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Author SHA1 Message Date
4b1be3019d fix: FDDB-Zeilen im CSV-Import speichern und in Ernährung zeigen
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Bezeichnung/Menge auch ohne Vorlagen-Mapping, Zuordnen-Hinweis, Tagesliste mit Lebensmitteln.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-09-12 15:11:37 +02:00
a07a668de2 fix: BLS-Datenimport als Hintergrundjob gegen HTTP 504
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Prüfung und Apply laufen serverseitig, die UI pollt nur noch den Status.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-09-12 14:57:13 +02:00
8e964509d7 fix: BLS-Import-UI und Timeout beim Daten-Apply
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Datei-Button volle Breite, Import als Aktionsbutton, Batch-Upsert statt Einzel-INSERTs.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-09-12 14:49:47 +02:00
7ccae33844 fix: BLS-Import prüft bei Dateiauswahl, Import nur per Schalter
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Eine Datei pro Typ, sofortiger Dry-Run, Schalter startet den Write.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-09-12 14:43:59 +02:00
9bb89231d0 fix: BLS-Import mit einer Datei plus Prüfen/Anwenden
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Zwei unbeschriftete File-Inputs pro Dateityp wirkten wie doppelte Auswahl.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-09-12 14:41:42 +02:00
c90dabc032 fix: doppelte BLS-Admin-Imports in App.jsx entfernen
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Vite-Build auf Dev war wegen redeklarierter Seitenimporte fehlgeschlagen.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-09-12 14:37:54 +02:00
919c77fcf8 feat: BLS-Stammdaten, FDDB-Mapping und Item-Tagebuch (#106)
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Katalog, lernendes Mapping ohne KI, optionale Items und Import-Policy.
Playwright-Smoke und Issue-Audit um Ernährung/Zuordnen/API ergänzt.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-09-12 14:35:57 +02:00
72d101415f fix: run activity import enforcement tests without pytest-asyncio
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CI container only installs pytest; use asyncio.run() for async route handlers.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-07-25 17:46:30 +02:00
ae7d0ac1d9 test: stabilize Playwright smoke and issue-audit against dev
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Fix nav selectors (Erfassen), shared auth via global-setup to avoid login rate limits, and desktop sidebar viewport handling.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-07-25 16:37:36 +02:00
79ec249bc3 feat: feature enforcement imports (#37/#38) and Universal CSV validation (#71)
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Activity and nutrition legacy CSV imports enforce tier limits with UsageBadge UI; Universal CSV gets mapping validation on copy/import, format-check parity, and structured error_details.

version: 0.9u
module: activity 1.2.1, nutrition 1.0.3, csv_import 0.4.0
Co-authored-by: Cursor <cursoragent@cursor.com>
2026-07-24 16:59:12 +02:00
70 changed files with 3953 additions and 181 deletions

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# Gitea Issues Landkarte (Auswertung)
**Quelle:** Gitea `Lars/mitai-jinkendo`, Stand **2026-04-11** (Abfrage `state=all`, ergänzt: #71, #76).
**Quelle:** Gitea `Lars/mitai-jinkendo`, Stand **2026-04-11** (Abfrage `state=all`, ergänzt: #71, #75, #76, #106, 2026-09-12).
**URL:** http://192.168.2.144:3000/Lars/mitai-jinkendo/issues
Dieses Dokument ist ein **Orientierungs-Index** für Agenten und Entwickler. Verbindliches Tracking bleibt **in Gitea**; hier: Kategorien, Dubletten-Hinweise, grobe Prioritätseinschätzung.
@ -82,6 +82,14 @@ Dieses Dokument ist ein **Orientierungs-Index** für Agenten und Entwickler. Ver
|---|--------|
| 37 | Feature-Enforcement für Activity CSV-Import |
| 38 | Feature-Enforcement für Nutrition CSV-Import UI |
| 71 | Universal CSV Import: Dry-Run, Mapping-Validierung, Fehler-Hints |
### Ernährung / BLS
| # | Titel |
|---|--------|
| 75 | Ernährung: Zucker/Ballaststoffe, Lebensmittelqualität, Timing (Folge nach #106) |
| 106 | BLS-Stammdaten, FDDB-Mapping und Item-Tagebuch |
### Qualität / Sonstiges

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| Dashboard-Widgets | `technical/DASHBOARD_WIDGETS_AGENT_GUIDE.md` | Widget-Katalog + Registrierung (siehe Guide) |
| Training Profiler / Resolver | `technical/TRAINING_PROFILE_RESOLVER_LAYER1.md`, `functional/TRAINING_TYPE_PROFILES.md` | Resolver-Module wie im Guide genannt |
| Universal CSV Import | `technical/UNIVERSAL_CSV_IMPORT_AGENT_GUIDE.md` | `backend/csv_parser/`, `routers/csv_import.py`, `routers/admin_csv_templates.py` |
| BLS / Lebensmittel | `functional/BLS_FOOD_REFERENCE.md`, `technical/BLS_FOOD_REFERENCE.md` | Migration 062, `backend/bls/`, `data_layer/food_mapping.py` |
| **Designprinzipien (Produktfamilie)** | **`jinkendo-foundation/design-principles/README.md`** | Querschnittsmuster; Foundation für Schwester-Apps |
| Aktivität Produktionsreife | `technical/ACTIVITY_PRODUCTION_ARCHITECTURE_AND_PHASES.md` (+ EAV-Guide) | `backend/data_layer/activity_session_metrics.py`, `activity_metrics.py`, CSV-Orchestrierung |
| Mitgliedschaft / Features | `technical/MEMBERSHIP_SYSTEM.md`, `architecture/FEATURE_ENFORCEMENT.md` | `backend/auth.py`, Feature-Logging, Router mit Enforcement |

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# BLS-Lebensmittelreferenz und FDDB-Mapping
**Stand:** 2026-09-12 · **Status:** Phase 1 (Umsetzung)
## WAS
Optionale Grundlage für verlässliche Nährwerte: offizieller Bundeslebensmittelschlüssel (BLS) 4.0 plus manuelle Katalogerweiterung, lernendes Mapping von FDDB-Bezeichnern, persistierte Tagebuchzeilen. Reine Tagesmakros bleiben First Class.
## Fachliche Regeln
- BLS-Code (`bls_code`, Stoff-`attr_key`) bleibt die stabile Identität bei Reimports.
- BLS 4.0 (~7140 Lebensmittel) ist frei nutzbar (MRI / blsdb.de); Dateien nicht im Git.
- Mapping ohne KI: Normalisierung + exakter Lookup (User vor Global) + Bestätigung neuer Namen.
- Gelernte Zuordnungen bleiben dauerhaft, sind aber änder- und löschbar.
- Ungemappte / Fertiggerichte: FDDB-Makros, keine erfundenen Mikros.
- Fasten und „unvollständig“ sind explizite Marken, kein Auto-Schluss aus fehlendem Import.
- Import-Policy (Profil): nachfragen / Katalog überschreiben / FDDB überschreiben / Makros behalten.
## Später
Platzhalter (Registry) für Mikros, Esszeitpunkte (`logged_at`), Fasten; Bezug Gitea #106 (Grundlage) und #75 (Folge).

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**Erledigt:** Phase A — [`ACTIVITY_SCALAR_KANON_TABLE.md`](./ACTIVITY_SCALAR_KANON_TABLE.md).
**Aktuell:** Phase B fortsetzen (weitere Consumer prüfen: Export, Import-Vorschau, ggf. zukünftige Chart-Metriken aus EAV), dann **Phase C** (Schreibpfad), dann **Phase D** (Composite-MVP).
**Aktuell:** Phase B abgeschlossen (Consumer-Audit 2026-04-16). **Phase C** Schreibpfad entschlackt (Sync abgestellt, Orchestrator als SSoT; Review 2026-04-16 + Regression `test_activity_insert_sql.py`). Nächster Schritt: **Phase D** (Composite-MVP).
---

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# BLS Food Reference technische Spec
**Stand:** 2026-09-12 · Migration **062**
## Tabellen
- `food_attributes` — dynamischer Stoff-/Merkmalskatalog (`attr_key`, `data_type`, `origin`)
- `food_catalog` — Lebensmittel (`bls_code` UNIQUE bei official_bls; manuell ohne BLS-Code)
- `food_attribute_values` — typisiertes EAV
- `food_name_mappings` — FDDB-Name → `food_id` (User / global)
- `nutrition_items` — Tagebuchzeilen inkl. `logged_at`
- `nutrition_daily_nutrients` — Tages-Rollup numerischer Attribute
- `nutrition_day_marks``fasting` | `incomplete`
## Layer 1
- `data_layer/food_mapping.py` — Normalisierung, Lookup, Learn, Apply, Delete
- `data_layer/nutrition_items.py` — Ingest, drei Makro-Summen, Policy, `resolve_*_attributes`
## Import
BLS: Admin-Upload Components + Daten-XLSX (`backend/bls/parser.py`). Upsert über `bls_code` / `attr_key`, nie Delete+Insert offizieller Zeilen.
FDDB: Items persistieren; `nutrition_log` nur bei leerem Tag oder laut Policy / Bestätigung.
## Router
- `/api/bls/*` — Suche, eigene Foods, eigene Mappings
- `/api/admin/bls/*` — Import, Katalog, Attribute
- `/api/admin/food-mappings` — Admin-CRUD
- `/api/nutrition/*` — Items, Unmapped, Bulk-Map, Marken, Konflikt-Resolve

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---
## 4. Bekannte Einschränkungen (Follow-up in Gitea)
## 4. Validierung & Dry-Run (Stand 2026-07-23, Gitea #71)
- Admin **„Format prüfen“** kann `import_row_processing` derzeit weglassen; volle Parität mit dem gespeicherten Template erst beim Speichern / echten Import.
- Nutzer-Mappings (Copy aus Systemvorlage) laufen nicht automatisch durch **`validate_csv_template`** Tracking: **Gitea #71** (http://192.168.2.144:3000/Lars/mitai-jinkendo/issues/71).
- Admin **„Format prüfen“** sendet dieselbe `import_row_processing`-Spec wie Speichern (`AdminCsvTemplateEditorPage` → `POST /api/admin/csv-templates/validate`).
- **Profil-Mappings:** `POST /api/csv/mappings/{id}/copy` und `POST /api/csv/import` prüfen vor dem Schreiben mit **`validate_csv_template`** (HTTP 422 bei Fehlern).
- **Diagnose:** `GET /api/csv/mappings/{id}/validate` — Strukturprüfung ohne Import.
- **Nutzer-UI:** `UniversalCsvImportPage` zeigt `error_details` mit Zeile, `code` und `hint` (`CsvImportErrorDetails`).
---

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**Automatischer Audit (Code + Playwright, 2026-07-23)**
Ziele-System ist im Repo umgesetzt:
- Backend: `backend/routers/goals.py`, Focus Areas, Goal Types, Progress
- Frontend: `frontend/src/pages/GoalsPage.jsx`, Nav `/goals` in `config/appNav.js`
- Spec: `docs/issues/issue-50-phase-0a-goal-system.md`
Playwright auf dev.mitai.jinkendo.de: `/goals` rendert ohne Fehler.
Verbleibende KI-Goal-Erweiterungen ggf. als neues Issue.

