LinkedIn Data Scientist Coding Questions

LinkedIn users are connected through various relationships, and understanding the shortest connection path between users can enhance user recommendations.
Given a graph representation of users and their connections as an adjacency list, implement Dijkstra's algorithm to find the shortest path from one user to another.Function Signature: def find_shortest_path(connections: Dict[int, List[Tuple[int, int]]], start: int, end: int) -> List[int]Example 1:
Input: {0: [(1, 1), (2, 4)], 1: [(2, 2)], 2: [(3, 1)], 3: []}, start=0, end=3
Output: [0, 1, 2, 3]
Explanation: The shortest path from user 0 to user 3 is 0 -> 1 -> 2 -> 3, with a total weight of 4.Example 2:
Input: {0: [(1, 5), (2, 1)], 1: [(2, 2), (3, 1)], 2: [(3, 4)], 3: []}, start=0, end=3
Output: [0, 1, 3]
Explanation: Path is from 0 to 1 to 3, with a weight of 6.Constraints:
- 1 <= len(connections) <= 1000
- Each connection weight is a positive integer.

LinkedIn's platform requires identifying the most engaged users over various time frames for enhanced user experience and targeted marketing strategies.
Given a list of user activity timestamps (in seconds) and a fixed time frame, write a function that returns the number of unique users who were active during that window.Function Signature: def count_active_users(timestamps: List[int], time_frame: int) -> intExample 1:
Input: [1, 2, 3, 4, 5, 6, 7], time_frame=3
Output: 5
Explanation: The unique users active between timestamps 1 and 3 are 1, 2, 3.Example 2:
Input: [1, 2, 2, 3, 5, 7, 9], time_frame=4
Output: 5
Explanation: The unique users between timestamps 2 and 5 are 1, 2, 3, 5.Constraints:
- 1 <= len(timestamps) <= 100000
- 0 <= timestamps[i] <= 10^9
- time_frame is a positive integer.