test indent issue

Dockerfile

@@ -1,5 +1,12 @@
 FROM python:3.12-slim
 
+ENV HOME=/app \
+    PYTHONUNBUFFERED=1 \
+    STREAMLIT_SERVER_PORT=8501 \
+    STREAMLIT_SERVER_ADDRESS=0.0.0.0 \
+    STREAMLIT_SERVER_HEADLESS=true \
+    STREAMLIT_BROWSER_GATHER_USAGE_STATS=false
+
 WORKDIR /app
 
 # Systeem-dependency voor de HEALTHCHECK hieronder
@@ -11,8 +18,9 @@ RUN pip install --no-cache-dir -r requirements.txt
 
 COPY . .
 
+RUN chgrp -R 0 /app && chmod -R g=u /app
+
+USER 1001
 EXPOSE 8501
-
 HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health || exit 1
-
+CMD ["streamlit", "run", "app.py"]
-ENTRYPOINT ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0"]

Jenkinsfile

@@ -1,11 +1,103 @@
 pipeline {
-    agent any
+    agent {
+        label 'ssh-agent'
+    }
+
+
+    environment {
+        REGISTRY    = 'gitea.zb-kw.duckdns.org'
+        IMAGE       = "${REGISTRY}/willemjan/glucose-dashboard"
+        OC_SERVER   = 'https://api.rm1.0a51.p1.openshiftapps.com:6443'
+        OC_PROJECT  = 'wulsspaans-dev'
+    }
+
+    options {
+        buildDiscarder(logRotator(numToKeepStr: '20'))
+        timeout(time: 20, unit: 'MINUTES')
+    }
 
     stages {
-        stage('Do nothing') {
+        stage('Checkout') {
             steps {
-                sh '/bin/true'
+                checkout scm
+                script {
+                    env.TAG = sh(script: 'git rev-parse --short HEAD',
+                                 returnStdout: true).trim()
+                }
+            }
+        }
+
+        stage('Test') {
+            steps {
+                sh '''
+                    pip install --break-system-packages --no-warn-script-location -q -r requirements.txt
+                    python -m pytest -q --junitxml=report.xml
+                '''
+            }
+            post {
+                always { junit allowEmptyResults: true, testResults: 'report.xml' }
+            }
+        }
+
+        stage('Build & push image') {
+            steps {
+                withCredentials([usernamePassword(
+                    credentialsId: 'gitea_user',
+                    usernameVariable: 'REG_USER',
+                    passwordVariable: 'REG_PASS')]) {
+                    sh '''
+                        echo "$REG_PASS" | docker login $REGISTRY -u "$REG_USER" --password-stdin
+                        docker build -t $IMAGE:$TAG -t $IMAGE:latest .
+                        docker push $IMAGE:$TAG
+                        docker push $IMAGE:latest
+                    '''
+                }
+            }
+        }
+
+        stage('Scan') {
+            steps {
+                sh '''
+                    docker run --rm \
+                      -v /var/run/docker.sock:/var/run/docker.sock \
+                      -v trivy-cache:/root/.cache/trivy \
+                      aquasec/trivy:latest image \
+                        --severity HIGH,CRITICAL \
+                        --ignore-unfixed \
+                        --exit-code 0 \
+                        $IMAGE:$TAG
+                '''
+            }
+        }
+
+        stage('Deploy to OpenShift') {
+            steps {
+                withCredentials([string(
+                    credentialsId: 'openshift-token',
+                    variable: 'OC_TOKEN')]) {
+                    sh '''
+                        oc login --token="$OC_TOKEN" --server="$OC_SERVER"
+                        oc project $OC_PROJECT
+
+                        oc apply -f openshift/service.yaml
+                        oc apply -f openshift/route.yaml
+                        oc apply -f openshift/configmap.yaml
+                        oc apply -f openshift/deployment.yaml
+
+                        oc set image deployment/glucose-dashboard \
+                            glucose-dashboard=$IMAGE:$TAG
+
+                        oc rollout status deployment/glucose-dashboard --timeout=5m
+                    '''
+                }
+            }
+            post {
+                always  { sh 'oc logout || true' }
+                success {
+                    sh 'echo "Deployed: $(oc get route glucose-dashboard -o jsonpath={.spec.host})" || true'
+                }
             }
         }
     }
+    
 }

