fix: FDDB-Zeilen im CSV-Import speichern und in Ernährung zeigen

Bezeichnung/Menge auch ohne Vorlagen-Mapping, Zuordnen-Hinweis, Tagesliste mit Lebensmitteln.

Co-authored-by: Cursor <cursoragent@cursor.com>

backend/csv_parser/executor.py

@@ -11,7 +11,31 @@ from typing import Any
 
 import logging
 
-from csv_parser.core import iter_csv_dict_rows, resolve_effective_csv_delimiter
+from csv_parser.core import iter_csv_dict_rows, normalize_header_for_signature, resolve_effective_csv_delimiter
+
+_FOOD_NAME_HEADERS = frozenset({
+    "bezeichnung", "lebensmittel", "food", "food_name", "name", "gericht",
+})
+_QTY_HEADERS = frozenset({
+    "menge", "quantity", "quantity_raw", "portion", "amount", "gramm",
+})
+
+
+def guess_nutrition_item_fields(csv_row: dict[str, Any] | None) -> tuple[str | None, str | None]:
+    """FDDB-Spalten auch ohne Vorlagen-Mapping auf food_name / menge erkennen."""
+    name = qty = None
+    for key, val in (csv_row or {}).items():
+        if val is None:
+            continue
+        text = str(val).strip().strip('"')
+        if not text:
+            continue
+        norm = normalize_header_for_signature(str(key))
+        if name is None and (norm in _FOOD_NAME_HEADERS or "bezeichnung" in norm):
+            name = text
+        if qty is None and (norm in _QTY_HEADERS or norm.startswith("menge")):
+            qty = text
+    return name, qty
 from csv_parser.import_row_processing import (
     aggregate_mapped_rows,
     resolve_import_row_processing,
@@ -181,6 +205,8 @@ def run_universal_csv_import(
         "error_details": error_details[:50],
         "new_entries": stats.get("new_entries", stats.get("inserted", 0)),
         "affected_ids": dict(affected_ids),
+        "items_written": stats.get("items_written", 0),
+        "unmapped_names": stats.get("unmapped_names", 0),
     }
     return out
 
@@ -203,6 +229,11 @@ def _import_nutrition(
     for csv_row in iter_csv_dict_rows(text, delim, has_header=has_header):
         rows_total += 1
         mapped = build_row_after_mapping(csv_row, fm, tc, module="nutrition")
+        guessed_name, guessed_qty = guess_nutrition_item_fields(csv_row)
+        if not mapped.get("food_name") and guessed_name:
+            mapped["food_name"] = guessed_name
+        if not mapped.get("quantity_raw") and guessed_qty:
+            mapped["quantity_raw"] = guessed_qty
         d = coerce_date(mapped.get("date"))
         if d is None:
             error_details.append({"row": rows_total, "error": "Datum fehlt oder ungültig"})
@@ -246,6 +277,15 @@ def _import_nutrition(
 
         policy = get_import_policy(cur, profile_id)
         ingest = replace_csv_items_for_dates(cur, profile_id, item_rows, policy=policy)
+        cur.execute(
+            """
+            SELECT COUNT(DISTINCT source_name_normalized) AS n
+            FROM nutrition_items
+            WHERE profile_id = %s AND food_id IS NULL
+            """,
+            (profile_id,),
+        )
+        unmapped_row = cur.fetchone() or {}
         return {
             "rows_total": rows_total,
             "inserted": ingest.get("new_log_days", 0),
@@ -253,6 +293,7 @@ def _import_nutrition(
             "skipped": skipped_groups,
             "new_entries": ingest.get("new_log_days", 0),
             "items_written": ingest.get("items_written", 0),
+            "unmapped_names": int(unmapped_row.get("n") or 0),
             "conflicts": ingest.get("conflicts") or [],
             "policy": ingest.get("policy"),
         }

backend/csv_parser/mapping_suggest.py

@@ -20,6 +20,8 @@ _MODULE_HEADER_ALIASES: dict[str, dict[str, frozenset[str]]] = {
         "protein_g": frozenset({"protein", "eiwei", "eiweiss"}),
         "fat_g": frozenset({"fett", "fat", "lipid"}),
         "carbs_g": frozenset({"kh", "carb", "kohlenhydr", "carbs", "sugar", "zucker"}),
+        "food_name": frozenset({"bezeichnung", "lebensmittel", "food", "gericht"}),
+        "quantity_raw": frozenset({"menge", "quantity", "portion", "gramm"}),
     },
     "weight": {
         "date": frozenset({"datum", "date", "tag", "day", "zeit"}),

