MediumDSA10 min read

When would you use BFS over Dijkstra for shortest paths?

Q: When would you use BFS over Dijkstra for shortest paths?

**Target Audience:** Beginners preparing for coding interviews — no graph-algorithm background assumed **Difficulty:** Medium **Language:** Python 3 > **How to read this doc:** Every idea is explained in plain language first, then tagged with `📌 Interview term:` so you also learn the exact word an interviewer expects. All code is Python, and every output block in the **Verified** section was copied from a real run of the examples on this page. ## 1. Why This Even Matters — A Story First You are on a metro map and want to get from your stop to a friend's. If every hop between neighbouring stations takes exactly two minutes, the quickest trip is simply the one with the **fewest hops**, and you can find it by looking at all stations one hop away, then all stations two hops away, and so on, like ripples on a pond. That is breadth-first search. Now the timetable changes: some hops take 2 minutes, one express hop takes 15. "Fewest hops" and "fewest minutes" are no longer the same questi

647 views

75 of 154

The problem

Question presented to candidate: "You need shortest paths in a graph. When is a plain BFS enough, and when do you need Dijkstra? Show me both in Python and explain what goes wrong if you pick the wrong one."

What a strong answer should cover:

BFS minimises the number of edges; Dijkstra minimises total weight. They agree exactly when all weights are equal (any equal value, not only 1).
Why BFS is correct there: its FIFO queue already releases nodes in distance order, so the O(log V) heap is unnecessary.
A concrete counterexample where BFS picks a fewer-edge but more expensive path.
0-1 BFS with a deque for weights 0 and 1, and Bellman-Ford when weights can be negative.
Python specifics: collections.deque with popleft() (O(1)) instead of list.pop(0), and heapq for Dijkstra.

Code / implementation expected: Yes — a Python BFS with collections.deque and a Dijkstra with heapq, ideally plus 0-1 BFS with appendleft.

graphs
shortest-path

Try it yourself

Sketch your approach before you read the solution. That is what the interview tests.

Stuck? Get a hint.

A short nudge toward the approach. It will not give the answer away.

Solution

Target Audience: Beginners preparing for coding interviews — no graph-algorithm background assumed Difficulty: Medium Language: Python 3

How to read this doc: Every idea is explained in plain language first, then tagged with 📌 Interview term: so you also learn the exact word an interviewer expects. All code is Python, and every output block in the Verified section was copied from a real run of the examples on this page.

1. Why This Even Matters — A Story First

You are on a metro map and want to get from your stop to a friend's. If every hop between neighbouring stations takes exactly two minutes, the quickest trip is simply the one with the fewest hops, and you can find it by looking at all stations one hop away, then all stations two hops away, and so on, like ripples on a pond. That is breadth-first search.

Now the timetable changes: some hops take 2

The solution is hidden so you can try first

10 min read · 12 sections

Python code

Edit the code and run it here. Each printed line with an expected value becomes a test.

PythonBFS and Dijkstra on equal and unequal weights

Practice

Python0-1 BFS with a deque versus Dijkstra

Practice

Discussion

Other approaches, follow-ups and how it went in real interviews.

No comments yet. Share how you would answer it.

Question 75 of 154 in DSA

Keep your momentum going.

Mark this question solved to track your progress, then take the next one while it is fresh.

All DSA questions

Up nextMedium→

How do you do a level-order (BFS) traversal of a tree?

Continue