DoorDash Mobile Engineer Coding Questions

DoorDash relies on drivers to fulfill user orders on time while maximizing efficiency. We want to ensure that drivers can cover as many orders as possible within a certain time window.
Problem Statement: Given an array of integers representing the times taken to deliver each order and an integer t for the total time available, return the maximum number of orders that can be delivered in that time frame.
Example 1:
Input: orders = [2, 3, 1, 5, 4], t = 7
Output: 4
Explanation: The maximum number of orders within the time frame is 4 (taking 1+2+3+1 = 7).Constraints:
- 1 <= orders.length <= 10000
- 1 <= orders[i] <= 1000
- 1 <= t <= 10000

DoorDash calls various APIs to fetch restaurant data. To improve performance and reduce unnecessary network calls, we need an efficient LRU (Least Recently Used) caching mechanism.
Problem Statement: Implement an LRUCache class that supports the following operations:
- get(key: int) -> int: Returns the value of the key if the key exists in the cache, otherwise returns -1.
- put(key: int, value: int) -> None: Updates the value of the key if the key exists, otherwise adds the key-value pair to the cache. When the cache reaches its capacity, it should invalidate the least recently used item before inserting a new item.Example 1:
Input:
cache = LRUCache(2)
cache.put(1, 1)
cache.put(2, 2)
cache.get(1) # returns 1
cache.put(3, 3) # evicts key 2
cache.get(2) # returns -1 (not found)Output:
1
-1Constraints:
- 1 <= capacity <= 3000
- 0 <= key <= 10000
- 0 <= value <= 10000