feat: Phase 0c - body_metrics.py module complete

Data Layer:
- get_latest_weight_data() - most recent weight with date
- get_weight_trend_data() - already existed (PoC)
- get_body_composition_data() - already existed (PoC)
- get_circumference_summary_data() - already existed (PoC)

Placeholder Layer:
- get_latest_weight() - refactored to use data layer
- get_caliper_summary() - refactored to use get_body_composition_data
- get_weight_trend() - already refactored (PoC)
- get_latest_bf() - already refactored (PoC)
- get_circ_summary() - already refactored (PoC)

body_metrics.py now complete with all 4 functions.

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

backend/data_layer/__init__.py

@@ -45,6 +45,7 @@ __all__ = [
     'serialize_dates',
 
     # Body Metrics
+    'get_latest_weight_data',
     'get_weight_trend_data',
     'get_body_composition_data',
     'get_circumference_summary_data',

backend/data_layer/body_metrics.py

@@ -4,6 +4,7 @@ Body Metrics Data Layer
 Provides structured data for body composition and measurements.
 
 Functions:
+    - get_latest_weight_data(): Most recent weight entry
     - get_weight_trend_data(): Weight trend with slope and direction
     - get_body_composition_data(): Body fat percentage and lean mass
     - get_circumference_summary_data(): Latest circumference measurements
@@ -21,6 +22,51 @@ from db import get_db, get_cursor, r2d
 from data_layer.utils import calculate_confidence, safe_float
 
 
+def get_latest_weight_data(
+    profile_id: str
+) -> Dict:
+    """
+    Get most recent weight entry.
+
+    Args:
+        profile_id: User profile ID
+
+    Returns:
+        {
+            "weight": float,             # kg
+            "date": date,
+            "confidence": str
+        }
+
+    Migration from Phase 0b:
+        OLD: get_latest_weight() returned formatted string "85.0 kg"
+        NEW: Returns structured data {"weight": 85.0, "date": ...}
+    """
+    with get_db() as conn:
+        cur = get_cursor(conn)
+        cur.execute(
+            """SELECT weight, date FROM weight_log
+               WHERE profile_id=%s
+               ORDER BY date DESC
+               LIMIT 1""",
+            (profile_id,)
+        )
+        row = cur.fetchone()
+
+        if not row:
+            return {
+                "weight": 0.0,
+                "date": None,
+                "confidence": "insufficient"
+            }
+
+        return {
+            "weight": safe_float(row['weight']),
+            "date": row['date'],
+            "confidence": "high"
+        }
+
+
 def get_weight_trend_data(
     profile_id: str,
     days: int = 28

backend/placeholder_resolver.py

@@ -14,6 +14,7 @@ from db import get_db, get_cursor, r2d
 
 # Phase 0c: Import data layer
 from data_layer.body_metrics import (
+    get_latest_weight_data,
     get_weight_trend_data,
     get_body_composition_data,
     get_circumference_summary_data
@@ -51,15 +52,18 @@ def get_profile_data(profile_id: str) -> Dict:
 
 
 def get_latest_weight(profile_id: str) -> Optional[str]:
-    """Get latest weight entry."""
+    """
-    with get_db() as conn:
+    Get latest weight entry.
-        cur = get_cursor(conn)
+
-        cur.execute(
+    Phase 0c: Refactored to use data_layer.body_metrics.get_latest_weight_data()
-            "SELECT weight FROM weight_log WHERE profile_id=%s ORDER BY date DESC LIMIT 1",
+    This function now only FORMATS the data for AI consumption.
-            (profile_id,)
+    """
-        )
+    data = get_latest_weight_data(profile_id)
-        row = cur.fetchone()
+
-        return f"{row['weight']:.1f} kg" if row else "nicht verfügbar"
+    if data['confidence'] == 'insufficient':
+        return "nicht verfügbar"
+
+    return f"{data['weight']:.1f} kg"
 
 
 def get_weight_trend(profile_id: str, days: int = 28) -> str:
@@ -129,22 +133,19 @@ def get_nutrition_avg(profile_id: str, field: str, days: int = 30) -> str:
 
 
 def get_caliper_summary(profile_id: str) -> str:
-    """Get latest caliper measurements summary."""
+    """
-    with get_db() as conn:
+    Get latest caliper measurements summary.
-        cur = get_cursor(conn)
-        cur.execute(
-            """SELECT body_fat_pct, sf_method, date FROM caliper_log
-               WHERE profile_id=%s AND body_fat_pct IS NOT NULL
-               ORDER BY date DESC LIMIT 1""",
-            (profile_id,)
-        )
-        row = r2d(cur.fetchone()) if cur.rowcount > 0 else None
 
-        if not row:
+    Phase 0c: Refactored to use data_layer.body_metrics.get_body_composition_data()
+    This function now only FORMATS the data for AI consumption.
+    """
+    data = get_body_composition_data(profile_id)
+
+    if data['confidence'] == 'insufficient':
         return "keine Caliper-Messungen"
 
-        method = row.get('sf_method', 'unbekannt')
+    method = data.get('method', 'unbekannt')
-        return f"{row['body_fat_pct']:.1f}% ({method} am {row['date']})"
+    return f"{data['body_fat_pct']:.1f}% ({method} am {data['date']})"
 
 
 def get_circ_summary(profile_id: str) -> str: