Coinbase Interview Questions

As Coinbase looks to integrate social features for trading, it's essential to design a system that tracks user feeds efficiently.
Problem statement: Design a class to manage a user's feed. Supports the following methods: follow(follower_id: int, followee_id: int), unfollow(follower_id: int, followee_id: int), and get_feed(user_id: int) -> List[int]. The feed should return the most recent 10 transactions from the followed users.
- Method signatures:
- def follow(follower_id: int, followee_id: int) -> None: update the following relationship.
- def unfollow(follower_id: int, followee_id: int) -> None: remove the following relationship.
- def get_feed(user_id: int) -> List[int]: return the user feed containing transaction IDs of the most recent 10 transactions from followed users.
Example 1:
Input: manager = FeedManager()
manager.follow(1, 2)
manager.follow(1, 3)
manager.get_feed(1)
Output: [x, y, z]
Constraints:
- 1 <= follower_id, followee_id <= 10^4
- Transaction history size can be up to 10^5.

In order to optimize data retrieval times and minimize database load, Coinbase requires an LRU cache to manage frequent API requests efficiently.
Problem statement: Design and implement a class that represents an LRU Cache with a fixed capacity. Supports get(key: int) -> int and put(key: int, value: int) -> void methods.
- Method signatures:
- def get(key: int) -> int: returns the value of the key if it exists or -1.
- def put(key: int, value: int) -> None: updates the value if the key exists, otherwise, adds the key-value pair to the cache. If 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)
Output: 1
cache.put(3, 3)
cache.get(2)
Output: -1
Constraints:
- 1 <= capacity <= 3000
- 0 <= key, value <= 10^4.

In the ever-changing world of cryptocurrency, it's crucial for Coinbase to determine the number of distinct markets that remain active within any given time frame.
Problem statement: Given an array of timestamps when markets were opened and closed, and a d days window, compute the total number of distinct markets open during that window.
- Function signature: def count_active_markets(timestamps: List[Tuple[int, int]], d: int) -> int: returns an integer count of active markets.Example 1:
Input: timestamps = [(1, 5), (2, 3), (4, 6)], d = 3
Output: 2
Explanation: Markets 1 and 2 overlap in the window [1, 4].Example 2:
Input: timestamps = [(1, 2), (3, 5), (7, 10)], d = 3
Output: 1
Explanation: Only one market is active at any time in the window 1 to 4.Constraints:
- 1 <= timestamps.length <= 1000
- 1 <= d <= 10000
- Timestamps are unique.

In Coinbase's ecosystem, efficient transaction routing is crucial for timely processing. The goal is to determine the shortest path between users in a peer-to-peer transaction graph.
Problem statement: Given a directed graph representing users and their transactions as edges, write a function to find the shortest path from the source user to the destination user. Users can have multiple transactions but there is a constraint on transaction types that can be traversed.
- Function signature: def shortest_path(transactions: List[Tuple[int, int]], source: int, destination: int) -> List[int]: returns a list of users representing the shortest path.Example 1:
Input: transactions = [(1, 2), (2, 3), (2, 4), (3, 4)]
Output: [1, 2, 3]
Explanation: The path from user 1 to user 3 is through user 2.Example 2:
Input: transactions = [(1, 2), (1, 3), (3, 4), (2, 4)]
Output: [1, 3, 4]
Explanation: The path from user 1 to user 4 is through user 3.Constraints:
- 1 <= transactions.length <= 100
- 1 <= source, destination <= 10^4
- All transactions are unique.