Coinbase Data Scientist Coding Questions

Coinbase often analyses transaction data to understand product adoption. You need to help find the number of distinct products a user has interacted with in a series of transaction records.Problem statement: Given a list of transaction records where each record is represented as a tuple containing (user_id, product_id), write a function to return the number of distinct products that each user has interacted with.- Method Signature: def count_distinct_products(transactions: List[Tuple[int, int]]) -> Dict[int, int]: Returns a dictionary with user_id as keys and the count of distinct product_ids as values.Example 1:
Input: transactions = [(1, 101), (1, 102), (2, 101), (1, 101), (2, 103)]
Output: {1: 2, 2: 2}
Explanation: User 1 interacted with products 101 and 102, while User 2 interacted with products 101 and 103.Constraints:
- 1 <= len(transactions) <= 10^5
- 1 <= user_id, product_id <= 10^4

Coinbase analytics processes vast amounts of transaction history data. You need to help the data team find the maximum sum of any contiguous subarray of transaction amounts over a specified transaction window.Problem statement: Write a function that returns the maximum sum of a contiguous subarray of n transaction amounts within the transaction history array. You need to capture the transaction amounts over a window_size.- Method Signature: def max_subarray_sum(transactions: List[int], window_size: int) -> int: Returns the maximum sum of a contiguous subarray of the specified size.Example 1:
Input: transactions = [1, -2, 3, 4, -1, 2, 1, -5, 4], window_size = 3
Output: 6
Explanation: The subarray [3, 4, -1] has the maximum sum of 6.Constraints:
- 1 <= len(transactions) <= 10^5
- -10^4 <= transactions[i] <= 10^4
- 1 <= window_size <= len(transactions)