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**Automatischer Audit (Code, 2026-07-23)**
Deprecated Tabelle `subscriptions` ist aus dem aktiven Schema entfernt:
- Kein Treffer in `backend/schema.sql`, `backend/migrations/`, Backend-Python
- Membership nutzt `access_grants`, `tier_limits`, etc. (Migration v9c)
Doku-Hinweis deprecated: `.claude/docs/technical/DATABASE.md`
Optional Prod-Check: `\dt subscriptions` — sollte leer/nicht vorhanden sein.

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**Automatischer Audit (Code, 2026-07-23)**
Bug behoben: JSONB-Insert für `abilities`/`profile` nutzt `psycopg2.extras.Json()`.
- Fix-Commit: `2977050` — wrap abilities dict with Json() for JSONB insert
- Aktuell: `backend/routers/admin_training_types.py` (`create_training_type`, Zeilen 111112)
Admin-UI: `frontend/src/pages/AdminTrainingTypesPage.jsx`

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**Umsetzung 2026-07-23 (nach Architektur-Abgleich)**
## Architektur-Check vor Implementierung
- **Phase C (Schreibpfad):** laut `ACTIVITY_PRODUCTION_ARCHITECTURE_AND_PHASES.md` bereits erledigt (Sync abgestellt, Orchestrator als SSoT, keine Aufrufer von `sync_column_backed_session_metrics`). Keine Doppel-Implementierung.
- **Feature-ID:** Issue-Vorgabe `activity_entries` (nicht separates `activity_import`) — konsistent mit `create_activity` und Universal-CSV-Modul-Check in `csv_import.py`.
- **Legacy-Endpoint bleibt:** Frontend nutzt weiterhin `POST /api/activity/import-csv` (`ActivityPage` Apple-Health-Panel); Universal-Pfad ist parallel (ARCH §8.2).
## Änderungen
**Backend** (`routers/activity.py`):
- `check_feature_access(pid, "activity_entries")` vor Legacy-Import
- HTTP 403 bei Limit (wie `nutrition/import-csv`)
- `increment_feature_usage` pro neu eingefügter Zeile (`inserted`)
**Frontend** (`ActivityPage.jsx` ImportPanel):
- `UsageBadge` am Import-Titel
- Drop-Zone deaktiviert bei Limit
- Usage-Reload nach Import
**Tests:** `tests/test_activity_import_feature_enforcement.py` (403 + Increment)
Regression INSERT-SQL: `tests/test_activity_insert_sql.py` (grün)

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**Umsetzung 2026-07-23 (UI-Teil; Backend war bereits erledigt)**
## Ist-Zustand vorher
- Backend: `POST /api/nutrition/import-csv` mit `check_feature_access('nutrition_entries')` und HTTP 403 — **bereits implementiert**
- Frontend: FDDB-Import ohne Usage-Anzeige, Drop-Zone blieb bei Limit klickbar
## Änderungen
**Frontend** (`NutritionPage.jsx`, ImportPanel):
- `getFeatureUsage()``nutrition_entries`
- `UsageBadge` am Import-Titel
- Drop-Zone und Paste-Import deaktiviert bei Limit
- Usage-Reload nach erfolgreichem Import
Analog zu Activity #37 (geschlossen 2026-07-23).
**Playwright:** `tests/issue-audit.spec.js` — Badge am FDDB-Panel
## Hinweis
Universal-CSV (`/api/csv-import/import`) prüft zusätzlich `data_import` — Legacy FDDB-Pfad folgt dem Nutrition-Muster (nur `nutrition_entries`), konsistent mit Architektur §8.2.

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**Automatischer Audit (Code + Playwright, 2026-07-23)**
Logout-Button im Mobile-Header neben Avatar implementiert:
- `frontend/src/App.jsx` — Button mit `title="Abmelden"`, Icon `LogOut`
- Zusätzlich Desktop: `frontend/src/components/DesktopSidebar.jsx`
Playwright auf dev.mitai.jinkendo.de: Button sichtbar und klickbar.

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**Duplikat — geschlossen im Rahmen Issue-Audit 2026-07-23**
Inhalt identisch mit **#42** (Enhanced Debug/Prompt Analysis UI).
Teilumsetzung existiert bereits (`Analysis.jsx` Experten-Modus, `WorkflowDebugPanel`). Weiterverfolgung unter #42.

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**Duplikat — geschlossen im Rahmen Issue-Audit 2026-07-23**
Inhalt identisch mit **#55** (Placeholder Registry: UNRESOLVED & TO_VERIFY Metadaten).
Bitte weiterverfolgen unter #55.

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**Duplikat — geschlossen im Rahmen Issue-Audit 2026-07-23**
Inhalt identisch mit **#56** (Body Cluster — Restarbeiten & Metadaten-Verifizierung).
Bitte weiterverfolgen unter #56.

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**Duplikat — geschlossen im Rahmen Issue-Audit 2026-07-23**
Inhalt identisch mit **#56** (Body Cluster — Restarbeiten & Metadaten-Verifizierung).
Bitte weiterverfolgen unter #56.

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**Automatischer Audit (Code + Playwright, 2026-07-23)**
Nutzer-konfigurierbares Dashboard umgesetzt:
- Migration `039_dashboard_layout.sql``profiles.dashboard_layout`
- API: `backend/routers/app_dashboard.py` — GET/PUT/reset `/api/app/dashboard-layout`
- Frontend: `DashboardConfigurePage.jsx`, Widget-Registry `registerDashboardWidgets.js`
- Tests: `test_dashboard_layout_schema.py`, `test_widget_catalog.py`
Playwright: `/settings/dashboard-layout` erreichbar, Widget/Layout-UI sichtbar.

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**Automatischer Audit (Code, 2026-07-23)**
Feature-Gate-Zuordnung aus Admin/DB implementiert:
- Migration `041_widget_feature_requirements.sql`
- Logik: `backend/widget_feature_requirements_db.py`, `dashboard_widget_entitlements.py`
- Admin-UI: `AdminWidgetFeatureAssignmentsPage.jsx`, Route `/admin/widget-features`
- Changelog: `backend/version.py` (Admin Widgets × Features)
Hardcodierter Katalog wird durch DB-Overrides ergänzt (Hybrid-Modell).

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**Implementierung abgeschlossen (2026-07-24)**
### 1. Admin „Format prüfen“ inkl. `import_row_processing`
- `AdminCsvTemplateEditorPage`: `resolveEditorImportRowProcessing()` — dieselbe Spec wie beim Speichern
- Dry-Run/Format-Check nutzt konsistente Vorlage inkl. Aggregation (`group_by` / `aggregates`)
### 2. Profil-Mappings validieren
- `csv_import.py`: `_validate_mapping_config` / `_ensure_mapping_valid` bei **Copy** und **Import**
- Neuer Endpoint: `GET /api/csv/mappings/{id}/validate`
- `api.js`: `validateCsvMapping()`; `formatFastApiDetail` für verschachtelte Validierungsfehler
### 3. Nutzer-UI: strukturierte Fehler
- Neue Komponente `CsvImportErrorDetails.jsx` (Zeile, code, hint)
- `UniversalCsvImportPage` zeigt `error_details` statt JSON-Dump
### Tests & Doku
- `backend/tests/test_csv_mapping_validation.py` — pytest grün
- Agent-Guide: `.claude/docs/technical/UNIVERSAL_CSV_IMPORT_AGENT_GUIDE.md` §4 aktualisiert
**Betroffene Dateien:** `backend/routers/csv_import.py`, `frontend/src/pages/AdminCsvTemplateEditorPage.jsx`, `frontend/src/pages/UniversalCsvImportPage.jsx`, `frontend/src/components/CsvImportErrorDetails.jsx`, `frontend/src/utils/api.js`

3
.gitignore vendored
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# Temp
tmp/
*.tmp
test-results/
screenshots/
tests/.auth/
# Claude: nur ausgewählte Bereiche versionieren (siehe .claude/rules/DOCUMENTATION.md)
.claude/**

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@ -117,6 +117,14 @@ frontend/src/
- **`main.py`:** `import placeholder_registrations` beim Start, damit die Registry (**114 Keys**, deckungsgleich `PLACEHOLDER_MAP`) und `get_placeholder_catalog()` ohne vorherigen Export-Request konsistent sind.
- **`placeholder_resolver.py`:** `{{top_goal_progress_pct}}` nutzt `_safe_int` statt `_safe_str` (Verdrahtung zu `scores.get_top_priority_goal` korrigiert).
### Updates (12.09.2026 - BLS-Stammdaten, FDDB-Mapping, Item-Tagebuch)
- **Migration 062:** `food_catalog` (BLS-Code bleibt Identität), dynamische `food_attributes` + EAV, `food_name_mappings`, `nutrition_items`, `nutrition_daily_nutrients`, `nutrition_day_marks`, Import-Policy am Profil.
- **Admin:** Gruppe Ernährung — BLS-Import, Katalog, Attribute, Mappings.
- **Nutzer:** Einzelerfassung unverändert; Tab Zuordnen; Fasten/Lücke; Import-Abgleich.
- **Gitea #106:** BLS-Stammdaten, FDDB-Mapping, Item-Tagebuch — http://192.168.2.144:3000/Lars/mitai-jinkendo/issues/106
- **Doku:** `.claude/docs/functional/BLS_FOOD_REFERENCE.md`, `.claude/docs/technical/BLS_FOOD_REFERENCE.md`, `docs/issues/issue-bls-food-mapping.md`. Folge #75.
### Updates (11.04.2026 - Gitea #75, nutrition_score Registry)
- **Gitea #75** (offen): Zucker/Ballaststoffe/Lebensmittelqualität, automatisches Lebensmittelprofil, später Mahlzeiten-Timing/Abgleich mit Training — http://192.168.2.144:3000/Lars/mitai-jinkendo/issues/75

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backend/bls/__init__.py Normal file
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"""BLS 4.0 ingest (official MRI XLSX)."""

