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Modern offline-first self-hosted open-source TickTick/Todoist alternative. Now with desktop app and quick add global OS popup! (infosec.pub)

submitted 22 hours ago by quolpr@lemmy.world to c/selfhosted@lemmy.world

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Hey everybody! I am building self-hosted fast task manager, and today I am happy announce that I made desktop app and it supports macos, windows and linux! For mobile it is still PWA. All platforms support fast sync and works offline even when your homelab is down.

Also, one of the top feature that I really wanted is global quick add shortcut. You can trigger it with cmd+shift+a on macos, ctrl+shift+a on windows/linux.

More info: https://will-be-done.app/
Demo: https://demo.will-be-done.app/
GitHub: https://github.com/will-be-done/will-be-done
Download: https://github.com/will-be-done/will-be-done/releases

Installation

Single Docker command with SQLite as db:

docker run -d \
   -p 3000:3000 \
   -v will_be_done_storage:/var/lib/will-be-done \
   --restart unless-stopped \
   ghcr.io/will-be-done/will-be-done:latest

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[–] quolpr@lemmy.world 2 points 3 hours ago

Oh yeah, it's a long story!

My core idea is to build a task manager that will stay with me for the rest of my life. Because of that, my main requirement is for it to be fast even with a massive database. If I have 10k+ tasks saved over the years, it should still load and feel instant.

Another requirement is that it must be offline-first. I live in a country where the internet goes down pretty often, and I need my tasks to be available regardless of the server status.

Finally, I wanted a clean API so I could connect things like an MCP server or create tasks via Telegram.

I couldn't find an existing app that met all these needs, here is a table where I compared all self-hosted apps that I found(in awesome self-hosted github):

Here is how my journey went:

First approach: I tried using Redux and MobX. Performance sucked. The main reason is that MobX/Redux don't support B-tree indexing. Local-first apps rely heavily on "intervals"(cause you use fractional-indexing-jittered to order things and to support LWW per column), and that’s exactly where B-trees shine. Without them, it just got slower as the data grew.
Second approach: I tried a reactive UI based on persistent SQLite queries (using wa-sqlite). It worked well for small lists, but it felt sluggish once the dataset got large.
Third approach (Current): I decided to build my own DB solution, which you can see here: HyperDB. The trick is that you write the logic once, but on the frontend, it runs against an in-memory B-tree index (which is incredibly fast) and data still stored at persistent wa-sqlite layer, while on the backend, it runs against persistent SQLite (which keeps memory usage low).

This third approach finally solved all three requirements. It’s hard to find an open-source app that does this because this specific architecture is difficult to "cook" correctly. On top of the database speed, I also had to solve the sync problem, that should also somehow resolve conflicts while clients are offline, which I handled by building own sync layer with LWW CRDT per column.