Stock Transactions Volume Aggregator - Coding Interview

Question

## Problem

Given a stream of stock trade events, each as `(symbol, quantity, price, timestamp)`, implement a `VolumeAggregator` that supports:

```python
class VolumeAggregator:
    def add_trade(self, symbol: str, qty: int, price: float, ts: int) -> None: ...
    def total_volume(self, symbol: str) -> int: ...              # total shares traded
    def vwap(self, symbol: str) -> float: ...                   # volume-weighted average price
    def volume_in_window(self, symbol: str, start: int, end: int) -> int: ...
    def top_symbols(self, n: int) -> list[tuple[str,int]]: ...  # top n by total volume, desc
```

**Example:**
```
agg = VolumeAggregator()
agg.add_trade("AAPL", 100, 150.0, 1000)
agg.add_trade("AAPL", 200, 152.0, 2000)
agg.vwap("AAPL")   -> (100*150 + 200*152) / 300 = 151.33
agg.volume_in_window("AAPL", 1500, 3000)  -> 200
```

## Follow-ups
- How would you implement `volume_in_window` efficiently using a sorted structure or binary search?
- What changes if trades can arrive out of order?
- Extend `top_symbols` to support a time-windowed version: top n symbols by volume in the last 60 seconds.

Stock Transactions Volume Aggregator - Coding Interview

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