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"""Apply parsed BLS 4.0 data: upsert attributes and foods, never delete official rows."""
from __future__ import annotations
from typing import Any
from psycopg2.extras import execute_values
VALUE_PAGE = 2000
FOOD_PAGE = 500
def should_persist_value(val: dict[str, Any]) -> bool:
if val.get("is_trace"):
return True
return val.get("value_num") is not None
def upsert_attributes(cur, attributes: list[dict[str, Any]]) -> dict[str, int]:
inserted = updated = 0
for a in attributes:
cur.execute(
"""
INSERT INTO food_attributes
(attr_key, name_de, name_en, unit, category, data_type, origin, sort_order, updated_at)
VALUES (%s, %s, %s, %s, %s, %s, 'official_bls', %s, NOW())
ON CONFLICT (attr_key) DO UPDATE SET
name_de = EXCLUDED.name_de,
name_en = COALESCE(EXCLUDED.name_en, food_attributes.name_en),
unit = COALESCE(EXCLUDED.unit, food_attributes.unit),
category = COALESCE(EXCLUDED.category, food_attributes.category),
sort_order = EXCLUDED.sort_order,
updated_at = NOW()
WHERE food_attributes.origin = 'official_bls'
RETURNING (xmax = 0) AS inserted
""",
(
a["attr_key"], a["name_de"], a.get("name_en"), a.get("unit"),
a.get("category"), a.get("data_type") or "num_per_100g",
a.get("sort_order") or 0,
),
)
row = cur.fetchone()
if row and row.get("inserted"):
inserted += 1
else:
updated += 1
return {"inserted": inserted, "updated": updated, "total": len(attributes)}
def upsert_foods(cur, foods: list[dict[str, Any]], bls_version: str = "4.0") -> dict[str, int]:
cur.execute("SELECT attr_key, id FROM food_attributes")
attr_ids = {r["attr_key"]: r["id"] for r in cur.fetchall()}
codes = [f["bls_code"] for f in foods if f.get("bls_code")]
existing: set[str] = set()
if codes:
cur.execute("SELECT bls_code FROM food_catalog WHERE bls_code = ANY(%s)", (codes,))
existing = {r["bls_code"] for r in cur.fetchall()}
inserted = sum(1 for c in codes if c not in existing)
updated = len(codes) - inserted
food_rows = [
(
f["bls_code"], f["name_de"], f.get("name_en"), f.get("food_group"),
"official_bls", bls_version, "bls_4.0",
)
for f in foods if f.get("bls_code")
]
if food_rows:
execute_values(
cur,
"""
INSERT INTO food_catalog
(bls_code, name_de, name_en, food_group, catalog_kind, bls_version, source)
VALUES %s
ON CONFLICT (bls_code) DO UPDATE SET
name_de = EXCLUDED.name_de,
name_en = EXCLUDED.name_en,
food_group = EXCLUDED.food_group,
bls_version = EXCLUDED.bls_version,
catalog_kind = 'official_bls',
source = 'bls_4.0',
is_active = true,
updated_at = NOW()
WHERE food_catalog.catalog_kind = 'official_bls'
""",
food_rows,
page_size=FOOD_PAGE,
)
food_ids: dict[str, Any] = {}
if codes:
cur.execute("SELECT bls_code, id FROM food_catalog WHERE bls_code = ANY(%s)", (codes,))
food_ids = {r["bls_code"]: r["id"] for r in cur.fetchall()}
value_rows = []
for f in foods:
food_id = food_ids.get(f.get("bls_code"))
if not food_id:
continue
for val in f.get("values") or []:
if not should_persist_value(val):
continue
aid = attr_ids.get(val["attr_key"])
if not aid:
continue
value_rows.append((
food_id,
aid,
None if val.get("is_trace") else val.get("value_num"),
bool(val.get("is_trace")),
val.get("origin_code"),
val.get("reference_text"),
))
if value_rows:
execute_values(
cur,
"""
INSERT INTO food_attribute_values
(food_id, attribute_id, value_num, is_trace, origin_code, reference_text, updated_at)
VALUES %s
ON CONFLICT (food_id, attribute_id) DO UPDATE SET
value_num = EXCLUDED.value_num,
is_trace = EXCLUDED.is_trace,
origin_code = EXCLUDED.origin_code,
reference_text = EXCLUDED.reference_text,
updated_at = NOW()
""",
value_rows,
template="(%s, %s, %s, %s, %s, %s, NOW())",
page_size=VALUE_PAGE,
)
return {
"inserted": inserted,
"updated": updated,
"foods_inserted": inserted,
"foods_updated": updated,
"values_written": len(value_rows),
"foods_total": len(foods),
}

171
backend/bls/jobs.py Normal file
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@ -0,0 +1,171 @@
"""In-memory BLS import jobs so HTTP requests stay short (avoid proxy 504)."""
from __future__ import annotations
import threading
import time
import uuid
from typing import Any
from bls.import_service import upsert_attributes, upsert_foods
from bls.parser import parse_components_xlsx, parse_foods_xlsx
from db import get_cursor, get_db
FOOD_CHUNK = 300
JOB_TTL_S = 2 * 60 * 60
MAX_JOBS = 12
_lock = threading.Lock()
_jobs: dict[str, dict[str, Any]] = {}
def _public(job: dict[str, Any]) -> dict[str, Any]:
return {
"id": job["id"],
"kind": job["kind"],
"status": job["status"],
"check": job.get("check"),
"progress": job.get("progress"),
"result": job.get("result"),
"error": job.get("error"),
}
def _purge_locked(now: float) -> None:
stale = [jid for jid, job in _jobs.items() if now - job["created_at"] > JOB_TTL_S]
for jid in stale:
_jobs.pop(jid, None)
if len(_jobs) <= MAX_JOBS:
return
oldest = sorted(_jobs.values(), key=lambda j: j["created_at"])
for job in oldest[: max(0, len(_jobs) - MAX_JOBS)]:
if job["status"] in ("checking", "applying"):
continue
_jobs.pop(job["id"], None)
def get_job(job_id: str) -> dict[str, Any] | None:
with _lock:
job = _jobs.get(job_id)
return _public(job) if job else None
def create_and_check(kind: str, raw: bytes) -> str:
if kind not in ("components", "foods"):
raise ValueError("kind muss components oder foods sein")
job_id = str(uuid.uuid4())
now = time.time()
with _lock:
_purge_locked(now)
_jobs[job_id] = {
"id": job_id,
"kind": kind,
"status": "checking",
"created_at": now,
"raw": raw,
"parsed": None,
"check": None,
"progress": None,
"result": None,
"error": None,
}
threading.Thread(target=_run_check, args=(job_id,), daemon=True).start()
return job_id
def start_apply(job_id: str) -> None:
with _lock:
job = _jobs.get(job_id)
if job is None:
raise KeyError(job_id)
if job["status"] != "checked":
raise ValueError("Zuerst die Prüfung abwarten")
if job.get("parsed") is None:
raise ValueError("Geparste Datei nicht mehr vorhanden — Datei neu wählen")
job["status"] = "applying"
job["error"] = None
job["progress"] = {"current": 0, "total": 0}
threading.Thread(target=_run_apply, args=(job_id,), daemon=True).start()
def _update(job_id: str, **fields: Any) -> None:
with _lock:
job = _jobs.get(job_id)
if not job:
return
job.update(fields)
def _run_check(job_id: str) -> None:
with _lock:
job = _jobs.get(job_id)
if not job:
return
kind = job["kind"]
raw = job["raw"]
try:
if kind == "components":
attrs = parse_components_xlsx(raw)
_update(
job_id,
parsed=attrs,
raw=None,
check={"attributes": len(attrs)},
status="checked",
)
return
parsed = parse_foods_xlsx(raw)
_update(
job_id,
parsed=parsed,
raw=None,
check={
"foods": len(parsed["foods"]),
"attribute_columns": len(parsed["attribute_headers"]),
},
status="checked",
)
except Exception as e:
_update(job_id, status="error", error=str(e), raw=None, parsed=None)
def _run_apply(job_id: str) -> None:
with _lock:
job = _jobs.get(job_id)
if not job:
return
kind = job["kind"]
parsed = job["parsed"]
try:
if kind == "components":
with get_db() as conn:
stats = upsert_attributes(get_cursor(conn), parsed)
_update(job_id, status="done", result=stats, parsed=None, progress={"current": stats.get("total", 0), "total": stats.get("total", 0)})
return
foods = parsed["foods"]
total = len(foods)
inserted = updated = values_written = 0
_update(job_id, progress={"current": 0, "total": total})
for i in range(0, total, FOOD_CHUNK):
chunk = foods[i : i + FOOD_CHUNK]
with get_db() as conn:
stats = upsert_foods(get_cursor(conn), chunk)
inserted += stats.get("inserted", 0)
updated += stats.get("updated", 0)
values_written += stats.get("values_written", 0)
_update(job_id, progress={"current": min(i + FOOD_CHUNK, total), "total": total})
_update(
job_id,
status="done",
parsed=None,
result={
"inserted": inserted,
"updated": updated,
"foods_inserted": inserted,
"foods_updated": updated,
"values_written": values_written,
"foods_total": total,
},
)
except Exception as e:
_update(job_id, status="error", error=str(e))

