#0167

Shortest Path in an Unweighted Graph

MediumDSA25 min20 XP

Problem

Given an adjacency list graph, start node, and target node, return the shortest number of edges. Return -1 if unreachable.

Why This Matters

BFS shortest path is a core graph pattern behind routing, social distance, and state-space search.

Function Signature

def shortest_path_length(graph, start, target):

Examples

Example 1

Input{'A':['B','C'], 'B':['D'], 'C':['D'], 'D':[]}, start='A', target='D'

Output2

A -> B -> D or A -> C -> D uses two edges.

Constraints

Return the exact requested output.
Handle ordinary edge cases.
Prefer simple, interview-readable code.

CodePython

def shortest_path_length(graph, start, target):
    """
    Input example: {'A':['B','C'], 'B':['D'], 'C':['D'], 'D':[]}, start='A', target='D'
    Return: 2
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # write your code here
    return -1

def shortest_path_length(graph, start, target):
    """
    Input example: {'A':['B','C'], 'B':['D'], 'C':['D'], 'D':[]}, start='A', target='D'
    Return: 2
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # write your code here
    return -1

Visible browser tests run here when available.

Testcases1 visible / 3 hidden categories

Core example

Input{'A':['B','C'], 'B':['D'], 'C':['D'], 'D':[]}, start='A', target='D'

Expected2

A -> B -> D or A -> C -> D uses two edges.

Hidden Test Categories

empty or minimal inputduplicates or tieslarger input