Trading Symbols Set Operations - Coding Interview

Question

## Problem

Design a `TradingSymbolSet` class that maintains a dynamic set of active trading symbols and supports efficient bulk operations.

```python
class TradingSymbolSet:
    def add(self, symbol: str) -> None: ...
    def remove(self, symbol: str) -> None: ...
    def contains(self, symbol: str) -> bool: ...
    def union(self, other: 'TradingSymbolSet') -> 'TradingSymbolSet': ...
    def intersection(self, other: 'TradingSymbolSet') -> 'TradingSymbolSet': ...
    def difference(self, other: 'TradingSymbolSet') -> 'TradingSymbolSet': ...
    def snapshot(self) -> list[str]: ...  # sorted alphabetically
```

Two exchanges publish their active symbol lists every minute. Use your class to compute:
1. Symbols active on both exchanges (for arbitrage scanning).
2. Symbols that went from one exchange's list but not the other's between two snapshots.

**Example:**
```
exch_a = TradingSymbolSet(); exch_a.add("AAPL"); exch_a.add("GOOG")
exch_b = TradingSymbolSet(); exch_b.add("GOOG"); exch_b.add("TSLA")
exch_a.intersection(exch_b).snapshot()  -> ["GOOG"]
exch_a.difference(exch_b).snapshot()    -> ["AAPL"]
```

## Follow-ups
- What is the time complexity of each operation?
- How would you persist and restore a snapshot for audit purposes?
- Extend to tag each symbol with metadata (sector, lot size) and filter set operations by tag.

Trading Symbols Set Operations - Coding Interview

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