My wife needed a cycle tracker. Everything out there was either Flo (which got sued twice for sharing health data) or an abandoned GitHub project. So I built Ovumcy. Single Go binary, SQLite, Docker-ready. No analytics, no third-party APIs, no cloud. Your data stays on your server. Features: period tracking, symptom logging, predictions (ovulation, fertile window), statistics, CSV/JSON export, dark mode, Russian and English. Just pushed v0.2.5. Looking for feedback from real users.

  • Fmstrat@lemmy.world
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    7 hours ago

    My partner might volunteer to try it out, but since she is very regular it probably wouldn’t help much for input.

    The main feature she says she misses from Flo (we are also data savy, so she left it), was for when things were irregular, the ability for it to predict the why’s and when’s like stress, etc.

    In the current iteration, if something is irregular can you put in what happened and have it auto-adjust?

    Also, reminder notifications a couple of days out were helpful.

    I had been considering a project like this as well, but one that uses on-device analytics to record the why’s and when’s, then allowing for scrubbed anonymous submissions (date adjusting/etc like you do in a clinical trial) to allow for algorithm development while preserving privacy.

    Happy to have a conversation about this for future potential PRs (I am an avid FOSS contributor in both planning and code, even working on a project for the Linux Foundation kernel dev team now).

    • terraincognita@lemmy.worldOP
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      44 minutes ago

      Thanks, this is really useful feedback.

      The reminder part is already on the roadmap, and I’ve now added two more issues based on your note about irregular cycles:

      • #17 Add irregularity factor tags for cycle tracking
      • #18 Use recorded cycle factors to improve prediction context

      The direction I’d want for Ovumcy is less “the app predicts the why” and more:

      • users can log things like stress, illness, travel, sleep disruption, etc.
      • the app can use that to give better context and reliability hints for irregular cycles
      • without pretending to make hard medical claims

      The anonymous scrubbed-submission idea is interesting too, but I’d treat that as much later, because it changes the privacy/trust model a lot.

      Happy to keep talking about it, and future PRs would definitely be welcome.