backend/routers/csv_import.py

@@ -712,6 +712,8 @@ async def csv_import_execute(
             "updated": result["rows_updated"],
             "skipped": result["rows_skipped"],
             "errors": result["rows_errors"],
+            "items_written": result.get("items_written", 0),
+            "unmapped_names": result.get("unmapped_names", 0),
         },
         "error_details": result["error_details"],
     }

backend/routers/nutrition.py

@@ -227,7 +227,23 @@ def list_nutrition(limit: int=365, x_profile_id: Optional[str]=Header(default=No
             """,
             (pid, limit),
         )
-        return [r2d(r) for r in cur.fetchall()]
+        rows = [r2d(r) for r in cur.fetchall()]
+        dates = [r["date"] for r in rows if r.get("date") is not None]
+        counts = {}
+        if dates:
+            cur.execute(
+                """
+                SELECT date, COUNT(*) AS item_count
+                FROM nutrition_items
+                WHERE profile_id = %s AND date = ANY(%s)
+                GROUP BY date
+                """,
+                (pid, dates),
+            )
+            counts = {str(r["date"]): int(r["item_count"] or 0) for r in cur.fetchall()}
+        for r in rows:
+            r["item_count"] = counts.get(str(r.get("date")), 0)
+        return rows
 
 
 @router.get("/by-date/{date}")

backend/tests/test_food_mapping.py

@@ -1,3 +1,4 @@
+from csv_parser.executor import guess_nutrition_item_fields
 from data_layer.food_mapping import normalize_food_name, parse_quantity_g
 from data_layer.nutrition_items import macros_differ
 
@@ -13,6 +14,16 @@ def test_parse_quantity_g():
     assert parse_quantity_g("1 Stück") is None
 
 
+def test_guess_fddb_bezeichnung_without_template_mapping():
+    name, qty = guess_nutrition_item_fields({
+        "bezeichnung": "50 g Hähnchen",
+        "menge": "50 g",
+        "kj": "800",
+    })
+    assert name == "50 g Hähnchen"
+    assert qty == "50 g"
+
+
 def test_macros_differ_rounds():
     assert not macros_differ({"kcal": 1.04, "protein_g": 0, "fat_g": 0, "carbs_g": 0}, {"kcal": 1.0, "protein_g": 0, "fat_g": 0, "carbs_g": 0})
     assert macros_differ({"kcal": 10, "protein_g": 0, "fat_g": 0, "carbs_g": 0}, {"kcal": 11, "protein_g": 0, "fat_g": 0, "carbs_g": 0})

frontend/src/pages/NutritionPage.jsx

@@ -195,6 +195,49 @@ function EntryForm({ onSaved }) {
 }
 
 // ── Data Tab (Editable Entry List) ───────────────────────────────────────────
+function DayItems({ date }) {
+  const [items, setItems] = useState(null)
+  const [open, setOpen] = useState(false)
+  const [error, setError] = useState(null)
+
+  const toggle = async () => {
+    if (open) {
+      setOpen(false)
+      return
+    }
+    if (!items) {
+      try {
+        setItems(await nutritionApi.listNutritionItems(date))
+      } catch (e) {
+        setError(e.message)
+        return
+      }
+    }
+    setOpen(true)
+  }
+
+  return (
+    <div style={{ marginTop: 8 }}>
+      <button type="button" className="btn btn-secondary" style={{ fontSize: 12 }} onClick={toggle}>
+        {open ? 'Lebensmittel ausblenden' : 'Lebensmittel zeigen'}
+      </button>
+      {error && <p style={{ color: 'var(--danger)', fontSize: 12, margin: '6px 0 0' }}>{error}</p>}
+      {open && Array.isArray(items) && (
+        <ul style={{ margin: '8px 0 0', paddingLeft: 18, fontSize: 13, color: 'var(--text1)' }}>
+          {items.length === 0 && <li style={{ color: 'var(--text3)' }}>Keine Zeilen für diesen Tag</li>}
+          {items.map((it) => (
+            <li key={it.id}>
+              {it.source_name_raw}
+              {it.quantity_raw ? ` · ${it.quantity_raw}` : ''}
+              {it.food_name_de ? ` → ${it.food_name_de}` : ' · noch nicht zugeordnet'}
+            </li>
+          ))}
+        </ul>
+      )}
+    </div>
+  )
+}
+
 function DataTab({ entries, onUpdate }) {
   const [editId, setEditId] = useState(null)
   const [editValues, setEditValues] = useState({})
@@ -327,8 +370,14 @@ function DataTab({ entries, onUpdate }) {
                   <div style={{fontSize:10, color:'var(--text3)', marginTop:4}}>
                     Quelle: {e.source}{e.macro_origin ? ` · Makros: ${e.macro_origin}` : ''}
                     {e.mark_type ? ` · ${e.mark_type === 'fasting' ? 'Fastentag' : 'unvollständig'}` : ''}
+                    {e.item_count ? ` · ${e.item_count} Lebensmittel` : ''}
                   </div>
                 )}
+                {e.item_count > 0 ? (
+                  <DayItems date={e.date} />
+                ) : (
+                  <div style={{fontSize:12, color:'var(--text3)', marginTop:6}}>Keine einzelnen Lebensmittelzeilen</div>
+                )}
                 <div style={{marginTop:8}}>
                   <DayMarkButtons date={e.date} markType={e.mark_type} onChanged={onUpdate} />
                 </div>
@@ -849,6 +898,7 @@ export default function NutritionPage() {
   const [hasData,    setHasData]= useState(false)
   const [importHistoryKey, setImportHistoryKey] = useState(Date.now())  // BUG-004 fix
   const [nutritionUsage, setNutritionUsage] = useState(null)
+  const [unmappedCount, setUnmappedCount] = useState(0)
 