nightscout_client.py

@@ -252,21 +252,3 @@ def fetch_treatments_range(start_date: date, end_date: date) -> pd.DataFrame:
     since = datetime.combine(start_date, time.min, tzinfo=timezone.utc)
     until = datetime.combine(end_date, time.max, tzinfo=timezone.utc)
     return _treatments_since(since, until)
-
-
-def fetch_profile() -> dict:
-    """Haal het meest recent gebruikte pompprofiel op.
-
-    Nightscout's /api/v1/profile.json geeft profieldocumenten terug, nieuwste
-    eerst; met count=1 krijgen we alleen het actief gebruikte document. Een
-    profiel is geen tijdreeks (in tegenstelling tot entries/treatments) dus
-    geen paginering nodig — één klein verzoek volstaat.
-
-    Geeft {} terug als er geen profiel bestaat (bijv. lege Nightscout-instantie).
-    Het resultaat is het rauwe Nightscout-documument; zie profile_data.parse_profile()
-    voor de genormaliseerde vorm (basaalschema, ISF, koolhydraatratio, DIA, streefwaarden).
-    """
-    data = _get("/api/v1/profile.json", {"count": 1})
-    if not data:
-        return {}
-    return data[0]

openshift/configmap.yaml

@@ -0,0 +1,6 @@
+apiVersion: v1
+kind: ConfigMap
+metadata:
+  name: glucose-dashboard-config
+data:
+  NIGHTSCOUT_URL: "https://zb-ns.duckdns.org"

openshift/deployment.yaml

@@ -0,0 +1,35 @@
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: glucose-dashboard
+  labels:
+    app: glucose-dashboard
+spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      app: glucose-dashboard
+  template:
+    metadata:
+      labels:
+        app: glucose-dashboard
+    spec:
+      imagePullSecrets:
+        - name: gitea-registry
+      containers:
+        - name: glucose-dashboard
+          image: PLACEHOLDER
+          envFrom:
+            - configMapRef:
+                name: glucose-dashboard-config
+          ports:
+            - containerPort: 8501
+          resources:
+            requests: { cpu: 100m, memory: 256Mi }
+            limits:   { cpu: 500m, memory: 512Mi }
+          readinessProbe:
+            httpGet: { path: /_stcore/health, port: 8501 }
+            initialDelaySeconds: 10
+          livenessProbe:
+            httpGet: { path: /_stcore/health, port: 8501 }
+            initialDelaySeconds: 30

openshift/route.yaml

@@ -0,0 +1,13 @@
+apiVersion: route.openshift.io/v1
+kind: Route
+metadata:
+  name: glucose-dashboard
+spec:
+  to:
+    kind: Service
+    name: glucose-dashboard
+  port:
+    targetPort: 8501
+  tls:
+    termination: edge
+    insecureEdgeTerminationPolicy: Redirect

openshift/service.yaml

@@ -0,0 +1,10 @@
+apiVersion: v1
+kind: Service
+metadata:
+  name: glucose-dashboard
+spec:
+  selector:
+    app: glucose-dashboard
+  ports:
+    - port: 8501
+      targetPort: 8501

