Duplicate Viewings: Deduplicate a User's Watch History Stream

Question

## Problem

You are given a list of viewing events for a single user. Each event has a `show_id` and a `timestamp`. A "duplicate" viewing occurs when the same `show_id` appears more than once within a 24-hour window of its first occurrence.

Return a deduplicated list preserving only the first occurrence of each show within any 24-hour window.

```python
from typing import List, Tuple

def deduplicate_viewings(events: List[Tuple[str, int]]) -> List[Tuple[str, int]]:
    # events: list of (show_id, unix_timestamp_seconds)
    # return: filtered list in original order
    pass
```

**Example:**
```
Input:  [("S1", 1000), ("S2", 1500), ("S1", 86200), ("S1", 87200)]
Output: [("S1", 1000), ("S2", 1500), ("S1", 87200)]
# S1 at 86200 is within 86400s of S1 at 1000, so dropped.
# S1 at 87200 is outside the window, so kept (new window starts).
```

## Follow-ups

1. What if events can arrive out of order by timestamp? How does your approach change?
2. How would you scale this to process millions of users' events per day in a streaming pipeline?
3. What if "duplicate" is defined per (show_id, season_number) pair instead of show_id alone?
4. How would you emit a count of dropped duplicates per show alongside the filtered list?

Duplicate Viewings: Deduplicate a User's Watch History Stream

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