Marlin/roadmap.md

Roadmap

Phase	Functional focus	Why do it now?	Key deliverables
1. Lock down the foundation	Migrations + tests	Schema churn and silent breakage are the biggest hidden costs. Catch them early.	• Split migrations.sql into versioned files • Remove runtime “ensure_column” path • Add CI job that runs cargo test on every PR
2. Trim the FTS triggers	Efficient index upkeep	The current triggers will bog down as soon as users bulk-tag thousands of files.	• Replace per-row GROUP_CONCAT triggers with a “dirty” flag or app-side refresh • Benchmark a full scan + mass tag on ≥100 k files
3. Hashing & dedup logic	Content integrity	Once the index is stable and fast, add SHA-256 so the DB can detect duplicates/corruption.	• files.hash column populated on first scan • marlin scan --rehash to force refresh
4. Alias / canonical tags	Usable taxonomy	Without this, tag sprawl happens quickly. Better to solve before users have thousands of tags.	• tags.aliases table or canonical_id enforcement • CLI subcommands: tag alias add, tag alias ls
5. Search parser upgrade	Power queries	After the data model is solid, richer search is the next visible win.	• Swap ad-hoc parser for nom-based grammar • Support grouping (...), boolean ops, quoted phrases
6. Attribute schemas	Structured metadata	Custom field templates let you build real workflows (e.g. Photo > Aperture).	• templates + template_fields tables • Validation on attr set
7. Dolphin extension MVP	Desktop integration	No point shipping a GUI until the backend is rock-solid.	• Read-only sidebar showing tags/attrs • Double-click tag to filter view
8. Write / edit UI	End-user adoption	Once people can browse metadata inside Dolphin, they’ll want to edit it too.	• In-place tag editor widget • Attribute form dialog tied to templates
9. Sync & sharing	Multi-device story	Last—most complex. Only tackle when single-machine use is boring.	• Lite RPC layer (SQLite WAL + notify?) • Optional read-only mode for network mounts

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How to tackle each phase

1. Do one migration PR that just moves existing DDL into 0001.sql. Merge, tag a release.
2. Prototype trigger-less FTS maintenance in a branch; measure with --timings tracing.
3. Hashing: gate expensive work behind mtime/size check you already coded.
4. Alias logic: start simple—single-level canonical_id; later add synonym sets if needed.
5. Parser: write unit tests for every example query first, then swap implementation—same public API.
6. Templates: store JSON schema in DB, validate with serde_json::Value + compiled regexes.
7. Dolphin plugin: expose DBus calls from Rust core, C++/Qt side just calls them.
8. Write UI: reuse the same DBus interface; no extra DB code.
9. Sync: decide early if you aim for local-first replication (Litestream, rqlite) or a bespoke solution.

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Practical next sprint (2 weeks)

1. Finish phase 1 (migrations + CI) ⇒ release v0.2.0.
2. Start phase 2: rip out FTS triggers, implement dirtied-rows rebuild, test at 50 k files.
3. If time remains: add --rehash flag and wire in SHA-256 function (phase 3 seed).

This path keeps user-visible features arriving every couple of weeks without accumulating technical debt.