pages/9_Insulineprofiel.py

@@ -1,98 +0,0 @@
-import pandas as pd
-import plotly.graph_objects as go
-import requests
-import streamlit as st
-
-from auth import require_auth
-from nightscout_client import NightscoutConfigError
-from profile_data import segments_table, segments_to_hourly_bars, total_daily_basal
-from ui_common import get_colors, load_profile
-
-st.set_page_config(page_title="Glucose dashboard — Insulineprofiel", page_icon="📊", layout="wide")
-require_auth()
-
-st.title("Insulineprofiel")
-st.caption("Het meest recent gebruikte pompprofiel: basaalschema, ISF, koolhydraatratio en DIA.")
-
-try:
-    profile = load_profile()
-except NightscoutConfigError as exc:
-    st.error(str(exc))
-    st.stop()
-except (requests.RequestException, ValueError) as exc:
-    st.error(f"Kon geen profiel ophalen van Nightscout: {exc}")
-    st.stop()
-
-if not profile:
-    st.info("Geen pompprofiel gevonden op deze Nightscout-instantie.")
-    st.stop()
-
-colors = get_colors()
-
-col1, col2 = st.columns(2)
-col1.metric("DIA (werkingsduur insuline)", f"{profile['dia']:.1f} uur")
-col2.caption(f"Profielnaam: {profile['name'] or '—'}")
-
-st.subheader("Basaalschema")
-bars = segments_to_hourly_bars(profile["basal"])
-fig = go.Figure(
-    go.Scatter(
-        x=[b["hour"] for b in bars],
-        y=[b["value"] for b in bars],
-        mode="lines",
-        line={"shape": "hv", "color": colors["basal"], "width": 2},
-        fill="tozeroy",
-        fillcolor=colors["basal"],
-        opacity=0.7,
-        name="Basaal",
-        hovertemplate="%{x:.0f}:00 · %{y:.2f} E/uur<extra></extra>",
-    )
-)
-fig.update_layout(
-    paper_bgcolor="rgba(0,0,0,0)",
-    plot_bgcolor="rgba(0,0,0,0)",
-    font_color=colors["text"],
-    height=320,
-    margin={"l": 10, "r": 10, "t": 10, "b": 10},
-    xaxis={"title": "Uur van de dag", "range": [0, 24], "dtick": 2, "gridcolor": colors["grid"]},
-    yaxis={"title": "E/uur", "gridcolor": colors["grid"], "rangemode": "tozero"},
-    showlegend=False,
-)
-st.plotly_chart(fig, width="stretch")
-
-basal_rows = segments_table(profile["basal"])
-st.dataframe(
-    pd.DataFrame(basal_rows).rename(
-        columns={"start": "Van", "end": "Tot", "value": "Basaalsnelheid (E/uur)"}
-    ),
-    width="stretch",
-    hide_index=True,
-)
-
-col_isf, col_ratio = st.columns(2)
-with col_isf:
-    st.subheader("Insulinegevoeligheid (ISF)")
-    isf_rows = segments_table(profile["sens"])
-    st.dataframe(
-        pd.DataFrame(isf_rows).rename(
-            columns={"start": "Van", "end": "Tot", "value": "ISF (mmol/L per E)"}
-        ),
-        width="stretch",
-        hide_index=True,
-    )
-
-with col_ratio:
-    st.subheader("Koolhydraatratio")
-    ratio_rows = segments_table(profile["carbratio"])
-    st.dataframe(
-        pd.DataFrame(ratio_rows).rename(
-            columns={"start": "Van", "end": "Tot", "value": "Ratio (g koolhydraten per E)"}
-        ),
-        width="stretch",
-        hide_index=True,
-    )
-
-st.caption(
-    f"Totale dagelijkse basaal: {total_daily_basal(profile['basal']):.1f} E "
-    "(volgens profielschema, exclusief tijdelijke aanpassingen)."
-)

