_order(graph, start):
    # Print BFS order

Sample solution

solution.py
def bfs_order(graph, start):
    # Print BFS order
    visited = []
    queue = [start]
    while queue:
        node = queue.pop(0)
        if node not in visited:
            visited.append(node)
            for nb in graph[node]:
                if nb not in visited:
                    queue.append(nb)
    print(visited)
bfs_order({0: [1, 2], 1: [0, 3], 2: [0, 3], 3: [1, 2]}, 0)

Expected output

[0, 1, 2, 3]

Questions and answers

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

1 Challenge 3: match the terms

Term Meaning
BFS Layer
queue Queue
visited No repeat
O(V+E) Fast

2 Which data structure does BFS use?

  • Queue Correct answer
  • Heap
  • Stack
  • Trie

Explanation: Queue.

3 Loop condition

Question 
while ____:
Answer 
while queue:

Explanation: queue is right.

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