158
backend/bls/parser.py Normal file
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@ -0,0 +1,158 @@
"""Parse official BLS 4.0 XLSX files without a hardcoded nutrient code list."""
from __future__ import annotations
import re
from io import BytesIO
from typing import Any
from openpyxl import load_workbook
# Header like: "ENERCJ Energie (Kilojoule) [kJ/100g]"
ATTR_HEADER_RE = re.compile(
r"^([A-Z][A-Z0-9:]{1,20})\s+(.+?)(?:\s*\[([^\]]+)\])?\s*$"
)
def _cell(v: Any) -> str:
if v is None:
return ""
return str(v).strip()
def parse_components_xlsx(data: bytes) -> list[dict[str, Any]]:
wb = load_workbook(filename=BytesIO(data), read_only=True, data_only=True)
ws = wb.active
rows = ws.iter_rows(values_only=True)
header = [_cell(c) for c in next(rows)]
idx = {h.lower(): i for i, h in enumerate(header) if h}
def col(*names: str) -> int | None:
for n in names:
if n.lower() in idx:
return idx[n.lower()]
for key, i in idx.items():
for n in names:
if n.lower() in key:
return i
return None
i_code = col("code", "schlüssel", "schluessel", "attr_key", "komponente")
i_de = col("name_de", "deutsch", "bezeichnung_de", "name de")
i_en = col("name_en", "english", "bezeichnung_en", "name en")
i_unit = col("unit", "einheit")
i_cat = col("category", "kategorie", "gruppe")
if i_code is None:
i_code = 0
if i_de is None:
i_de = 1 if len(header) > 1 else 0
out = []
sort_order = 0
for raw in rows:
if not raw:
continue
code = _cell(raw[i_code] if i_code < len(raw) else "")
if not code or code.lower() in ("code", "schlüssel", "schluessel"):
continue
name_de = _cell(raw[i_de] if i_de is not None and i_de < len(raw) else "") or code
name_en = _cell(raw[i_en] if i_en is not None and i_en < len(raw) else "") or None
unit = _cell(raw[i_unit] if i_unit is not None and i_unit < len(raw) else "") or None
category = _cell(raw[i_cat] if i_cat is not None and i_cat < len(raw) else "") or None
sort_order += 1
out.append({
"attr_key": code,
"name_de": name_de,
"name_en": name_en,
"unit": unit,
"category": category,
"data_type": "num_per_100g",
"origin": "official_bls",
"sort_order": sort_order,
})
wb.close()
return out
def _parse_value_header(title: str) -> tuple[str | None, str, str | None]:
t = title.strip()
m = ATTR_HEADER_RE.match(t)
if m:
return m.group(1), m.group(2).strip(), m.group(3)
# Fallback: first token
parts = t.split()
if parts and re.match(r"^[A-Z][A-Z0-9:]{1,20}$", parts[0]):
return parts[0], " ".join(parts[1:]) or parts[0], None
return None, t, None
def parse_foods_xlsx(data: bytes) -> dict[str, Any]:
wb = load_workbook(filename=BytesIO(data), read_only=True, data_only=True)
ws = wb.active
rows = ws.iter_rows(values_only=True)
header = [_cell(c) for c in next(rows)]
if len(header) < 3:
wb.close()
raise ValueError("BLS-Datendatei: erwartet mindestens BLS-Code, Name DE, Name EN")
triples: list[dict[str, Any]] = []
i = 3
while i < len(header):
code, name_de, unit = _parse_value_header(header[i])
origin_i = i + 1 if i + 1 < len(header) else None
ref_i = i + 2 if i + 2 < len(header) else None
triples.append({
"attr_key": code or f"COL{i}",
"name_de": name_de,
"unit": unit,
"value_col": i,
"origin_col": origin_i,
"ref_col": ref_i,
})
i += 3 if (origin_i is not None and ref_i is not None) else 1
foods = []
for raw in rows:
if not raw:
continue
code = _cell(raw[0] if len(raw) else "")
if not code:
continue
name_de = _cell(raw[1] if len(raw) > 1 else "") or code
name_en = _cell(raw[2] if len(raw) > 2 else "") or None
values = []
for t in triples:
vc = t["value_col"]
raw_v = raw[vc] if vc < len(raw) else None
is_trace = False
num = None
if raw_v is None or raw_v == "" or raw_v == "-":
num = None
elif str(raw_v).strip().upper() in ("TR", "TRACE", "SPUREN"):
is_trace = True
else:
try:
num = float(str(raw_v).replace(",", "."))
except (TypeError, ValueError):
num = None
origin = ""
if t["origin_col"] is not None and t["origin_col"] < len(raw):
origin = _cell(raw[t["origin_col"]])
ref = ""
if t["ref_col"] is not None and t["ref_col"] < len(raw):
ref = _cell(raw[t["ref_col"]])
values.append({
"attr_key": t["attr_key"],
"value_num": num,
"is_trace": is_trace,
"origin_code": origin or None,
"reference_text": ref or None,
})
foods.append({
"bls_code": code,
"name_de": name_de,
"name_en": name_en,
"food_group": code[0] if code else None,
"values": values,
})
wb.close()
return {"attribute_headers": triples, "foods": foods}

View File

@ -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"})
@ -223,6 +254,50 @@ def _import_nutrition(
skipped_groups = sum(n.get("rows_in_group", 0) for n in (agg_notes or []) if n.get("error") == "mehrere_zeilen_pro_schluessel")
item_rows = []
for mapped in mapped_rows:
name = mapped.get("food_name")
if not name:
continue
d_item = coerce_date(mapped.get("date"))
if d_item is None:
continue
item_rows.append({
"date": d_item.isoformat(),
"logged_at": mapped.get("logged_at") or mapped.get("date"),
"food_name": str(name).strip(),
"quantity_raw": mapped.get("quantity_raw"),
"kcal": mapped.get("kcal"),
"protein_g": mapped.get("protein_g"),
"fat_g": mapped.get("fat_g"),
"carbs_g": mapped.get("carbs_g"),
})
if item_rows:
from data_layer.nutrition_items import get_import_policy, replace_csv_items_for_dates
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),
"updated": max(0, ingest.get("days_written", 0) - ingest.get("new_log_days", 0)),
"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"),
}
inserted = 0
updated = 0
new_entries = 0

View File

@ -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"}),

View File

@ -20,6 +20,8 @@ MODULE_DEFINITIONS: Dict[str, Dict[str, Any]] = {
"protein_g": {"type": "float", "required": False, "min": 0, "unit": "g"},
"fat_g": {"type": "float", "required": False, "min": 0, "unit": "g"},
"carbs_g": {"type": "float", "required": False, "min": 0, "unit": "g"},
"food_name": {"type": "string", "required": False, "label_de": "Lebensmittel"},
"quantity_raw": {"type": "string", "required": False, "label_de": "Menge"},
},
"duplicate_key": ["profile_id", "date"],
"duplicate_strategy": "update",

View File

@ -0,0 +1,194 @@
"""FDDB → food_catalog mapping: normalize, lookup (user then global), learn, apply."""
from __future__ import annotations
import re
import unicodedata
from typing import Any
LEADING_QTY_RE = re.compile(
r"^\s*\d+(?:[.,]\d+)?\s*(?:g|kg|ml|l|stück|stk|st\.?|portion(?:en)?)\b[\s,.:\-]*",
re.IGNORECASE,
)
MULTISPACE_RE = re.compile(r"\s+")
DECIMAL_IN_NAME_RE = re.compile(r"(\d),(\d)")
def normalize_food_name(raw: str | None) -> str:
if not raw:
return ""
s = unicodedata.normalize("NFKC", str(raw)).strip().strip('"').strip("'")
s = LEADING_QTY_RE.sub("", s)
s = DECIMAL_IN_NAME_RE.sub(r"\1.\2", s)
s = MULTISPACE_RE.sub(" ", s).strip().lower()
return s
def parse_quantity_g(raw: str | None) -> float | None:
if raw is None or str(raw).strip() == "":
return None
text = str(raw).strip().replace(",", ".")
m = re.match(r"^\s*(\d+(?:\.\d+)?)\s*(g|gramm)?\s*$", text, re.IGNORECASE)
if m:
return round(float(m.group(1)), 3)
return None
def get_food_mapping_with_cursor(
cur,
source_name: str,
profile_id: str | None = None,
source_system: str = "fddb",
) -> dict[str, Any] | None:
norm = normalize_food_name(source_name)
if not norm:
return None
if profile_id:
cur.execute(
"""
SELECT m.id AS mapping_id, m.food_id, m.profile_id, m.source,
f.bls_code, f.name_de, f.catalog_kind
FROM food_name_mappings m
JOIN food_catalog f ON f.id = m.food_id
WHERE m.source_system = %s AND m.source_name_normalized = %s
AND m.profile_id = %s
LIMIT 1
""",
(source_system, norm, profile_id),
)
row = cur.fetchone()
if row:
return dict(row)
cur.execute(
"""
SELECT m.id AS mapping_id, m.food_id, m.profile_id, m.source,
f.bls_code, f.name_de, f.catalog_kind
FROM food_name_mappings m
JOIN food_catalog f ON f.id = m.food_id
WHERE m.source_system = %s AND m.source_name_normalized = %s
AND m.profile_id IS NULL
LIMIT 1
""",
(source_system, norm),
)
row = cur.fetchone()
return dict(row) if row else None
def upsert_food_mapping(
cur,
*,
source_name_raw: str,
food_id: str,
profile_id: str | None,
source: str = "bulk",
source_system: str = "fddb",
) -> int:
norm = normalize_food_name(source_name_raw)
if not norm:
raise ValueError("Leerer Lebensmittelname")
if profile_id:
cur.execute(
"""
SELECT id FROM food_name_mappings
WHERE source_system = %s AND source_name_normalized = %s AND profile_id = %s
""",
(source_system, norm, profile_id),
)
else:
cur.execute(
"""
SELECT id FROM food_name_mappings
WHERE source_system = %s AND source_name_normalized = %s AND profile_id IS NULL
""",
(source_system, norm),
)
existing = cur.fetchone()
raw = source_name_raw.strip()
if existing:
cur.execute(
"""
UPDATE food_name_mappings
SET food_id = %s, source_name_raw = %s, source = %s, updated_at = NOW()
WHERE id = %s
""",
(food_id, raw, source, existing["id"]),
)
return int(existing["id"])
cur.execute(
"""
INSERT INTO food_name_mappings
(source_system, source_name_raw, source_name_normalized, food_id, profile_id, source, updated_at)
VALUES (%s, %s, %s, %s, %s, %s, NOW())
RETURNING id
""",
(source_system, raw, norm, food_id, profile_id, source),
)
return int(cur.fetchone()["id"])
def apply_mapping_to_items(cur, profile_id: str, source_name_normalized: str, food_id: str, mapping_id: int) -> int:
origin = _value_origin_for_food(cur, food_id)
cur.execute(
"""
UPDATE nutrition_items
SET food_id = %s, mapping_id = %s, value_origin = %s, updated_at = NOW()
WHERE profile_id = %s AND source_name_normalized = %s
""",
(food_id, mapping_id, origin, profile_id, source_name_normalized),
)
return cur.rowcount or 0
def clear_mapping_from_items(cur, profile_id: str, source_name_normalized: str) -> int:
cur.execute(
"""
UPDATE nutrition_items
SET food_id = NULL, mapping_id = NULL, value_origin = 'fddb', updated_at = NOW()
WHERE profile_id = %s AND source_name_normalized = %s
""",
(profile_id, source_name_normalized),
)
return cur.rowcount or 0
def _value_origin_for_food(cur, food_id: str) -> str:
cur.execute("SELECT catalog_kind FROM food_catalog WHERE id = %s", (food_id,))
row = cur.fetchone()
if not row:
return "fddb"
kind = row["catalog_kind"]
if kind == "official_bls":
return "bls"
return "manual_catalog"
def suggest_catalog_foods(cur, query: str, profile_id: str | None, limit: int = 8) -> list[dict]:
q = (query or "").strip()
if not q:
return []
like = f"%{q}%"
norm = normalize_food_name(q)
cur.execute(
"""
SELECT id, bls_code, name_de, name_en, catalog_kind, food_group
FROM food_catalog
WHERE is_active = true
AND (
owner_profile_id IS NULL
OR owner_profile_id = %s
)
AND (
name_de ILIKE %s OR COALESCE(name_en, '') ILIKE %s
OR COALESCE(bls_code, '') ILIKE %s
OR lower(name_de) = %s
)
ORDER BY
CASE WHEN lower(name_de) = %s THEN 0
WHEN COALESCE(bls_code, '') ILIKE %s THEN 1
ELSE 2 END,
name_de
LIMIT %s
""",
(profile_id, like, like, like, norm, norm, q, limit),
)
return [dict(r) for r in cur.fetchall()]