profile_data.py

@@ -1,146 +0,0 @@
-"""
-Parsing van het Nightscout-pompprofiel (/api/v1/profile): basaalschema,
-insulinegevoeligheid (ISF), koolhydraatratio, DIA en streefwaarden.
-
-Framework-vrije module (geen streamlit-import), zelfde opzet als reporting.py:
-puur functies op dicts, zodat dit los van de UI te unit-testen is. Zie
-nightscout_client.fetch_profile() voor de ruwe fetch; deze module normaliseert
-alleen (uren -> minuten sinds middernacht, mg/dl -> mmol/L waar nodig).
-"""
-
-from __future__ import annotations
-
-from nightscout_client import mgdl_to_mmol
-
-SEGMENT_FIELDS = ("basal", "sens", "carbratio", "target_low", "target_high")
-
-
-def _time_to_minutes(time_str: str) -> int:
-    """Zet 'HH:MM' (Nightscout's segmenttijd-notatie) om naar minuten sinds middernacht."""
-    hours, minutes = time_str.split(":")
-    return int(hours) * 60 + int(minutes)
-
-
-def _parse_segments(raw_segments: list[dict], *, to_mmol: bool = False) -> list[dict]:
-    """Zet Nightscout-segmenten ([{'time': 'HH:MM', 'value': ...}, ...]) om naar
-    [{'minutes': int, 'value': float}, ...], oplopend gesorteerd op tijd."""
-    segments = []
-    for seg in raw_segments:
-        value = float(seg["value"])
-        if to_mmol:
-            value = mgdl_to_mmol(value)
-        segments.append({"minutes": _time_to_minutes(seg["time"]), "value": value})
-    return sorted(segments, key=lambda s: s["minutes"])
-
-
-def parse_profile(raw: dict) -> dict:
-    """Parse één Nightscout-profieldocument (zoals teruggegeven door
-    nightscout_client.fetch_profile()) naar een genormaliseerde dict:
-
-        {
-            "name": str,
-            "units": "mmol",           # altijd genormaliseerd, ongeacht bronformaat
-            "dia": float,               # uur
-            "basal": [{"minutes": int, "value": float}, ...],       # E/uur
-            "sens": [{"minutes": int, "value": float}, ...],        # mmol/L per E (ISF)
-            "carbratio": [{"minutes": int, "value": float}, ...],   # g koolhydraten per E
-            "target_low": [{"minutes": int, "value": float}, ...],  # mmol/L
-            "target_high": [{"minutes": int, "value": float}, ...], # mmol/L
-        }
-
-    Geeft {} terug als er geen (bruikbaar) profiel is.
-    """
-    if not raw:
-        return {}
-
-    default_name = raw.get("defaultProfile")
-    store = raw.get("store", {})
-    profile = store.get(default_name) if default_name else None
-    if profile is None and store:
-        # defaultProfile ontbreekt of matcht niet met een sleutel in store:
-        # val terug op het enige/eerste beschikbare profiel.
-        profile = next(iter(store.values()))
-    if profile is None:
-        return {}
-
-    units = str(profile.get("units", "mg/dl")).strip().lower()
-    to_mmol = units != "mmol"
-
-    return {
-        "name": default_name or "",
-        "units": "mmol",
-        "dia": float(profile.get("dia", 0) or 0),
-        "basal": _parse_segments(profile.get("basal", [])),
-        "sens": _parse_segments(profile.get("sens", []), to_mmol=to_mmol),
-        "carbratio": _parse_segments(profile.get("carbratio", [])),
-        "target_low": _parse_segments(profile.get("target_low", []), to_mmol=to_mmol),
-        "target_high": _parse_segments(profile.get("target_high", []), to_mmol=to_mmol),
-    }
-
-
-def value_at(segments: list[dict], minutes: int) -> float | None:
-    """Geef de waarde terug die actief is op het gegeven tijdstip (minuten
-    sinds middernacht) — het laatste segment met `minutes <= t`. Ligt `t` vóór
-    het eerste segment van de dag, dan geldt het laatste segment (dat loopt
-    door vanaf de vorige dag, want een profiel dekt altijd de volle 24 uur).
-
-    Geeft None terug als `segments` leeg is.
-    """
-    if not segments:
-        return None
-    active = None
-    for seg in segments:
-        if seg["minutes"] <= minutes:
-            active = seg
-        else:
-            break
-    if active is None:
-        active = segments[-1]
-    return active["value"]
-
-
-def _format_time(minutes: int) -> str:
-    """Zet minuten sinds middernacht om naar 'HH:MM'."""
-    return f"{minutes // 60:02d}:{minutes % 60:02d}"
-
-
-def segments_table(segments: list[dict]) -> list[dict]:
-    """Zet segmenten om naar rijen met een start- en eindtijd voor tabelweergave:
-    [{'start': 'HH:MM', 'end': 'HH:MM', 'value': float}, ...]. Het laatste
-    segment loopt door tot 24:00 (een profiel dekt altijd de volle dag)."""
-    rows = []
-    for i, seg in enumerate(segments):
-        end_minutes = segments[i + 1]["minutes"] if i + 1 < len(segments) else 24 * 60
-        rows.append(
-            {
-                "start": _format_time(seg["minutes"]),
-                "end": "24:00" if end_minutes == 24 * 60 else _format_time(end_minutes),
-                "value": seg["value"],
-            }
-        )
-    return rows
-
-
-def total_daily_basal(segments: list[dict]) -> float:
-    """Totale basaaldosis per dag in E: som van elk segment se duur (uur) x snelheid (E/uur)."""
-    if not segments:
-        return 0.0
-    total = 0.0
-    for i, seg in enumerate(segments):
-        end_minutes = segments[i + 1]["minutes"] if i + 1 < len(segments) else 24 * 60
-        total += seg["value"] * (end_minutes - seg["minutes"]) / 60
-    return total
-
-
-def segments_to_hourly_bars(segments: list[dict]) -> list[dict]:
-    """Zet segmenten om naar een lijst geschikt voor een staafgrafiek per uur van
-    de dag: [{'hour': float, 'value': float}, ...], met een extra punt op uur 24
-    (gelijk aan het eerste segment) zodat een staaf/stap-grafiek de volle dag dekt.
-
-    Gebruikt door de basaalgrafiek op de Insulineprofiel-pagina.
-    """
-    if not segments:
-        return []
-    bars = [{"hour": seg["minutes"] / 60, "value": seg["value"]} for seg in segments]
-    bars.append({"hour": 24.0, "value": segments[0]["value"]})
-    return bars

tests/test_nightscout_client.py

@@ -357,29 +357,6 @@ def test_fetch_treatments_range_retrieves_full_history_even_with_a_hidden_server
     assert result["timestamp"].max().date() == end_date
 
