Feat/csv import export#12
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secrets context is invalid in job-level if conditions, causing a workflow parse error. The backend job also requires a Neon test DB that won't be available in CI, so remove it entirely rather than leave a permanently-broken job in the pipeline.
Add searchMovieByTitleAndYear to the TMDB client so the import pipeline can resolve a film to a tmdbId without a URI or a local record. Add existsByUserAndMovie (any date) and existsByUserMovieAndDate to DiaryRepository for deduplication during CSV import.
Export: GET /api/data/export returns the user's full diary as a CSV (WatchedDate, Title, Year, TmdbId, Rating, Rewatch, Review, Spoilers). TmdbId in the export makes re-import instant. Import: POST /api/data/import accepts text/csv and streams ndjson back — one event per processed row so the client can render live progress. Auto-detects Letterboxd diary.csv, reviews.csv, watched.csv, and the Interis export format. Letterboxd watched.csv uses any-date deduplication (skip if the film exists in the diary at all), while diary/reviews use exact userId+movieId+watchedDate matching.
Frontend reads the ndjson stream via an async generator and feeds it into useImportStream, which accumulates lines and summary state in the parent page — not in the dialog — so the modal can be dismissed while import continues in the background. ImportDialog renders a scrolling terminal log (✓ imported, → skipped, ✗ failed) with a live progress bar and summary stat grid. A "Work in background" button closes the dialog; a banner in the settings page shows live progress and lets the user reopen the log when done. Export is a single button that triggers a browser file download. Wired into /settings/data with a Download tab in SettingsTabs.
watchlist.csv shares identical headers with watched.csv so the format is resolved from the filename passed as a query param. Watchlist rows upsert movie_interaction.watchlisted=true via a new InteractionsService.setWatchlisted helper that takes movieId directly — avoids a redundant findOrCreate call. Reviews were already being saved via upsertReview when the Review column is present (reviews.csv). No additional changes needed for that path.
Send file.name as ?filename= so the backend can distinguish watchlist.csv from watched.csv. Update the import section copy to mention watchlist.csv and clarify that reviews are imported automatically from reviews.csv.
Year fallback: if a title+year search returns nothing, retry without the year. Letterboxd and TMDB frequently disagree on release year for late-December films, causing well-known movies to fail unnecessarily. Parallel processing: replace the sequential row loop with a worker pool (concurrency=5). Each worker pulls the next row from a shared queue, so 5 TMDB lookups run simultaneously. Expected import time drops from ~100s to ~20s for a 163-entry diary.
…port Add searchSeriesByTitleAndYear to the TMDB serials client using first_air_date_year (the correct TV param, not year). Add to SerialsInteractionsRepository: existsByUserAndSeries, existsByUserSeriesAndDate, insertSerialDiaryEntry, setWatchlisted to mirror the movie-side DiaryRepository methods needed by the CSV import pipeline.
Replace resolveTmdbId with resolveMedia which returns a typed
{ mediaType, tmdbId } discriminated union. Resolution order:
1. movie + year
2. movie without year (year mismatch fallback)
3. TV series + year
4. TV series without year
The import loop branches on mediaType — series entries go into
serial_diary_entry via SerialsInteractionsRepository, movie
entries go into diary_entry via DiaryRepository. Watchlist import
also branches so TV shows land in serial_interaction instead of
movie_interaction.
Deploying interis with
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