Limit Order Book Price-Time Matching

What's being tested

This tests stateful stream processing with priority queues / ordered maps and FIFO queues to implement a limit order book. You must preserve price-time priority, handle partial fills, and update mutable book state cleanly across a sequence of buy/sell orders.

Patterns & templates

• Use two books: bids sorted by highest price first, asks sorted by lowest price first; each price level stores a FIFO queue.

• Matching condition: buy crosses when buy.price >= bestAsk; sell crosses when sell.price <= bestBid; loop until order filled or no cross.

• Store per-price orders in deque to preserve time priority; consume from the front and append residual incoming orders at the back.

• Use TreeMap, SortedDict, heap plus lazy deletion, or ordered balanced BST; target O(log P + F) per order, where P is price levels and F fills.

• Keep mutable fields explicit: remaining_qty, order_id, timestamp, side, price; never mutate price or time priority after insertion.

• Remove empty price levels immediately after the last order at that level is filled; stale levels cause wrong best bid/ask behavior.

• Factor helpers like match(order, opposite_book), add_to_book(order, same_side_book), and best_price(book) for testable, readable code.

Common pitfalls

Pitfall: Matching by best timestamp globally instead of best price first; priority is price, then FIFO within the same price.

Pitfall: Forgetting partial fills; both the incoming order and resting order can have residual quantity after each trade.

Pitfall: Using a plain hash map for prices without an efficient best-price lookup, causing O(P) scans per incoming order.

Practice these

The practice cards below cover the canonical variants — solve all of them and time yourself.