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Solve small string and API tasks

NVIDIASoftware Engineer · Onsite
MediumSoftware EngineerOnsiteCoding & Algorithms

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This problem tests your ability to handle nested structural validation using stacks and the design of a robust API integration function that aggregates paginated responses.

Part 1: Bracket Validator

Write a function is_valid(s: str) -> bool that determines if a string containing parentheses '()', curly braces '{}', and square brackets '[]' is valid. The string is valid if every opening bracket has a corresponding closing bracket of the same type and brackets are closed in the correct order.

Example:

  • Input: "()[]{}", Output: True
  • Input: "([)]", Output: False

Part 2: API Aggregator

You are provided a mock interface fetch_page(url: str, page_num: int) -> dict. The API returns a JSON object: {"data": [...], "next_page": int or None}. Write a function get_all_data(base_url: str) -> list that fetches data from all pages until next_page is null and returns a flat list of all items.

Constraints:

  • page_num starts at 1.
  • You should handle basic JSON parsing errors.
  • The total number of pages is unknown.
def get_all_data(base_url: str) -> list:
    # Implementation here

Edge Cases:

  • Empty strings for validation.
  • API returning an empty data list or an error code.
  • Malformed JSON responses.

Hints

Hint 1

For bracket validation, use a stack to keep track of opening brackets and match them against the most recently added bracket when a closing one is encountered.

Hint 2

For the API task, use a while-loop that continues as long as a valid page number or pointer exists in the previous response.

Hint 3

Remember to handle the case where the API returns an empty list but the next_page pointer is still valid.

Follow-up questions

  • How would you modify the bracket validator to support arbitrary custom brackets like '' if they were provided in a dictionary mapping?
  • If the API calls are slow, how would you implement concurrent fetching using threading or async/await to speed up the data aggregation?
  • How would you handle rate limiting (e.g., 429 Too Many Requests) if the API suddenly throttled your requests?