The stage-composition chart totalled each wake day, and a nap ends on the
same wake day as that morning's night. An afternoon nap was added straight
into the night's stage buckets, so the column read longer and shallower
than the night actually was.
The composition now asks the same question the night view already asks:
which session was the night. The night's stages are the night's, and the
nap sits on its own band above them, in its own colour, with its own line
in the tooltip. Days without a nap look exactly as they did.
The envelope was assigned after the loop, so the loop's IN_BED skip had
no observable effect - removing it changed nothing, which makes it a
dead branch rather than a guarantee. Assign the envelope first and let
the skip protect it.
A device can write the same period twice: an original envelope and a
corrected one, same start, later end, distinct external ids. Both rows
belong to the same writer, so the writer collapse keeps both, and the
per-stage totals added them. One night served a 10 h 13 min in-bed
headline next to a 20 h 17 min in-bed legend on the same screen, and
the hypnogram drew the night twice over.
Every per-stage total is now the measure of the union of that stage's
spans rather than the sum of the rows, and the same merged spans feed
the hypnogram segments and the time-asleep headline. Stages merge
independently: two stages describing one minute is a contest, and the
writer collapse is this file's mechanism for that - arbitrating again
would collapse the summary-shaped writers, which stamp every stage
total on the sleep end instant and nest by design.
stages.IN_BED is now the in-bed envelope itself, the same union
inBedMinutes reports, so the legend cannot contradict the headline and
a night whose envelope only a losing writer recorded still reports it.
Two in-memory key builders joined their parts with a literal NUL
(`${a}\x00${b}`): the sleep writer-bucket key and the correlation
pair key. The embedded NUL made grep classify both files as binary, so a
plain `grep symbol src/**` skipped them silently.
Swap the separator for U+241F (␟, the unit separator). It cannot appear
in a `MeasurementSource` enum literal, a device-type tag, or a
correlation-channel name, so the key semantics are identical — the sleep
key still slices its source prefix unambiguously and the correlation Set
still excludes double-counts. Both keys are ephemeral (one pass, never
persisted), so the byte change is invisible to any stored state.
The sleep source-discrepancy annotation now reaches the surfaces: SleepNight
carries the MAIN session's annotation (naps never cross-compare), the analytics
slim slice / dashboard snapshot / iOS summary thread it additively, and the
dashboard sleep tile renders the shared discreet marker (extracted from the
sleep panel — one implementation, two surfaces). Served totals unchanged,
pinned by tests.
Apple Health medications groundwork (server side of the medication-import
request): IntakeSource gains APPLE_HEALTH; medications accept an external
mirror identity (source-exclusive by policy) and dose imports carry the HK
dose-event UUID — both idempotent per stable key, with the concurrent-create
race resolved to the winner. Migration 0239, additive only. Entries without
the new fields behave byte-identically.
Hardening: doctor-report aggregation + PDF charts compute ranges with loops
instead of spread calls — a report over a sample-dense year cannot overflow
the call stack (the class fixed for the Google Health full sync).
A one-time background pass re-reads each connected account's Google Health
sleep history so nights stored twice before the sleep fix collapse to their
true total (new sleep_repaired_at marker, migration 0238; watermark-safe,
enqueued once at boot per un-repaired connection).
The sleep night read reports when two writers disagree about the same night —
the served total is unchanged, the disagreement rides along as an annotation
(sourceDiscrepancy on the night DTO) so clients can mark the number instead of
silently picking a side.
A GLP-1 medication whose weight has plateaued on the current dose says so next
to the estimated drug level (efficacy tab + insights) — a factual note from the
existing detector, association only, verb-guard covered.
Google Health diagnostics: the sync log now separates a daily-totals read that
returned nothing from one the importer could not parse
(googleHealth.rollup.emptyResponse vs droppedAll), and the connection test's
structure probe reports the raw response envelope key names when a rollup type
parses to zero — a per-account naming drift becomes visible from one report.
Polar exposes only per-stage duration totals, so its mapper already
reconstructs a contiguous CORE-DEEP-REM order exactly like WHOOP and flags
each segment reconstructed. The night reader's honesty allow-list only held
WHOOP, so a Polar-won night was served with reconstructed:false — presenting
a synthetic stage order to web and iOS as if it were the device's measured
timing. Add POLAR to the allow-list so the layout is labelled approximate.
Polar's total_interruption_duration carried the night's awake time but was
dropped, so every Polar night read as fully consolidated (awakeMinutes:null,
awakenings:0) with overstated asleep-vs-in-bed efficiency. Lay it as a
leading AWAKE segment so the asleep stages partition the remaining window and
the reader surfaces real awake time.
WHOOP and Polar independently implemented the same contiguous-timeline walk.
