The five hand-written registrars (about 5,500 lines, one 997-line function)
are replaced by `jobs/registry/`: one `defineJob` entry per queue with its
cron, schedule send options, policy, work options, lock, lane and a handler
loader. `registerJobGroup` creates, schedules, retires and binds each group
in the order the registrars used; the worker boot walks the groups and runs
their boot discovery.
Handlers load on their queue's first job. The facts a declaration needs at
boot (names, crons, concurrency, send options) moved out of the heavy job
modules into light `*-queue.ts` siblings, and their importers point there,
so loading the registry evaluates 288 modules instead of the 1,164 the
registrars pulled in. The formerly inline handlers moved verbatim into
handler modules under `jobs/reminder/`.
Fitbit's queues live in `fitbit/jobs/definitions.ts` and enter the registry
through one spread, so removing the integration later is that folder and
that line.
`tests/integration/queue-registration-parity.test.ts` proves pg-boss holds
exactly what the registrars left (queues, schedules, bindings, byte for
byte) and loads every handler once. The queue tests and the runtime guard
assert on the registry objects instead of reading registrar source.
The Health Connect import stored its unit factors' binary noise as is
(grams to kilograms, millis to minutes, the day sums) and rounded the
pulse means and nutrients privately. Every measurement value now takes
importValue at the write boundary, and importValue takes a precision for
the two places that need another one. The rounding guard now covers the
import directory and the scaled Math.round form.
The nightly dense-intraday fold scanned Apple Health rows only, so the
per-minute heart rate a Health Connect import writes for the last 90 days
never aged into hourly means and every new export added another quarter
of raw samples.
The fold now walks each fold source in turn, Apple Health first and
unchanged, and folds Health Connect samples into hourly stats: rows under
their own source, deleting the raw rows outright. The folded_window rule
covers both sources for the hour window and looks a covering row up under
the sample's own source; the day window stays Apple Health only. The
Health Connect importer applies the same rule to raw samples, so an
export that still holds folded minutes does not put them back.
Upload the ZIP the Android Health Connect app writes and import its
`health_connect_export.db` in the background, the same way an Apple
Health export is imported: streamed to disk with a SHA-256, capped at
1 GiB, one import per account, a job row of kind `health_connect` that
the shared reconcile cron and staging sweep now look up on its own
queue.
The worker extracts the database (4 GiB ceiling, zip-bomb checks) and
opens it read-only with `immutable=1`, `trusted_schema=OFF` and
`query_only`. A view in place of a record table refuses the file,
columns are found by name, and schema versions below 9 are refused.
Records are read in batches of 500 and aggregated in SQLite: steps,
energy and distance as one total per day from the app the person's
Health Connect priority list ranks first, heart rate per minute for 90
days and as hourly means before that, sleep stages with the unknown
stage counted only in sessions without real stages, workouts, cycle
days, water and micronutrients. Apps whose integration the account has
connected are left out, and a reading already stored under another
source is skipped. Rows carry source HEALTH_CONNECT, `hc:<uuid>` or the
`stats:` ids, so a second import of the same export writes nothing.
Both staged files are removed on every way out; the job result holds
counts per type and per app only. Settings gain a Health Connect card
with the export steps, progress and the outcome, in all seven
languages, and the import is documented in
docs/integrations/health-connect.md.
Marc-André Bombeck