fix: Nightscout API silently truncated multi-day fetches to ~3-4 days

_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.

tests/test_reporting.py

@@ -1,9 +1,12 @@
+from datetime import date
+
 import pandas as pd
 import pytest
 
 from reporting import (
     agp_percentile_bands,
     bolus_stats,
+    completeness_warning,
     day_of_week_pattern,
     detect_events,
     gmi_percent,
@@ -93,6 +96,42 @@ def test_sensor_active_percent_handles_gaps():
     assert result == pytest.approx(50.0, abs=1.0)
 
 
+def test_completeness_warning_none_for_empty_glucose():
+    empty = pd.DataFrame(columns=["timestamp", "mmol"])
+    assert completeness_warning(empty, "2026-01-01", "2026-01-14") == "Geen glucosedata gevonden in deze periode."
+
+
+def test_completeness_warning_none_when_period_is_fully_covered():
+    # 14 volle dagen aan 5-minuten-metingen, precies de gekozen periode
+    timestamps = pd.date_range("2026-01-01 00:00", "2026-01-14 23:55", freq="5min")
+    glucose = pd.DataFrame({"timestamp": timestamps, "mmol": [6.0] * len(timestamps)})
+    assert completeness_warning(glucose, date(2026, 1, 1), date(2026, 1, 14)) is None
+
+
+def test_completeness_warning_flags_missing_days_at_start_of_period():
+    # gevraagd: 1 t/m 14 januari, maar data begint pas op 11 januari (de
+    # exacte bug: alleen de laatste ~4 dagen van een langere periode zijn
+    # opgehaald)
+    timestamps = pd.date_range("2026-01-11 00:00", "2026-01-14 23:55", freq="5min")
+    glucose = pd.DataFrame({"timestamp": timestamps, "mmol": [6.0] * len(timestamps)})
+    message = completeness_warning(glucose, date(2026, 1, 1), date(2026, 1, 14))
+    assert message is not None
+    assert "11-01-2026" in message
+    assert "10 dag" in message  # 1 t/m 10 januari ontbreken volledig = 10 dagen
+    assert "sensorhiaten" in message
+
+
+def test_completeness_warning_flags_low_coverage_without_start_gap():
+    # data start op tijd, maar met veel verspreide hiaten -> lage dekking
+    # zonder dat er een aaneengesloten gat aan het begin is
+    timestamps = pd.date_range("2026-01-01 00:00", periods=20, freq="5min")
+    glucose = pd.DataFrame({"timestamp": timestamps, "mmol": [6.0] * 20})
+    message = completeness_warning(glucose, date(2026, 1, 1), date(2026, 1, 14))
+    assert message is not None
+    assert "sensordekking" in message
+    assert "sensorhiaten" not in message  # dit is de generieke, niet de "ontbreekt volledig"-boodschap
+
+
 def test_detect_events_ignores_dip_shorter_than_minimum_duration():
     # dip van 10 minuten (< 15 min drempel) mag niet meetellen
     glucose = _series(