Extract a shared reconstructContiguousSleepTimeline helper under src/lib/sleep
and call it from both; each mapper keeps only its field normalisation. Oura's
measured 5-min hypnogram is a different algorithm and is left untouched.
WHOOP's v2 API returns only per-stage sleep duration totals — no onset
timestamps, no hypnogram endpoint. The mapper stamped all five stage
totals on the one sleep-END instant, so the hypnogram reconstructed
every stage as a span touching the night's right edge: bars stacked
right-aligned with no clock times whenever WHOOP was the sole source.
Lay the asleep stages back-to-back from sleep onset in a fixed
physiological order (AWAKE lead, then CORE → DEEP → REM), emitting one
timed row per segment with measuredAt at that segment's end and a
distinct indexed externalId. IN_BED stays a single envelope row over the
whole window. The existing reader and renderer are untouched — they now
see distinct per-segment instants and place each block at its own time.
The order is synthesised, not measured, so every reconstructed row is
flagged and the night DTO carries a per-session `reconstructed` boolean
(GET /api/sleep/night, regenerated OpenAPI). The client renders the
hypnogram but labels it an approximate layout and never recomputes;
real-series sources (Apple Health, Withings, Fitbit) stay false.
A writer whose stage rows all share one timestamp carries night totals,
not segments — reconstructing them as segments paints every stage
flush against the night's right edge. The session picker now prefers a
writer with genuinely timed rows among the granular candidates, so a
stage summary backfilled for a night an actually-timed writer also
recorded no longer evicts the real timeline; summary-only nights still
resolve. The hypnogram itself degrades a summary-shaped session to the
stage breakdown instead of drawing the false skyline.
Per-status texts check AI consent before the unchanged-data refresh can
re-stamp them, the comprehensive fingerprint folds in the comparison
baseline and generation language so toggling either regenerates once,
and profile, threshold and source-priority writes evict the analytics,
targets and derived caches they feed. CSV export neutralises spreadsheet
formula prefixes on free-text cells while numeric columns stay typed,
the derived batch validates its type token against the measurement enum
and carries a per-user rate limit, and a dose synced from the phone app
counts as the interactive write it is. Background cache refresh
failures log a structured event instead of vanishing, the warm queue
runs visit-triggered jobs alongside the nightly walk, the formatter
memo evicts one entry instead of flushing wholesale with its option
objects frozen, the targets cold build bounds its fan-out, and time in
bed unions every writer's envelope while stages stay with the richest
recorder.
Sleep nights collapse per writer instead of per source: several
HealthKit apps land behind the same source value, so a phone's coarse
awake and in-bed blocks could blend into or fully constitute a night
whose stages another writer had recorded. The winning writer per
session is the one with the most distinct granular stages, then the
user's source ladder, and its rows are kept whole. The device type is
threaded through every sleep read including the stage stacked bar, and
the sync overlap for late-arriving nights widens from one day to seven
so a night scored after the cursor passed is fetched on the next tick —
assembly is read-time, so affected nights heal without manual repair.
Mood notes expand to their full text in the list on desktop and touch,
replacing the hover-only tooltip, and the mood CSV export carries a
note column.
A night with coarse apple-health samples next to granular watch data
showed only awake and asleep — the per-session source pick now prefers
the source that knows its stages. Tour popovers clamp into the
viewport, wrap their footer and fall back to a bottom sheet on narrow
screens. Settings and admin sections share one alignment rule — icon
column left, everything else flush on the content column — with neutral
header icons, no duplicated section titles under the shell heading, and
every select on the account-style idiom with a visible chevron. The
dashboard's customize icon matches insights, the target-settings link
leaves the home charts, and the mood heatmap adopts the damped fills
the other mood charts already use.
Apple Health writes an unspecified ASLEEP aggregate alongside the granular
CORE/DEEP/REM partition for the same period. The asleep total already preferred
the granular partition, but the per-night/per-session `stages` map and the
hypnogram `segments` list recorded every stage row unconditionally, so a night
ended up carrying the granular set PLUS its ~equal bare twin — a double-height
green ASLEEP block on the stacked bar and the hypnogram, and a doubled total in
the analytics stage breakdown. Route the `stages` map and the `segments` list
through the same granular-over-bare gate as the asleep total: when a session
carries a granular stage, drop the redundant bare ASLEEP (and stage-less) rows
everywhere. WHOOP never emits a bare ASLEEP, so WHOOP nights are unaffected.
Apply the gate per session, not over the merged night pool, so a granular
overnight no longer strips a same-day bare-only nap's minutes from the night
total. Render the hypnogram per-segment in the stage palette (one ReferenceArea
per segment) instead of a single flat cyan line, and show the breakdown plus
totals footer whenever any per-stage minutes exist — reserving the unavailable
state for a truly empty session — so a legacy stage-summary night still surfaces
its breakdown. Thread the user's source priority into the CSV export's sleep
dedup, and honour offset with a true pre-slice night count on the sleep list.