View File

@ -0,0 +1,437 @@
"""Nutrition diary items, three macro sums, import policy, attribute resolve."""
from __future__ import annotations
import uuid
from datetime import date, datetime
from typing import Any
from data_layer.food_mapping import (
get_food_mapping_with_cursor,
normalize_food_name,
parse_quantity_g,
)
MACRO_ATTR_KEYS = {
"kcal": "ENERCC",
"protein_g": "PROT625",
"fat_g": "FAT",
"carbs_g": "CHO",
}
POLICIES = frozenset({"prompt", "overwrite_catalog", "overwrite_fddb", "keep_existing"})
def _f(v: Any) -> float:
if v is None or v == "":
return 0.0
try:
return float(v)
except (TypeError, ValueError):
return 0.0
def _round_macros(d: dict[str, float]) -> dict[str, float]:
return {
"kcal": round(_f(d.get("kcal")), 1),
"protein_g": round(_f(d.get("protein_g")), 1),
"fat_g": round(_f(d.get("fat_g")), 1),
"carbs_g": round(_f(d.get("carbs_g")), 1),
}
def macros_differ(a: dict[str, float], b: dict[str, float]) -> bool:
aa, bb = _round_macros(a), _round_macros(b)
return any(aa[k] != bb[k] for k in aa)
def get_import_policy(cur, profile_id: str) -> str:
cur.execute(
"SELECT nutrition_import_conflict_policy FROM profiles WHERE id = %s",
(profile_id,),
)
row = cur.fetchone()
if not row:
return "prompt"
pol = row.get("nutrition_import_conflict_policy") or "prompt"
return pol if pol in POLICIES else "prompt"
def catalog_macros_for_item(cur, food_id: str | None, quantity_g: float | None) -> dict[str, float] | None:
if not food_id or quantity_g is None or quantity_g <= 0:
return None
cur.execute(
"""
SELECT a.attr_key, v.value_num, v.is_trace
FROM food_attribute_values v
JOIN food_attributes a ON a.id = v.attribute_id
WHERE v.food_id = %s AND a.attr_key = ANY(%s) AND a.data_type = 'num_per_100g'
""",
(food_id, list(MACRO_ATTR_KEYS.values())),
)
by_key = {r["attr_key"]: r for r in cur.fetchall()}
if not by_key:
return None
out = {}
factor = float(quantity_g) / 100.0
missing = False
for field, key in MACRO_ATTR_KEYS.items():
row = by_key.get(key)
if not row or row.get("is_trace") or row.get("value_num") is None:
missing = True
break
out[field] = float(row["value_num"]) * factor
return None if missing else out
def compute_day_macro_sums(cur, profile_id: str, day: date | str) -> dict[str, Any]:
cur.execute(
"""
SELECT kcal, protein_g, fat_g, carbs_g, macro_origin, has_items
FROM nutrition_log WHERE profile_id = %s AND date = %s
""",
(profile_id, day),
)
existing = cur.fetchone()
existing_macros = (
_round_macros(existing)
if existing
else None
)
cur.execute(
"""
SELECT food_id, quantity_g, fddb_kcal, fddb_protein_g, fddb_fat_g, fddb_carbs_g, value_origin
FROM nutrition_items
WHERE profile_id = %s AND date = %s
""",
(profile_id, day),
)
items = cur.fetchall()
fddb = {"kcal": 0.0, "protein_g": 0.0, "fat_g": 0.0, "carbs_g": 0.0}
catalog = {"kcal": 0.0, "protein_g": 0.0, "fat_g": 0.0, "carbs_g": 0.0}
mapped = unmapped = 0
used_bls = used_fddb = False
for it in items:
fddb["kcal"] += _f(it.get("fddb_kcal"))
fddb["protein_g"] += _f(it.get("fddb_protein_g"))
fddb["fat_g"] += _f(it.get("fddb_fat_g"))
fddb["carbs_g"] += _f(it.get("fddb_carbs_g"))
cat = catalog_macros_for_item(cur, it.get("food_id"), it.get("quantity_g"))
if cat:
mapped += 1
used_bls = True
for k in catalog:
catalog[k] += cat[k]
else:
unmapped += 1
used_fddb = True
catalog["kcal"] += _f(it.get("fddb_kcal"))
catalog["protein_g"] += _f(it.get("fddb_protein_g"))
catalog["fat_g"] += _f(it.get("fddb_fat_g"))
catalog["carbs_g"] += _f(it.get("fddb_carbs_g"))
origin = "mixed"
if used_bls and not used_fddb:
origin = "bls"
elif used_fddb and not used_bls:
origin = "fddb"
if not items:
origin = "manual"
return {
"existing": existing_macros,
"fddb": _round_macros(fddb) if items else None,
"catalog": _round_macros(catalog) if items else None,
"mapped_item_count": mapped,
"unmapped_item_count": unmapped,
"has_items": bool(items),
"catalog_origin": origin,
"has_log": existing is not None,
"macro_origin": existing["macro_origin"] if existing else None,
}
def apply_nutrition_day_macros(
cur,
profile_id: str,
day: date | str,
macros: dict[str, float],
*,
macro_origin: str,
source: str = "csv",
confirm: bool = False,
) -> str:
m = _round_macros(macros)
cur.execute("SELECT id FROM nutrition_log WHERE profile_id = %s AND date = %s", (profile_id, day))
row = cur.fetchone()
counts = compute_day_macro_sums(cur, profile_id, day)
extra = (
counts["mapped_item_count"],
counts["unmapped_item_count"],
counts["has_items"],
)
confirmed = datetime.utcnow() if confirm else None
if row:
cur.execute(
"""
UPDATE nutrition_log
SET kcal=%s, protein_g=%s, fat_g=%s, carbs_g=%s, source=%s,
macro_origin=%s, mapped_item_count=%s, unmapped_item_count=%s,
has_items=%s, last_import_at=NOW(), macros_confirmed_at=COALESCE(%s, macros_confirmed_at)
WHERE profile_id=%s AND date=%s
""",
(
m["kcal"], m["protein_g"], m["fat_g"], m["carbs_g"], source,
macro_origin, extra[0], extra[1], extra[2], confirmed, profile_id, day,
),
)
return "updated"
eid = str(uuid.uuid4())
cur.execute(
"""
INSERT INTO nutrition_log (
id, profile_id, date, kcal, protein_g, fat_g, carbs_g, source,
macro_origin, mapped_item_count, unmapped_item_count, has_items,
last_import_at, macros_confirmed_at, created
) VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,NOW(),%s,CURRENT_TIMESTAMP)
""",
(
eid, profile_id, day, m["kcal"], m["protein_g"], m["fat_g"], m["carbs_g"], source,
macro_origin, extra[0], extra[1], extra[2], confirmed,
),
)
return "created"
def rebuild_daily_nutrients(cur, profile_id: str, day: date | str) -> None:
cur.execute(
"DELETE FROM nutrition_daily_nutrients WHERE profile_id = %s AND date = %s",
(profile_id, day),
)
cur.execute(
"""
SELECT i.food_id, i.quantity_g
FROM nutrition_items i
WHERE i.profile_id = %s AND i.date = %s
AND i.food_id IS NOT NULL AND i.quantity_g IS NOT NULL AND i.quantity_g > 0
""",
(profile_id, day),
)
acc: dict[int, list[float]] = {}
