feat: Phase 0c - health_metrics.py module complete

Data Layer:
- get_resting_heart_rate_data() - avg RHR with min/max trend
- get_heart_rate_variability_data() - avg HRV with min/max trend
- get_vo2_max_data() - latest VO2 Max with date

Placeholder Layer:
- get_vitals_avg_hr() - refactored to use data layer
- get_vitals_avg_hrv() - refactored to use data layer
- get_vitals_vo2_max() - refactored to use data layer

All 3 health data functions + 3 placeholder refactors complete.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

backend/data_layer/__init__.py

@@ -33,9 +33,9 @@ from .body_metrics import *
 from .nutrition_metrics import *
 from .activity_metrics import *
 from .recovery_metrics import *
+from .health_metrics import *
 
 # Future imports (will be added as modules are created):
-# from .health_metrics import *
 # from .goals import *
 # from .correlations import *
 
@@ -66,4 +66,9 @@ __all__ = [
     'get_sleep_duration_data',
     'get_sleep_quality_data',
     'get_rest_days_data',
+
+    # Health Metrics
+    'get_resting_heart_rate_data',
+    'get_heart_rate_variability_data',
+    'get_vo2_max_data',
 ]

backend/data_layer/health_metrics.py

@@ -0,0 +1,197 @@
+"""
+Health Metrics Data Layer
+
+Provides structured data for vital signs and health monitoring.
+
+Functions:
+    - get_resting_heart_rate_data(): Average RHR with trend
+    - get_heart_rate_variability_data(): Average HRV with trend
+    - get_vo2_max_data(): Latest VO2 Max value
+
+All functions return structured data (dict) without formatting.
+Use placeholder_resolver.py for formatted strings for AI.
+
+Phase 0c: Multi-Layer Architecture
+Version: 1.0
+"""
+
+from typing import Dict, List, Optional
+from datetime import datetime, timedelta, date
+from db import get_db, get_cursor, r2d
+from data_layer.utils import calculate_confidence, safe_float, safe_int
+
+
+def get_resting_heart_rate_data(
+    profile_id: str,
+    days: int = 7
+) -> Dict:
+    """
+    Get average resting heart rate with trend.
+
+    Args:
+        profile_id: User profile ID
+        days: Analysis window (default 7)
+
+    Returns:
+        {
+            "avg_rhr": int,              # beats per minute
+            "min_rhr": int,
+            "max_rhr": int,
+            "measurements": int,
+            "confidence": str,
+            "days_analyzed": int
+        }
+
+    Migration from Phase 0b:
+        OLD: get_vitals_avg_hr(pid, days) formatted string
+        NEW: Structured data with min/max
+    """
+    with get_db() as conn:
+        cur = get_cursor(conn)
+        cutoff = (datetime.now() - timedelta(days=days)).strftime('%Y-%m-%d')
+
+        cur.execute(
+            """SELECT
+                AVG(resting_hr) as avg,
+                MIN(resting_hr) as min,
+                MAX(resting_hr) as max,
+                COUNT(*) as count
+               FROM vitals_baseline
+               WHERE profile_id=%s
+                 AND date >= %s
+                 AND resting_hr IS NOT NULL""",
+            (profile_id, cutoff)
+        )
+        row = cur.fetchone()
+
+        if not row or row['count'] == 0:
+            return {
+                "avg_rhr": 0,
+                "min_rhr": 0,
+                "max_rhr": 0,
+                "measurements": 0,
+                "confidence": "insufficient",
+                "days_analyzed": days
+            }
+
+        measurements = row['count']
+        confidence = calculate_confidence(measurements, days, "general")
+
+        return {
+            "avg_rhr": safe_int(row['avg']),
+            "min_rhr": safe_int(row['min']),
+            "max_rhr": safe_int(row['max']),
+            "measurements": measurements,
+            "confidence": confidence,
+            "days_analyzed": days
+        }
+
+
+def get_heart_rate_variability_data(
+    profile_id: str,
+    days: int = 7
+) -> Dict:
+    """
+    Get average heart rate variability with trend.
+
+    Args:
+        profile_id: User profile ID
+        days: Analysis window (default 7)
+
+    Returns:
+        {
+            "avg_hrv": int,              # milliseconds
+            "min_hrv": int,
+            "max_hrv": int,
+            "measurements": int,
+            "confidence": str,
+            "days_analyzed": int
+        }
+
+    Migration from Phase 0b:
+        OLD: get_vitals_avg_hrv(pid, days) formatted string
+        NEW: Structured data with min/max
+    """
+    with get_db() as conn:
+        cur = get_cursor(conn)
+        cutoff = (datetime.now() - timedelta(days=days)).strftime('%Y-%m-%d')
+
+        cur.execute(
+            """SELECT
+                AVG(hrv) as avg,
+                MIN(hrv) as min,
+                MAX(hrv) as max,
+                COUNT(*) as count
+               FROM vitals_baseline
+               WHERE profile_id=%s
+                 AND date >= %s
+                 AND hrv IS NOT NULL""",
+            (profile_id, cutoff)
+        )
+        row = cur.fetchone()
+
+        if not row or row['count'] == 0:
+            return {
+                "avg_hrv": 0,
+                "min_hrv": 0,
+                "max_hrv": 0,
+                "measurements": 0,
+                "confidence": "insufficient",
+                "days_analyzed": days
+            }
+
+        measurements = row['count']
+        confidence = calculate_confidence(measurements, days, "general")
+
+        return {
+            "avg_hrv": safe_int(row['avg']),
+            "min_hrv": safe_int(row['min']),
+            "max_hrv": safe_int(row['max']),
+            "measurements": measurements,
+            "confidence": confidence,
+            "days_analyzed": days
+        }
+
+
+def get_vo2_max_data(
+    profile_id: str
+) -> Dict:
+    """
+    Get latest VO2 Max value with date.
+
+    Args:
+        profile_id: User profile ID
+
+    Returns:
+        {
+            "vo2_max": float,            # ml/kg/min
+            "date": date,
+            "confidence": str
+        }
+
+    Migration from Phase 0b:
+        OLD: get_vitals_vo2_max(pid) formatted string
+        NEW: Structured data with date
+    """
+    with get_db() as conn:
+        cur = get_cursor(conn)
+        cur.execute(
+            """SELECT vo2_max, date FROM vitals_baseline
+               WHERE profile_id=%s AND vo2_max IS NOT NULL
+               ORDER BY date DESC LIMIT 1""",
+            (profile_id,)
+        )
+        row = cur.fetchone()
+
+        if not row:
+            return {
+                "vo2_max": 0.0,
+                "date": None,
+                "confidence": "insufficient"
+            }
+
+        return {
+            "vo2_max": safe_float(row['vo2_max']),
+            "date": row['date'],
+            "confidence": "high"
+        }