 
-def test_fetch_profile_returns_first_document(monkeypatch):
-    monkeypatch.setenv("NIGHTSCOUT_URL", "https://example.com")
-    payload = [{"defaultProfile": "Default", "store": {"Default": {"dia": "5"}}}]
-
-    seen_params = []
-    monkeypatch.setattr(
-        ns.requests,
-        "get",
-        lambda *a, **k: (seen_params.append(k["params"]), FakeResponse(payload))[1],
-    )
-
-    result = ns.fetch_profile()
-    assert result == payload[0]
-    assert seen_params[0]["count"] == 1
-
-
-def test_fetch_profile_handles_empty_response(monkeypatch):
-    monkeypatch.setenv("NIGHTSCOUT_URL", "https://example.com")
-    monkeypatch.setattr(ns.requests, "get", lambda *a, **k: FakeResponse([]))
-
-    assert ns.fetch_profile() == {}
-
-
 def test_paginated_get_uses_created_at_field_for_treatments_cursor(monkeypatch):
     """Losstaande, gerichte assertie op het daadwerkelijke queryparameter-veld
     — moet `find[created_at][$lte]` zijn, nooit `find[date][$lte]`, voor het

tests/test_profile_data.py

@@ -1,117 +0,0 @@
-import pytest
-
-import profile_data as pd_
-
-
-def _raw_profile(units="mg/dl", default_name="Default"):
-    return {
-        "defaultProfile": default_name,
-        "store": {
-            "Default": {
-                "units": units,
-                "dia": "5",
-                "basal": [
-                    {"time": "00:00", "value": "0.8"},
-                    {"time": "06:00", "value": "1.2"},
-                    {"time": "22:00", "value": "0.7"},
-                ],
-                "sens": [{"time": "00:00", "value": "50"}],
-                "carbratio": [{"time": "00:00", "value": "10"}],
-                "target_low": [{"time": "00:00", "value": "90"}],
-                "target_high": [{"time": "00:00", "value": "120"}],
-            }
-        },
-    }
-
-
-def test_parse_profile_returns_empty_dict_for_empty_input():
-    assert pd_.parse_profile({}) == {}
-
-
-def test_parse_profile_converts_mgdl_to_mmol():
-    profile = pd_.parse_profile(_raw_profile(units="mg/dl"))
-    assert profile["units"] == "mmol"
-    # 90 mg/dl -> ~5.0 mmol/L, 120 mg/dl -> ~6.7 mmol/L, 50 mg/dl (ISF) -> ~2.8 mmol/L
-    assert profile["target_low"][0]["value"] == pytest.approx(5.0, abs=0.05)
-    assert profile["target_high"][0]["value"] == pytest.approx(6.7, abs=0.05)
-    assert profile["sens"][0]["value"] == pytest.approx(2.8, abs=0.05)
-
-
-def test_parse_profile_leaves_mmol_profiles_unconverted():
-    profile = pd_.parse_profile(_raw_profile(units="mmol"))
-    assert profile["target_low"][0]["value"] == pytest.approx(90.0)
-
-
-def test_parse_profile_does_not_convert_basal_or_carbratio():
-    profile = pd_.parse_profile(_raw_profile(units="mg/dl"))
-    assert profile["basal"][0]["value"] == pytest.approx(0.8)
-    assert profile["carbratio"][0]["value"] == pytest.approx(10.0)
-
-
-def test_parse_profile_sorts_basal_segments_by_time():
-    raw = _raw_profile()
-    raw["store"]["Default"]["basal"] = [
-        {"time": "22:00", "value": "0.7"},
-        {"time": "00:00", "value": "0.8"},
-        {"time": "06:00", "value": "1.2"},
-    ]
-    profile = pd_.parse_profile(raw)
-    assert [seg["minutes"] for seg in profile["basal"]] == [0, 360, 1320]
-
-
-def test_parse_profile_falls_back_to_first_profile_when_default_name_missing():
-    raw = _raw_profile(default_name="DoesNotExist")
-    profile = pd_.parse_profile(raw)
-    assert profile["dia"] == pytest.approx(5.0)
-
-
-def test_parse_profile_dia_and_name():
-    profile = pd_.parse_profile(_raw_profile())
-    assert profile["dia"] == pytest.approx(5.0)
-    assert profile["name"] == "Default"
-
-
-def test_value_at_returns_active_segment():
-    segments = [{"minutes": 0, "value": 0.8}, {"minutes": 360, "value": 1.2}, {"minutes": 1320, "value": 0.7}]
-    assert pd_.value_at(segments, 100) == pytest.approx(0.8)
-    assert pd_.value_at(segments, 360) == pytest.approx(1.2)
-    assert pd_.value_at(segments, 1000) == pytest.approx(1.2)
-    assert pd_.value_at(segments, 1350) == pytest.approx(0.7)
-
-
-def test_value_at_wraps_to_last_segment_before_first():
-    segments = [{"minutes": 360, "value": 1.2}, {"minutes": 1320, "value": 0.7}]
-    assert pd_.value_at(segments, 100) == pytest.approx(0.7)
-
-
-def test_value_at_empty_segments_returns_none():
-    assert pd_.value_at([], 100) is None
-
-
-def test_segments_table_computes_end_times_from_next_segment():
-    segments = [{"minutes": 0, "value": 0.8}, {"minutes": 360, "value": 1.2}]
-    rows = pd_.segments_table(segments)
-    assert rows == [
-        {"start": "00:00", "end": "06:00", "value": 0.8},
-        {"start": "06:00", "end": "24:00", "value": 1.2},
-    ]
-
-
-def test_segments_to_hourly_bars_closes_the_24h_loop():
-    segments = [{"minutes": 0, "value": 0.8}, {"minutes": 360, "value": 1.2}]
-    bars = pd_.segments_to_hourly_bars(segments)
-    assert bars[-1] == {"hour": 24.0, "value": 0.8}
-
-
-def test_segments_to_hourly_bars_empty_input():
-    assert pd_.segments_to_hourly_bars([]) == []
-
-
-def test_total_daily_basal_weights_by_segment_duration():
-    # 6h @ 0.8 + 18h @ 1.2 = 4.8 + 21.6 = 26.4
-    segments = [{"minutes": 0, "value": 0.8}, {"minutes": 360, "value": 1.2}]
-    assert pd_.total_daily_basal(segments) == pytest.approx(26.4)
-
-
-def test_total_daily_basal_empty_input():
-    assert pd_.total_daily_basal([]) == 0.0

