No aggregate stats for a user's watchlist

Product wants a simple stats summary for a dashboard/onboarding email ("you're 40% through your watchlist!"). Right now the only way to build that is for every client to page through the entire list and compute it themselves -- wasteful for a user with a large watchlist, and it means every client re-implements the same aggregation logic instead of the server doing it once, correctly.

There is no way to get a summary of a user's watchlist. A client that wants to show "you've watched 42 of 108 movies, averaging a 7.3 rating" has to fetch every single page of GET /api/movies and compute it client-side.

cd flask/movie_watchlist .venv/bin/python -m pytest practicetickets/test_ticket06_stats_endpoint.py -v

GET /api/movies/stats returns 404 -- the route and aggregation logic do not exist yet.

This is the same load-bearing rule the rest of this project exists to enforce, applied to a new kind of endpoint: an aggregate query, not a single-resource lookup. movies/service.py's get_owned_movie_or_404() filters by user_id at the query level for a single row -- it's easy to reach for MovieEntry.query.filter_by(user_id=...) there and get it right, because the existing helper does it for you. A new aggregate endpoint has no existing helper to lean on, and it's correspondingly easy to write a query that aggregates over all users' movies by forgetting the user_id filter -- which would silently leak one user's rating/watched counts into another user's stats. Getting this ticket right means applying the same ownership discipline the rest of the codebase already has, to a query shape (COUNT/AVG) that doesn't have a ready-made helper for it yet.

Look at how list_movies() builds base_query = MovieEntry.query.filter_by(user_id=current_user_id) and how it resolves current_user_id from the JWT. Your new endpoint needs the same starting filter, then an aggregation over it instead of a .paginate(...)/.dump(...). Think about what SQL AVG() already does with NULL values (unrated entries) versus what a naive sum(ratings) / len(ratings) in Python would do with an empty list.