Add reconstructSleepSessions — the session-level sibling to
reconstructSleepNights that keeps each sleep session separate (rather
than merging same-wake-day sessions under one key) and resolves every
stage row to its absolute span (start = measuredAt − duration), picks
one canonical source per session, and counts mid-sleep awakenings.
Add pickMainNightAndNaps to make the nap convention explicit: the main
night is the session with the most asleep minutes; every other session
on the same wake day is a nap, surfaced separately and never folded into
the headline.
These views are pure functions over existing per-stage rows — no schema
change, no new measurement type. They back the per-night list collapse,
the analytics reconciliation, and the hypnogram.
Apple Health (and some WHOOP shapes) write BOTH an unspecified ASLEEP
aggregate row AND the granular CORE/DEEP/REM breakdown for the same
sleep period. The per-night reconstruction summed both, so a real ~8 h
night surfaced as ~16 h across every sleep surface — the chart showed
~16-18 h points and the target-range 30-day average read ~16.4 h/day.
Prefer the granular partition: when any CORE/DEEP/REM stage is present
for a night/source, count only those; fall back to the bare ASLEEP (or
a stage-less legacy/manual) row only when no granular stage exists.
IN_BED and AWAKE stay excluded; dual-source nights still collapse to one
canonical source via the user's sleep priority ladder. The same rule
applies inside the per-source asleep tiebreak so a source writing both
shapes is not over-weighted.
Align the surfaces that bypassed the shared helper:
- insights/targets: SLEEP_DURATION was averaged as raw per-stage rows
(minutes) and fed into a target band expressed in hours, producing the
bogus 16.4 h/day. Reconstruct per-night time-asleep, convert to hours,
and classify + roll up consistency on the nightly hour totals.
- coach snapshot: route the sleep block through reconstructSleepNights
so the prompt narrates the same nightly numbers (was summing every
stage row, including IN_BED + AWAKE).
- sleep card chart: read /api/measurements/series?kind=sleep (night
reconstruction, hours) instead of the generic measurement
daily-average path, and label the axis in hours instead of minutes.
Add regression fixtures: a night with both a bare ASLEEP row and the
granular breakdown asserts the granular total (no double-count); a
dual-source night with both shapes per source; and a multi-night 30-day
average that lands at ~8 h, not ~16 h.
Per-stage SLEEP_DURATION rows carry the stage segment's END instant, so a
night where the user falls asleep before local midnight spread its stages
across two calendar days. Keying each stage by its own day split one
overnight sleep into two partial nights, and the headline last-night tile
showed only the post-midnight slice.
Reconstruct nights by clustering stage segments into sessions: a new session
starts only when the next segment's start (end minus its minute duration) is
more than three hours after the running session end. A single long stage
block no longer splits a night, a daytime nap stays separable from the
following overnight block, and the gap is measured on the absolute instant so
the clustering is DST-immune. Each session is keyed by the local wake day of
its latest segment end, matching the convention that a sleep session belongs
to the morning you wake up.
Collapse a multi-source night to one canonical source before summing, using
the user's sleep source-priority ladder (default WHOOP > Apple Health >
Withings), so a dual-source account no longer double-counts the total. Sources
are never blended within a night.
Bound the series sleep read to one year even on the 'Alle' range, matching the
slim slice's sleep window, so a multi-year dual-source account does not walk a
six-figure stage-row set into JS.
Add fixtures straddling local midnight, crossing a DST spring-forward, keeping
a nap separable, and collapsing a dual-source night.
SLEEP_DURATION is stored in minutes, one row per sleep stage per night
(IN_BED / AWAKE / ASLEEP / CORE / DEEP / REM) since the HealthKit
category-sample ingest landed. The value is not cumulative, so reading
the single most-recent row surfaced one stage's minutes — never the
night. The dashboard sleep tile and the sleep series therefore showed a
fragment of the night rather than the night.
Add a shared `summarizeSleepNights` helper that groups the per-stage
rows by the wake-day calendar date in the user's timezone and sums the
asleep stages (CORE + DEEP + REM, plus a legacy bare-duration row),
excluding IN_BED and AWAKE per the AASM convention already used by the
sleep score. Wire it into:
- the dashboard summary tile, which now emits last night's time asleep
in hours with an explicit `unit: "h"` and a per-stage breakdown for a
future detail view;
- the sleep series, which now returns one point per night (time asleep
in hours) plus a top-level `unit` for every kind so clients never
infer the unit;
- the slim summaries slice, so the web dashboard tile and the insights
overview read per-night totals (kept in canonical minutes there; the
web tile converts to hours) — strictly more correct than averaging
across stage rows, and parity with the iOS value.
Marc-André Bombeck