for it in cur.fetchall():
cur.execute(
"""
SELECT v.attribute_id, v.value_num, v.is_trace, a.data_type
FROM food_attribute_values v
JOIN food_attributes a ON a.id = v.attribute_id
WHERE v.food_id = %s AND a.data_type = 'num_per_100g'
AND v.value_num IS NOT NULL AND v.is_trace = false
""",
(it["food_id"],),
)
factor = float(it["quantity_g"]) / 100.0
for row in cur.fetchall():
acc.setdefault(row["attribute_id"], []).append(float(row["value_num"]) * factor)
for attr_id, vals in acc.items():
cur.execute(
"""
INSERT INTO nutrition_daily_nutrients
(profile_id, date, attribute_id, value, contributing_item_count, updated_at)
VALUES (%s, %s, %s, %s, %s, NOW())
""",
(profile_id, day, attr_id, round(sum(vals), 6), len(vals)),
)
def _item_value_origin(mapping: dict | None) -> str:
if not mapping:
return "fddb"
kind = mapping.get("catalog_kind")
if kind == "official_bls":
return "bls"
if kind in ("manual_admin", "manual_user"):
return "manual_catalog"
return "fddb"
def replace_csv_items_for_dates(
cur,
profile_id: str,
rows: list[dict[str, Any]],
*,
policy: str,
policy_override: str | None = None,
) -> dict[str, Any]:
"""
Replace csv-sourced items for the dates present in rows.
Returns conflicts when policy is prompt and existing macros differ.
"""
effective = policy_override if policy_override in POLICIES else policy
by_date: dict[str, list[dict]] = {}
for row in rows:
d = row.get("date")
if hasattr(d, "isoformat"):
iso = d.isoformat()
else:
iso = str(d)[:10]
if not iso:
continue
by_date.setdefault(iso, []).append(row)
conflicts = []
days_written = 0
items_written = 0
new_log_days = 0
for iso, day_rows in by_date.items():
cur.execute(
"""
DELETE FROM nutrition_items
WHERE profile_id = %s AND date = %s AND source = 'csv'
""",
(profile_id, iso),
)
for raw in day_rows:
name = (raw.get("food_name") or raw.get("source_name_raw") or "").strip()
if not name:
continue
qty_raw = raw.get("quantity_raw")
qty_g = parse_quantity_g(qty_raw if qty_raw is not None else name)
mapping = get_food_mapping_with_cursor(cur, name, profile_id)
logged_at = raw.get("logged_at")
cur.execute(
"""
INSERT INTO nutrition_items (
id, profile_id, date, logged_at, source_name_raw, source_name_normalized,
source_system, quantity_raw, quantity_g,
fddb_kcal, fddb_protein_g, fddb_fat_g, fddb_carbs_g,
food_id, mapping_id, value_origin, source
) VALUES (
%s,%s,%s,%s,%s,%s,'fddb',%s,%s,%s,%s,%s,%s,%s,%s,%s,'csv'
)
""",
(
str(uuid.uuid4()),
profile_id,
iso,
logged_at,
name,
normalize_food_name(name),
str(qty_raw) if qty_raw is not None else None,
qty_g,
_f(raw.get("fddb_kcal") if raw.get("fddb_kcal") is not None else raw.get("kcal")),
_f(raw.get("fddb_protein_g") if raw.get("fddb_protein_g") is not None else raw.get("protein_g")),
_f(raw.get("fddb_fat_g") if raw.get("fddb_fat_g") is not None else raw.get("fat_g")),
_f(raw.get("fddb_carbs_g") if raw.get("fddb_carbs_g") is not None else raw.get("carbs_g")),
mapping["food_id"] if mapping else None,
mapping["mapping_id"] if mapping else None,
_item_value_origin(mapping),
),
)
items_written += 1
days_written += 1
sums = compute_day_macro_sums(cur, profile_id, iso)
rebuild_daily_nutrients(cur, profile_id, iso)
if not sums["has_items"]:
continue
if not sums["has_log"]:
apply_nutrition_day_macros(
cur, profile_id, iso, sums["catalog"],
macro_origin=sums["catalog_origin"], source="csv",
)
new_log_days += 1
continue
existing = sums["existing"]
catalog = sums["catalog"]
fddb = sums["fddb"]
differ = macros_differ(existing, catalog) or macros_differ(existing, fddb)
if effective == "keep_existing":
_touch_item_counts(cur, profile_id, iso, sums)
continue
if effective == "overwrite_catalog":
apply_nutrition_day_macros(
cur, profile_id, iso, catalog,
macro_origin=sums["catalog_origin"], source="csv",
)
continue
if effective == "overwrite_fddb":
apply_nutrition_day_macros(
cur, profile_id, iso, fddb, macro_origin="fddb", source="csv",
)
continue
# prompt
if differ:
conflicts.append({
"date": iso,
"existing": existing,
"fddb": fddb,
"catalog": catalog,
"catalog_origin": sums["catalog_origin"],
"mapped_item_count": sums["mapped_item_count"],
"unmapped_item_count": sums["unmapped_item_count"],
})
else:
apply_nutrition_day_macros(
cur, profile_id, iso, catalog,
macro_origin=sums["catalog_origin"], source="csv",
)
return {
"days_written": days_written,
"items_written": items_written,
"new_log_days": new_log_days,
"conflicts": conflicts,
"policy": effective,
}
def _touch_item_counts(cur, profile_id: str, day: str, sums: dict) -> None:
cur.execute(
"""
UPDATE nutrition_log
SET mapped_item_count=%s, unmapped_item_count=%s, has_items=%s, last_import_at=NOW()
WHERE profile_id=%s AND date=%s
""",
(
sums["mapped_item_count"],
sums["unmapped_item_count"],
sums["has_items"],
profile_id,
day,
),
)
def resolve_choice_macros(sums: dict[str, Any], choice: str) -> tuple[dict[str, float], str]:
if choice == "existing":
return sums["existing"], "user_confirmed"
if choice == "fddb":
return sums["fddb"], "fddb"
if choice == "catalog":
return sums["catalog"], sums.get("catalog_origin") or "mixed"
raise ValueError("Ungültige Wahl (existing|fddb|catalog)")
def resolve_food_attributes(cur, food_id: str) -> list[dict]:
cur.execute(
"""
SELECT a.attr_key, a.name_de, a.unit, a.category, a.data_type, a.origin AS attr_origin,
v.value_num, v.value_bool, v.value_text, v.is_trace, v.origin_code
FROM food_attributes a
LEFT JOIN food_attribute_values v
ON v.attribute_id = a.id AND v.food_id = %s
WHERE a.is_active = true
ORDER BY a.sort_order, a.attr_key
""",
(food_id,),
)
return [dict(r) for r in cur.fetchall()]
def dates_for_normalized_name(cur, profile_id: str, source_name_normalized: str) -> list[str]:
cur.execute(
"""
SELECT DISTINCT date::text AS date
FROM nutrition_items
WHERE profile_id = %s AND source_name_normalized = %s
""",
(profile_id, source_name_normalized),
)
return [r["date"] for r in cur.fetchall()]

