Lyft Coding Interview Questions
32 Lyft coding interview problems with full optimal solutions — 20 easy, 10 medium, 2 hard. Every problem ships with multiple approaches (brute-force first, then the optimal), complexity tables for each, company-specific tips on what an Lyft interviewer values, and a FAQ section.
- #21mediumfoundational
21. Network Delay Time
Find how long a signal takes to reach all nodes — Lyft applies the same Dijkstra logic to propagate ETA updates across its real-time driver-location graph when dispatch events fire from a central node.
- #22mediumfoundational
22. Cheapest Flights Within K Stops
Minimize cost with a hop constraint — Lyft applies the same bounded shortest-path logic when optimizing multi-leg ride chains where passengers switch vehicles at hubs, keeping transfers under a service limit.
- #23mediumfoundational
23. Task Scheduler
Minimize total time to execute tasks with a cooldown — Lyft uses the exact same greedy cooling logic to schedule repeated driver-pings so no driver is contacted more frequently than a system-defined interval.
- #24mediumfoundational
24. Meeting Rooms II
Find the minimum number of rooms for overlapping meetings — Lyft maps this to how many concurrent driver-pickup windows they need to keep open at a hub so no ride request is ever left unserviced.
- #25mediumfoundational
25. Top K Frequent Elements
Return the k most frequent elements — Lyft applies the same bucket-frequency pattern to surface the top-k pickup hotspots across a metro area so dispatchers can pre-position drivers before demand spikes.
- #26mediumfoundational
26. Number of Islands
Count connected land regions in a grid — Lyft uses the same BFS flood-fill to identify distinct geographic service zones from binary availability grids when partitioning its coverage map into driver dispatch regions.
- #27mediumfoundational
27. Kth Largest Element in an Array
Find the k-th largest element without full sorting — Lyft applies quickselect to rank surge-pricing multipliers across zones and identify the k-th highest demand area to allocate driver incentives efficiently.
- #28mediumfoundational
28. Coin Change
Minimize coins to reach a target — Lyft uses the same bottom-up DP to decompose a surge-pricing budget into the fewest discount tiers needed to reach a target incentive amount for driver recruitment campaigns.
- #29mediumfoundational
29. LRU Cache
Design an O(1) get/put cache that evicts the least-recently-used entry — Lyft runs the exact same LRU structure to cache driver location pings in memory so repeated ETA lookups for the same driver avoid hitting the database.
- #30mediumfoundational
30. Word Search
Search for a word in a 2D character grid — Lyft applies the same DFS-with-backtracking to trace contiguous route segments on a map grid, checking if a sequence of location codes spells a valid service corridor.
- #31hardfoundational
31. Serialize and Deserialize Binary Tree
Encode and reconstruct a binary tree via a string — Lyft applies the same BFS-serialization contract to persist driver-preference decision trees to its configuration store and reload them across service restarts without losing structure.
- #32hardfoundational
32. Trapping Rain Water
Compute water trapped between elevation bars — Lyft uses the two-pointer scan pattern to calculate residual ride capacity between demand spikes across time windows, finding how much latent supply is 'trapped' between peak surge events.
- #1easyfoundational
1. Two Sum
Find two indices in an array whose values sum to a target.
- #2easyfoundational
2. Valid Parentheses
Validate that bracket characters in a string close in the right order.
- #3easyfoundational
3. Merge Two Sorted Lists
Combine two sorted singly-linked lists into one sorted list.
- #4easyfoundational
4. Remove Duplicates from Sorted Array
Remove duplicates from a sorted array in-place and return the new length.
- #5easyfoundational
5. Remove Element
Strip all instances of a value from an array in-place.
- #6easyfoundational
6. Search Insert Position
Find the index where target would be inserted into a sorted array.
- #7easyfoundational
7. Plus One
Add one to a number represented as a digit array.
- #8easyfoundational
8. Merge Sorted Array
Merge two sorted integer arrays in-place into the first one.
- #9easyfoundational
9. Binary Tree Inorder Traversal
Return the inorder traversal of a binary tree.
- #10easyfoundational
10. Same Tree
Check whether two binary trees are structurally identical with the same values.
- #11easyfoundational
11. Symmetric Tree
Determine whether a binary tree is a mirror of itself.
- #12easyfoundational
12. Maximum Depth of Binary Tree
Compute the maximum depth of a binary tree.
- #13easyfoundational
13. Balanced Binary Tree
Determine if a binary tree is height-balanced.
- #14easyfoundational
14. Minimum Depth of Binary Tree
Find the minimum depth of a binary tree.
- #15easyfoundational
15. Pascal's Triangle
Generate the first numRows of Pascal's triangle.
- #16easyfoundational
16. Best Time to Buy and Sell Stock
Find the maximum single-buy single-sell profit from a price array.
- #17easyfoundational
17. Valid Palindrome
Check whether a string is a palindrome considering only alphanumeric characters.
- #18easyfoundational
18. Single Number
Find the element that appears once when every other element appears twice.
- #19easyfoundational
19. Linked List Cycle
Detect whether a singly-linked list contains a cycle.
- #20easyfoundational
20. Min Stack
Design a stack that supports getMin in constant time.
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