Top K Symbols by Traded Volume

The end-of-day report lists the symbols that traded the most. The trade log holds one row per fill, so a busy symbol appears thousands of times and a quiet one once.

Implement top_k_symbols(trades, k). trades is a sequence of symbol and quantity pairs in any order. Rank symbols by their total quantity across all their trades:

• The largest total comes first.
• If two symbols have the same total, the one that comes first alphabetically ranks higher.

Return the top k symbols in rank order. If there are fewer than k distinct symbols, return all of them.

def top_k_symbols(trades: list[tuple[str, int]], k: int) -> list[str]: ...

Each trade is a (symbol, quantity) tuple and the result is a list of symbols.

Examples

top_k_symbols([("AAPL", 100), ("MSFT", 250), ("AAPL", 200), ("NVDA", 50)], 2)
# ['AAPL', 'MSFT']  (AAPL totals 300, MSFT 250)

top_k_symbols([("XOM", 10), ("BP", 10), ("SHEL", 5)], 2)
# ['BP', 'XOM']  (a tie at 10, broken alphabetically)

Constraints

• Up to \(5 \times 10^5\) trades and \(10^5\) distinct symbols; k >= 1.
• Quantities are positive integers.
• The hidden performance test asks for the top 10,000 of 100,000 symbols. Picking the largest remaining symbol k times scans every symbol k times and will not finish. A heap of size k gives \(O(n + m \log k)\) for n trades and m symbols; sorting all m totals, \(O(n + m \log m)\), also passes.