View File

@ -38,6 +38,7 @@ from routers import app_dashboard # Geschützter App-Bereich: Dashboard-Layout
from routers import reports # Strukturierter PDF-Bericht (Profil v1)
from routers import csv_import, admin_csv_templates # Issue #21 Universal CSV Parser
from routers import admin_training_parameters, admin_activity_attribute_profiles # EAV session metrics
from routers import bls, admin_bls, admin_food_mappings # BLS catalog + FDDB mapping
# ── App Configuration ─────────────────────────────────────────────────────────
DATA_DIR = Path(os.getenv("DATA_DIR", "./data"))
@ -133,6 +134,9 @@ app.include_router(csv_import.router) # /api/csv/* (Issue #21)
app.include_router(admin_csv_templates.router) # /api/admin/csv-templates/* (Issue #21)
app.include_router(admin_training_parameters.router) # /api/admin/training-parameters
app.include_router(admin_activity_attribute_profiles.router) # /api/admin/training-*-parameters
app.include_router(bls.router) # /api/bls/*
app.include_router(admin_bls.router) # /api/admin/bls/*
app.include_router(admin_food_mappings.router) # /api/admin/food-mappings
# ── Health Check ──────────────────────────────────────────────────────────────
@app.get("/")

View File

@ -0,0 +1,205 @@
-- Migration 062: BLS/food catalog, typed attributes, FDDB mapping, nutrition items, day marks
-- Additive only. Official BLS rows upsert by bls_code / attr_key — never delete+reinsert.
CREATE TABLE IF NOT EXISTS food_attributes (
id SERIAL PRIMARY KEY,
attr_key VARCHAR(64) NOT NULL,
name_de VARCHAR(255) NOT NULL,
name_en VARCHAR(255),
unit VARCHAR(40),
category VARCHAR(80),
data_type VARCHAR(20) NOT NULL DEFAULT 'num_per_100g'
CHECK (data_type IN ('num_per_100g', 'boolean', 'text', 'enum')),
enum_values JSONB,
origin VARCHAR(20) NOT NULL DEFAULT 'official_bls'
CHECK (origin IN ('official_bls', 'extension')),
sort_order INT NOT NULL DEFAULT 0,
is_active BOOLEAN NOT NULL DEFAULT true,
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
CONSTRAINT uq_food_attributes_key UNIQUE (attr_key)
);
CREATE INDEX IF NOT EXISTS idx_food_attributes_origin ON food_attributes (origin);
CREATE TABLE IF NOT EXISTS food_catalog (
id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
bls_code VARCHAR(16),
external_key VARCHAR(80),
name_de VARCHAR(500) NOT NULL,
name_en VARCHAR(500),
food_group VARCHAR(8),
catalog_kind VARCHAR(20) NOT NULL DEFAULT 'official_bls'
CHECK (catalog_kind IN ('official_bls', 'manual_admin', 'manual_user')),
owner_profile_id UUID REFERENCES profiles(id) ON DELETE CASCADE,
bls_version VARCHAR(16),
source VARCHAR(40) NOT NULL DEFAULT 'bls_4.0',
is_active BOOLEAN NOT NULL DEFAULT true,
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
CONSTRAINT uq_food_catalog_bls_code UNIQUE (bls_code),
CONSTRAINT chk_food_catalog_bls_code CHECK (
(catalog_kind = 'official_bls' AND bls_code IS NOT NULL)
OR (catalog_kind <> 'official_bls' AND bls_code IS NULL)
)
);
CREATE INDEX IF NOT EXISTS idx_food_catalog_name_de ON food_catalog (lower(name_de));
CREATE INDEX IF NOT EXISTS idx_food_catalog_kind ON food_catalog (catalog_kind);
CREATE INDEX IF NOT EXISTS idx_food_catalog_owner ON food_catalog (owner_profile_id)
WHERE owner_profile_id IS NOT NULL;
CREATE TABLE IF NOT EXISTS food_attribute_values (
id BIGSERIAL PRIMARY KEY,
food_id UUID NOT NULL REFERENCES food_catalog(id) ON DELETE CASCADE,
attribute_id INT NOT NULL REFERENCES food_attributes(id) ON DELETE CASCADE,
value_num DOUBLE PRECISION,
value_bool BOOLEAN,
value_text TEXT,
is_trace BOOLEAN NOT NULL DEFAULT false,
origin_code VARCHAR(80),
reference_text TEXT,
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
CONSTRAINT uq_food_attribute_value UNIQUE (food_id, attribute_id),
CONSTRAINT chk_food_attr_one_value CHECK (
(
(value_num IS NOT NULL)::int
+ (value_bool IS NOT NULL)::int
+ (value_text IS NOT NULL)::int
) <= 1
)
);
CREATE INDEX IF NOT EXISTS idx_fav_food ON food_attribute_values (food_id);
CREATE INDEX IF NOT EXISTS idx_fav_attr ON food_attribute_values (attribute_id);
CREATE TABLE IF NOT EXISTS food_name_mappings (
id SERIAL PRIMARY KEY,
source_system VARCHAR(20) NOT NULL DEFAULT 'fddb',
source_name_raw VARCHAR(500) NOT NULL,
source_name_normalized VARCHAR(500) NOT NULL,
food_id UUID NOT NULL REFERENCES food_catalog(id) ON DELETE CASCADE,
profile_id UUID REFERENCES profiles(id) ON DELETE CASCADE,
source VARCHAR(20) NOT NULL DEFAULT 'manual'
CHECK (source IN ('manual', 'bulk', 'admin')),
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
);
CREATE UNIQUE INDEX IF NOT EXISTS uq_food_map_global
ON food_name_mappings (source_system, source_name_normalized)
WHERE profile_id IS NULL;
CREATE UNIQUE INDEX IF NOT EXISTS uq_food_map_user
ON food_name_mappings (source_system, source_name_normalized, profile_id)
WHERE profile_id IS NOT NULL;
CREATE INDEX IF NOT EXISTS idx_food_map_food ON food_name_mappings (food_id);
CREATE TABLE IF NOT EXISTS nutrition_items (
id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
profile_id UUID NOT NULL REFERENCES profiles(id) ON DELETE CASCADE,
date DATE NOT NULL,
logged_at TIMESTAMPTZ,
source_name_raw VARCHAR(500) NOT NULL,
source_name_normalized VARCHAR(500) NOT NULL,
source_system VARCHAR(20) NOT NULL DEFAULT 'fddb',
quantity_raw VARCHAR(80),
quantity_g NUMERIC(10,3),
fddb_kcal NUMERIC(8,2),
fddb_protein_g NUMERIC(8,2),
fddb_fat_g NUMERIC(8,2),
fddb_carbs_g NUMERIC(8,2),
food_id UUID REFERENCES food_catalog(id) ON DELETE SET NULL,
mapping_id INT REFERENCES food_name_mappings(id) ON DELETE SET NULL,
value_origin VARCHAR(20) NOT NULL DEFAULT 'fddb'
CHECK (value_origin IN ('fddb', 'bls', 'manual_catalog')),
source VARCHAR(20) NOT NULL DEFAULT 'csv'
CHECK (source IN ('csv', 'manual')),
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
);
CREATE INDEX IF NOT EXISTS idx_nutrition_items_profile_date
ON nutrition_items (profile_id, date DESC);
CREATE INDEX IF NOT EXISTS idx_nutrition_items_unmapped
ON nutrition_items (profile_id, source_name_normalized)
WHERE food_id IS NULL;
CREATE TABLE IF NOT EXISTS nutrition_daily_nutrients (
id BIGSERIAL PRIMARY KEY,
profile_id UUID NOT NULL REFERENCES profiles(id) ON DELETE CASCADE,
date DATE NOT NULL,
attribute_id INT NOT NULL REFERENCES food_attributes(id) ON DELETE CASCADE,
value DOUBLE PRECISION NOT NULL,
contributing_item_count INT NOT NULL DEFAULT 0,
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
CONSTRAINT uq_nutrition_daily_nutrient UNIQUE (profile_id, date, attribute_id)
);
CREATE INDEX IF NOT EXISTS idx_ndn_profile_date
ON nutrition_daily_nutrients (profile_id, date DESC);
CREATE TABLE IF NOT EXISTS nutrition_day_marks (
id SERIAL PRIMARY KEY,
profile_id UUID NOT NULL REFERENCES profiles(id) ON DELETE CASCADE,
date DATE NOT NULL,
mark_type VARCHAR(20) NOT NULL CHECK (mark_type IN ('fasting', 'incomplete')),
note TEXT,
source VARCHAR(20) NOT NULL DEFAULT 'manual',
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
CONSTRAINT uq_nutrition_day_mark UNIQUE (profile_id, date)
);
ALTER TABLE nutrition_log ADD COLUMN IF NOT EXISTS macro_origin VARCHAR(20);
ALTER TABLE nutrition_log ADD COLUMN IF NOT EXISTS mapped_item_count INT;
ALTER TABLE nutrition_log ADD COLUMN IF NOT EXISTS unmapped_item_count INT;
ALTER TABLE nutrition_log ADD COLUMN IF NOT EXISTS has_items BOOLEAN DEFAULT false;
ALTER TABLE nutrition_log ADD COLUMN IF NOT EXISTS last_import_at TIMESTAMPTZ;
ALTER TABLE nutrition_log ADD COLUMN IF NOT EXISTS macros_confirmed_at TIMESTAMPTZ;
DELETE FROM nutrition_log a
USING nutrition_log b
WHERE a.profile_id = b.profile_id
AND a.date = b.date
AND (a.created < b.created OR (a.created = b.created AND a.id::text < b.id::text));
CREATE UNIQUE INDEX IF NOT EXISTS uq_nutrition_log_profile_date
ON nutrition_log (profile_id, date);
ALTER TABLE profiles
ADD COLUMN IF NOT EXISTS nutrition_import_conflict_policy VARCHAR(30) DEFAULT 'prompt';
DO $$
BEGIN
IF NOT EXISTS (
SELECT 1 FROM pg_constraint WHERE conname = 'chk_nutrition_import_policy'
) THEN
ALTER TABLE profiles ADD CONSTRAINT chk_nutrition_import_policy
CHECK (nutrition_import_conflict_policy IN (
'prompt', 'overwrite_catalog', 'overwrite_fddb', 'keep_existing'
));
END IF;
END $$;
UPDATE csv_field_mappings
SET field_mappings = COALESCE(field_mappings, '{}'::jsonb)
|| '{"bezeichnung": "food_name", "menge": "quantity_raw"}'::jsonb,
updated_at = NOW()
WHERE is_system = true
AND module = 'nutrition'
AND (
mapping_name ILIKE '%FDDB%'
OR mapping_name ILIKE '%fddb%'
);
COMMENT ON TABLE food_catalog IS 'BLS 4.0 official foods + manual catalog extensions';
COMMENT ON COLUMN food_catalog.bls_code IS 'Stable official BLS identity; upsert key';
COMMENT ON TABLE food_name_mappings IS 'Learned FDDB name -> food_catalog; user overrides global';
COMMENT ON TABLE nutrition_day_marks IS 'Explicit fasting/incomplete; import must not delete';
DO $$
BEGIN
RAISE NOTICE 'Migration 062: BLS food catalog, mappings, nutrition items, day marks';
END $$;

View File

@ -30,6 +30,7 @@ class ProfileUpdate(BaseModel):
goal_bf_pct: Optional[float] = None
quality_filter_level: Optional[str] = None # Issue #31: Global quality filter
email: Optional[str] = None # Self-service; leer = entfernen; Änderung setzt Verifikation zurück
nutrition_import_conflict_policy: Optional[str] = None
# ── Tracking Models ───────────────────────────────────────────────────────────

View File

@ -12,3 +12,4 @@ python-dateutil==2.9.0
tzdata>=2024.1 # ZoneInfo (Europe/Berlin) auch unter Windows
matplotlib==3.8.4
reportlab==4.2.0
openpyxl==3.1.5

View File

@ -617,6 +617,24 @@ async def import_activity_csv(file: UploadFile=File(...), x_profile_id: Optional
Persistenz läuft über activity_persistence_orchestrator gleiche Schicht wie Universal-CSV.
"""
pid = get_pid(x_profile_id)
# Feature-Enforcement (wie manueller Create + nutrition/import-csv): activity_entries
access = check_feature_access(pid, "activity_entries")
log_feature_usage(pid, "activity_entries", access, "import_csv")
if not access["allowed"]:
logger.warning(
f"[FEATURE-LIMIT] User {pid} blocked: "
f"activity_entries {access['reason']} (used: {access['used']}, limit: {access['limit']})"
)
raise HTTPException(
status_code=403,
detail=(
f"Limit erreicht: Du hast das Kontingent für Aktivitätseinträge überschritten "
f"({access['used']}/{access['limit']}). "
f"Bitte kontaktiere den Admin oder warte bis zum nächsten Reset."
),
)
raw = await file.read()
try: text = raw.decode('utf-8')
except: text = raw.decode('latin-1')
@ -729,4 +747,8 @@ async def import_activity_csv(file: UploadFile=File(...), x_profile_id: Optional
except Exception as e:
logger.warning(f"Import row failed: {e}")
skipped+=1
for _ in range(inserted):
increment_feature_usage(pid, "activity_entries")
return {"inserted":inserted,"skipped":skipped,"message":f"{inserted} Trainings importiert"}

