Determine Trading Availability - Coding Interview

Question

## Problem

A trading platform has market hours defined per exchange as a list of `(open_time, close_time)` intervals (24-hour integers, e.g., 930 = 9:30 AM). Intervals within an exchange may overlap. Given a query time `t`, determine which exchanges are currently open.

Additionally, given a list of trades each with a `timestamp`, filter out any trade that occurred outside the exchange's open hours.

```python
def open_exchanges(schedules: dict[str, list[tuple[int,int]]], query: int) -> list[str]:
    ...

def valid_trades(
    schedules: dict[str, list[tuple[int,int]]],
    trades: list[dict]  # each: {exchange, timestamp, symbol, qty}
) -> list[dict]:
    ...
```

**Example:**
```
schedules = {"NYSE": [(930,1200),(1300,1600)], "CRYPTO": [(0,2359)]}
open_exchanges(schedules, 1230)  -> ["CRYPTO"]
open_exchanges(schedules, 1000)  -> ["NYSE", "CRYPTO"]
```

## Follow-ups
- How would you preprocess the schedule intervals to answer queries in O(log n) per exchange?
- Extend to support timezone-aware schedules (each exchange in its local timezone).
- What if exchange hours span midnight (e.g., open 2200, close 0200)?

Determine Trading Availability - Coding Interview

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