ui_common.py

@@ -14,8 +14,7 @@ import pandas as pd
 import plotly.graph_objects as go
 import streamlit as st
 
-from nightscout_client import fetch_entries_range, fetch_profile, fetch_treatments_range
+from nightscout_client import fetch_entries_range, fetch_treatments_range
-from profile_data import parse_profile
 from reporting import (
     HIGH,
     LOW,
@@ -58,11 +57,6 @@ PALETTE = {
         "tir_in_range": "#0ca30c",
         "tir_high": "#fab219",
         "tir_very_high": "#c76f0a",
-        "basal": "#7b5ea3",
-        "bolus_food": "#1baf7a",
-        "bolus_correction": "#2a78d6",
-        "bolus_smb": "#898781",
-        "target": "#52514e",
     },
     "dark": {
         "glucose": "#3987e5",
@@ -82,11 +76,6 @@ PALETTE = {
         "tir_in_range": "#0ca30c",
         "tir_high": "#fab219",
         "tir_very_high": "#d9852e",
-        "basal": "#9b7ec2",
-        "bolus_food": "#199e70",
-        "bolus_correction": "#3987e5",
-        "bolus_smb": "#898781",
-        "target": "#c3c2b7",
     },
 }
 
@@ -140,15 +129,6 @@ def load_range_data(start: date, end: date):
     return glucose, treatments
 
 
-@st.cache_data(ttl=21600, show_spinner="Profiel ophalen van Nightscout...")
-def load_profile() -> dict:
-    """Gecachete profiel-fetch. Langere TTL dan load_range_data (6 uur i.p.v.
-    1 uur): een pompprofiel wijzigt zelden, in tegenstelling tot glucose-/
-    behandeldata van een lopende periode."""
-    raw = fetch_profile()
-    return parse_profile(raw)
-
-
 def add_threshold_lines(fig: go.Figure, colors: dict, row: int | None = None) -> None:
     """Teken de 4 klinische drempellijnen (3.0/3.9/10.0/13.9 mmol/L) op een grafiek.