DFS + BFS

When to use

Use for traversal, connectivity, levels, paths, components, and tree recursion. DFS for exploring all paths or doing recursive tree work. BFS for shortest path in unweighted graphs or level-by-level processing.

Core intuition

DFS dives as deep as possible before backtracking — use a stack or recursion. BFS explores all neighbors at the current level before going deeper — use a queue. Both need a visited set for graphs.

Template

# DFS recursive (tree)
def dfs(node):
    if not node:
        return 0
    left = dfs(node.left)
    right = dfs(node.right)
    return 1 + max(left, right)

# BFS (shortest path / level order)
from collections import deque
def bfs(start):
    queue = deque([start])
    visited = {start}
    steps = 0
    while queue:
        for _ in range(len(queue)):
            node = queue.popleft()
            for neighbor in graph[node]:
                if neighbor not in visited:
                    visited.add(neighbor)
                    queue.append(neighbor)
        steps += 1
    return steps

Suggested problems