pytest-cov + pyproject.toml [tool.coverage.*] measure reporting.py,
nightscout_client.py, data_processing.py, pdf_export.py, profile_data.py,
ui_common.py, and auth.py; app.py and pages/*.py are omitted (thin
Streamlit UI scripts, not meaningfully unit-testable without a running
Streamlit session — the handful of similarly UI-coupled functions left
in ui_common.py/auth.py are marked "# pragma: no cover" with the same
rationale, since the logic they call into is already fully tested).
The Gitea Actions test job now runs with --cov and fails the build
below 80%; the coverage XML is uploaded as a build artifact and fed
into the SonarQube scan (closing the gap flagged in
homelab-cicd-werkinstructie.md). Backfilled a few missing branches
(get_colors() theme fallback, secondary-y-axis overlay traces) to reach
98% on the measured modules — comfortable headroom above the 80% gate.
Builds on #29/#30/#31.
Overlay the full insulin picture onto the interactive glucose charts:
basal rate as a semi-transparent step-area (profile schedule overridden
by active temp basal), bolus doses as size-scaled dots split into
food/correction/SMB categories (food and correction labeled with units,
SMB left unlabeled), carbs as bars, and the pump's target glucose as a
line — each with its own color, alpha, and legend entry. Shared trace-
building helpers live in ui_common.py so both pages (and the PDF report
in a follow-up PR) render identically.
Builds on the pump profile work in #29 (profile_data.py, load_profile()).
Fetch and parse the latest-used Nightscout profile (basal schedule, ISF,
carb ratio, DIA, targets) and show it as a new dashboard page: a list of
basal/ISF/carb-ratio segments plus a bar chart of basal rate by hour of
day. This is the data foundation for treatment overlays on the glucose
charts and the redesigned PDF report in follow-up PRs.
_entries_since/_treatments_since requested a single page via `count`,
but Nightscout's /api/v1/entries and /api/v1/treatments ignore a large
`count` and cap the response around ~1150/~700 documents regardless of
how far back the requested period goes. Every report page relying on
fetch_entries_range/fetch_treatments_range (7/14/30/90-day selectors)
was silently only getting the most recent ~3-4 days, no matter the
selected period.
Fixed by paginating with `find[date][$lte]` cursors in a new
_paginated_get(), walking back until the requested `since` boundary is
reached or the server returns a short/empty page (= genuinely no more
data, confirmed by manually paginating against the real instance:
entries go back 50+ days, treatments only ~4 days on this install).
Also added reporting.completeness_warning(), shared by the interactive
pages (via ui_common.render_completeness_warning) and the PDF export,
that distinguishes "a structural gap at the start of the period" (data
wasn't fetched/available) from "scattered gaps below the clinical AGP
coverage threshold" (Danne et al. 2017) — the previous single generic
"X% sensor coverage" message read as a CGM/sensor problem even when
the real cause was this fetch bug.
Dagoverzicht stacks one glucose trace per calendar day (small multiples
via a shared 0-24h x-axis). The two event pages share a new
render_event_level() helper in ui_common.py so Level 1/Level 2 hypo and
hyper are rendered identically: count/avg/longest/events-per-week
metrics, a time-of-day histogram, and a table of individual events.
Co-Authored-By: Claude Sonnet 5 <[email protected]>
Wires reporting.py's stats into two new pages: a summary panel (data
completeness, GMI, %CV, 5-band time-in-range vs. consensus targets) and
the standard AGP percentile chart (5th-95th and 25th-75th bands plus
median, aggregated by time-of-day across the selected period).
Co-Authored-By: Claude Sonnet 5 <[email protected]>
First increment of the clinical reporting feature (see
docs/requirements-reporting.md and docs/design-reporting.md): moves the
existing live view to pages/1_Live.py, adds a password gate since the
dashboard URL will be shared with the diabetes team, adds
fetch_entries_range/fetch_treatments_range for multi-day report queries,
and adds reporting.py with the core clinical calculations (GMI, %CV,
5-band time-in-range, hypo/hyper event detection per the Battelino et al.
2019 persistence rule). No report pages wired up yet — that's next.
Co-Authored-By: Claude Sonnet 5 <[email protected]>
willemjan