backend/placeholder_resolver.py

@@ -33,6 +33,11 @@ from data_layer.recovery_metrics import (
     get_sleep_quality_data,
     get_rest_days_data
 )
+from data_layer.health_metrics import (
+    get_resting_heart_rate_data,
+    get_heart_rate_variability_data,
+    get_vo2_max_data
+)
 
 
 # ── Helper Functions ──────────────────────────────────────────────────────────
@@ -351,55 +356,49 @@ def get_rest_days_count(profile_id: str, days: int = 30) -> str:
 
 
 def get_vitals_avg_hr(profile_id: str, days: int = 7) -> str:
-    """Calculate average resting heart rate."""
+    """
-    with get_db() as conn:
+    Calculate average resting heart rate.
-        cur = get_cursor(conn)
-        cutoff = (datetime.now() - timedelta(days=days)).strftime('%Y-%m-%d')
-        cur.execute(
-            """SELECT AVG(resting_hr) as avg FROM vitals_baseline
-               WHERE profile_id=%s AND date >= %s AND resting_hr IS NOT NULL""",
-            (profile_id, cutoff)
-        )
-        row = cur.fetchone()
 
-        if row and row['avg']:
+    Phase 0c: Refactored to use data_layer.health_metrics.get_resting_heart_rate_data()
-            return f"{int(row['avg'])} bpm"
+    This function now only FORMATS the data for AI consumption.
+    """
+    data = get_resting_heart_rate_data(profile_id, days)
+
+    if data['confidence'] == 'insufficient':
         return "nicht verfügbar"
 
+    return f"{data['avg_rhr']} bpm"
+
 
 def get_vitals_avg_hrv(profile_id: str, days: int = 7) -> str:
-    """Calculate average heart rate variability."""
+    """
-    with get_db() as conn:
+    Calculate average heart rate variability.
-        cur = get_cursor(conn)
-        cutoff = (datetime.now() - timedelta(days=days)).strftime('%Y-%m-%d')
-        cur.execute(
-            """SELECT AVG(hrv) as avg FROM vitals_baseline
-               WHERE profile_id=%s AND date >= %s AND hrv IS NOT NULL""",
-            (profile_id, cutoff)
-        )
-        row = cur.fetchone()
 
-        if row and row['avg']:
+    Phase 0c: Refactored to use data_layer.health_metrics.get_heart_rate_variability_data()
-            return f"{int(row['avg'])} ms"
+    This function now only FORMATS the data for AI consumption.
+    """
+    data = get_heart_rate_variability_data(profile_id, days)
+
+    if data['confidence'] == 'insufficient':
         return "nicht verfügbar"
 
+    return f"{data['avg_hrv']} ms"
+
 
 def get_vitals_vo2_max(profile_id: str) -> str:
-    """Get latest VO2 Max value."""
+    """
-    with get_db() as conn:
+    Get latest VO2 Max value.
-        cur = get_cursor(conn)
-        cur.execute(
-            """SELECT vo2_max FROM vitals_baseline
-               WHERE profile_id=%s AND vo2_max IS NOT NULL
-               ORDER BY date DESC LIMIT 1""",
-            (profile_id,)
-        )
-        row = cur.fetchone()
 
-        if row and row['vo2_max']:
+    Phase 0c: Refactored to use data_layer.health_metrics.get_vo2_max_data()
-            return f"{row['vo2_max']:.1f} ml/kg/min"
+    This function now only FORMATS the data for AI consumption.
+    """
+    data = get_vo2_max_data(profile_id)
+
+    if data['confidence'] == 'insufficient':
         return "nicht verfügbar"
 
+    return f"{data['vo2_max']:.1f} ml/kg/min"
+
 
 # ── Phase 0b Calculation Engine Integration ──────────────────────────────────