   const loadUsage = () => {
     nutritionApi.getFeatureUsage().then(features => {
@@ -860,16 +910,18 @@ export default function NutritionPage() {
   const load = async () => {
     setLoad(true)
     try {
-      const [corr, wkly, ent, prof] = await Promise.all([
+      const [corr, wkly, ent, prof, unmapped] = await Promise.all([
         nutritionApi.nutritionCorrelations(),
         nutritionApi.nutritionWeekly(16),
         nutritionApi.listNutrition(365),  // BUG-002 fix: load raw entries
         nutritionApi.getActiveProfile(),
+        nutritionApi.listUnmappedFoods().catch(() => []),
       ])
       setCorr(Array.isArray(corr)?corr:[])
       setWeekly(Array.isArray(wkly)?wkly:[])
       setEntries(Array.isArray(ent)?ent:[])  // BUG-002 fix
       setProf(prof)
+      setUnmappedCount(Array.isArray(unmapped) ? unmapped.length : 0)
       setHasData(Array.isArray(corr) && corr.some(d=>d.kcal))
     } catch(e) { console.error('load error:', e) }
     finally { setLoad(false) }
@@ -880,6 +932,14 @@ export default function NutritionPage() {
   return (
     <div className="capture-page">
       <h1 className="page-title">Ernährung</h1>
+      {unmappedCount > 0 && (
+        <div className="card" style={{ marginBottom: 12, padding: 12, fontSize: 13 }}>
+          {unmappedCount} Lebensmittel noch ohne BLS-Zuordnung.{' '}
+          <button type="button" className="btn btn-secondary" style={{ marginLeft: 8 }} onClick={() => setInputTab('map')}>
+            Jetzt zuordnen
+          </button>
+        </div>
+      )}
 
       {/* Input Method Tabs */}
       <div className="tabs section-gap" style={{marginBottom:0}}>
@@ -890,7 +950,7 @@ export default function NutritionPage() {
           📥 Import
         </button>
         <button className={'tab'+(inputTab==='map'?' active':'')} onClick={()=>setInputTab('map')}>
-          Zuordnen
+          Zuordnen{unmappedCount ? ` (${unmappedCount})` : ''}
         </button>
       </div>
 

frontend/src/pages/UniversalCsvImportPage.jsx

@@ -201,10 +201,14 @@ export default function UniversalCsvImportPage() {
       setLastImport(res)
       const st = res.stats || {}
       const modLabel = MODULE_LABEL[res.module] || res.module || ''
+      const extra = []
+      if (st.items_written) extra.push(`${st.items_written} Lebensmittelzeilen`)
+      if (st.unmapped_names) extra.push(`${st.unmapped_names} noch ohne Zuordnung — Ernährung → Zuordnen`)
       setSuccess(
         (modLabel ? `${modLabel}: ` : '') +
           `Import fertig — ${st.imported ?? 0} neu, ${st.updated ?? 0} aktualisiert, ` +
-          `${st.skipped ?? 0} übersprungen, ${st.errors ?? 0} Zeilenfehler.`,
+          `${st.skipped ?? 0} übersprungen, ${st.errors ?? 0} Zeilenfehler.` +
+          (extra.length ? ` ${extra.join(' · ')}.` : ''),
       )
     } catch (e) {
       setError(e.message || 'Import fehlgeschlagen')