View File

@ -0,0 +1,282 @@
"""Admin BLS catalog import and attribute/food maintenance."""
from __future__ import annotations
from typing import Optional
from fastapi import APIRouter, Depends, File, HTTPException, UploadFile
from fastapi.concurrency import run_in_threadpool
from pydantic import BaseModel
from auth import require_admin
from bls.import_service import upsert_attributes, upsert_foods
from bls.jobs import create_and_check, get_job, start_apply
from bls.parser import parse_components_xlsx, parse_foods_xlsx
from db import get_cursor, get_db, r2d
MAX_IMPORT_BYTES = 50 * 1024 * 1024
router = APIRouter(prefix="/api/admin/bls", tags=["admin", "bls"])
class AttributeCreate(BaseModel):
attr_key: str
name_de: str
name_en: Optional[str] = None
unit: Optional[str] = None
category: Optional[str] = None
data_type: str = "num_per_100g"
enum_values: Optional[list] = None
class ManualFoodCreate(BaseModel):
name_de: str
name_en: Optional[str] = None
macros_per_100g: Optional[dict] = None
@router.get("/status")
def bls_status(session: dict = Depends(require_admin)):
with get_db() as conn:
cur = get_cursor(conn)
cur.execute("SELECT COUNT(*) AS n FROM food_catalog WHERE catalog_kind = 'official_bls'")
foods = cur.fetchone()["n"]
cur.execute("SELECT COUNT(*) AS n FROM food_attributes WHERE origin = 'official_bls'")
attrs = cur.fetchone()["n"]
cur.execute("SELECT COUNT(*) AS n FROM food_catalog WHERE catalog_kind <> 'official_bls'")
manual = cur.fetchone()["n"]
cur.execute("SELECT MAX(updated_at) AS last_updated FROM food_catalog WHERE catalog_kind = 'official_bls'")
last = cur.fetchone()["last_updated"]
return {
"official_foods": foods,
"official_attributes": attrs,
"manual_foods": manual,
"last_updated": last,
"source": "Max Rubner-Institut, BLS 4.0 (frei verfügbar)",
}
@router.post("/import/components")
async def import_components(
file: UploadFile = File(...),
dry_run: bool = True,
session: dict = Depends(require_admin),
):
raw = await file.read()
if not raw:
raise HTTPException(400, "Leere Datei")
try:
attrs = await run_in_threadpool(parse_components_xlsx, raw)
except Exception as e:
raise HTTPException(400, f"Components-Datei unlesbar: {e}") from e
if dry_run:
return {"dry_run": True, "attributes": len(attrs), "sample": attrs[:8]}
def apply():
with get_db() as conn:
cur = get_cursor(conn)
return upsert_attributes(cur, attrs)
stats = await run_in_threadpool(apply)
return {"dry_run": False, **stats}
@router.post("/import/foods")
async def import_foods(
file: UploadFile = File(...),
dry_run: bool = True,
session: dict = Depends(require_admin),
):
raw = await file.read()
if not raw:
raise HTTPException(400, "Leere Datei")
try:
parsed = await run_in_threadpool(parse_foods_xlsx, raw)
except Exception as e:
raise HTTPException(400, f"Datendatei unlesbar: {e}") from e
foods = parsed["foods"]
if dry_run:
return {
"dry_run": True,
"foods": len(foods),
"attribute_columns": len(parsed["attribute_headers"]),
"sample": [
{"bls_code": f["bls_code"], "name_de": f["name_de"]}
for f in foods[:8]
],
}
def apply():
with get_db() as conn:
cur = get_cursor(conn)
return upsert_foods(cur, foods)
stats = await run_in_threadpool(apply)
return {"dry_run": False, **stats}
@router.post("/import/jobs")
async def start_import_job(
kind: str,
file: UploadFile = File(...),
session: dict = Depends(require_admin),
):
if kind not in ("components", "foods"):
raise HTTPException(400, "kind muss components oder foods sein")
raw = await file.read()
if not raw:
raise HTTPException(400, "Leere Datei")
if len(raw) > MAX_IMPORT_BYTES:
raise HTTPException(400, "Datei größer als 50 MB")
job_id = create_and_check(kind, raw)
return {"id": job_id, "status": "checking"}
@router.get("/import/jobs/{job_id}")
def import_job_status(job_id: str, session: dict = Depends(require_admin)):
job = get_job(job_id)
if not job:
raise HTTPException(404, "Import-Job nicht gefunden")
return job
@router.post("/import/jobs/{job_id}/apply")
def apply_import_job(job_id: str, session: dict = Depends(require_admin)):
try:
start_apply(job_id)
except KeyError:
raise HTTPException(404, "Import-Job nicht gefunden") from None
except ValueError as e:
raise HTTPException(409, str(e)) from e
return get_job(job_id)
@router.get("/foods")
def admin_list_foods(
q: Optional[str] = None,
kind: Optional[str] = None,
limit: int = 50,
session: dict = Depends(require_admin),
):
limit = min(max(limit, 1), 200)
with get_db() as conn:
cur = get_cursor(conn)
conds = ["is_active = true"]
params: list = []
if kind:
conds.append("catalog_kind = %s")
params.append(kind)
if q:
conds.append("(name_de ILIKE %s OR COALESCE(name_en,'') ILIKE %s OR COALESCE(bls_code,'') ILIKE %s)")
like = f"%{q}%"
params.extend([like, like, like])
params.append(limit)
cur.execute(
f"""
SELECT id, bls_code, name_de, name_en, catalog_kind, food_group, bls_version
FROM food_catalog
WHERE {' AND '.join(conds)}
ORDER BY name_de
LIMIT %s
""",
params,
)
return [r2d(r) for r in cur.fetchall()]
@router.get("/foods/{food_id}")
def admin_food_detail(food_id: str, session: dict = Depends(require_admin)):
from data_layer.nutrition_items import resolve_food_attributes
with get_db() as conn:
cur = get_cursor(conn)
cur.execute("SELECT * FROM food_catalog WHERE id = %s", (food_id,))
row = cur.fetchone()
if not row:
raise HTTPException(404, "Lebensmittel nicht gefunden")
attrs = resolve_food_attributes(cur, food_id)
return {**r2d(row), "attributes": attrs}
@router.post("/foods/manual")
def admin_create_manual_food(body: ManualFoodCreate, session: dict = Depends(require_admin)):
from data_layer.food_mapping import normalize_food_name
name = (body.name_de or "").strip()
if not name:
raise HTTPException(400, "Name fehlt")
with get_db() as conn:
cur = get_cursor(conn)
cur.execute(
"""
INSERT INTO food_catalog (name_de, name_en, catalog_kind, source, external_key)
VALUES (%s, %s, 'manual_admin', 'manual', %s)
RETURNING *
""",
(name, body.name_en, f"man-admin-{normalize_food_name(name)[:40]}"),
)
food = r2d(cur.fetchone())
_write_manual_macros(cur, food["id"], body.macros_per_100g)
return food
@router.get("/attributes")
def admin_list_attributes(session: dict = Depends(require_admin)):
with get_db() as conn:
cur = get_cursor(conn)
cur.execute(
"""
SELECT id, attr_key, name_de, name_en, unit, category, data_type, origin, sort_order
FROM food_attributes
WHERE is_active = true
ORDER BY origin, sort_order, attr_key
"""
)
return [r2d(r) for r in cur.fetchall()]
@router.post("/attributes")
def admin_create_attribute(body: AttributeCreate, session: dict = Depends(require_admin)):
key = body.attr_key.strip().upper().replace(" ", "_")
if not key:
raise HTTPException(400, "attr_key fehlt")
if body.data_type not in ("num_per_100g", "boolean", "text", "enum"):
raise HTTPException(400, "Ungültiger data_type")
with get_db() as conn:
cur = get_cursor(conn)
try:
cur.execute(
"""
INSERT INTO food_attributes
(attr_key, name_de, name_en, unit, category, data_type, enum_values, origin, sort_order)
VALUES (%s, %s, %s, %s, %s, %s, %s, 'extension', 9000)
RETURNING *
""",
(
key, body.name_de, body.name_en, body.unit, body.category,
body.data_type, None if not body.enum_values else body.enum_values,
),
)
except Exception as e:
raise HTTPException(409, f"Attribut existiert bereits oder ist ungültig: {e}") from e
return r2d(cur.fetchone())
def _write_manual_macros(cur, food_id: str, macros: dict | None) -> None:
if not macros:
return
mapping = {"kcal": "ENERCC", "protein_g": "PROT625", "fat_g": "FAT", "carbs_g": "CHO"}
for field, key in mapping.items():
if field not in macros or macros[field] is None:
continue
cur.execute("SELECT id FROM food_attributes WHERE attr_key = %s", (key,))
row = cur.fetchone()
if not row:
continue
cur.execute(
"""
INSERT INTO food_attribute_values (food_id, attribute_id, value_num, is_trace)
VALUES (%s, %s, %s, false)
ON CONFLICT (food_id, attribute_id) DO UPDATE SET value_num = EXCLUDED.value_num, updated_at = NOW()
""",
(food_id, row["id"], float(macros[field])),
)

View File

@ -0,0 +1,103 @@
"""Admin CRUD for food_name_mappings."""
from __future__ import annotations
from typing import Optional
from fastapi import APIRouter, Depends, HTTPException
from pydantic import BaseModel
from auth import require_admin
from data_layer.food_mapping import upsert_food_mapping
from db import get_cursor, get_db, r2d
router = APIRouter(prefix="/api/admin/food-mappings", tags=["admin", "food-mappings"])
class FoodMappingCreate(BaseModel):
source_name: str
food_id: str
profile_id: Optional[str] = None
source_system: str = "fddb"
@router.get("")
def list_food_mappings(
profile_id: Optional[str] = None,
global_only: bool = False,
session: dict = Depends(require_admin),
):
with get_db() as conn:
cur = get_cursor(conn)
q = """
SELECT m.id, m.source_name_raw, m.source_name_normalized, m.food_id,
m.profile_id, m.source, m.created_at, m.updated_at,
f.name_de AS food_name_de, f.bls_code, f.catalog_kind
FROM food_name_mappings m
JOIN food_catalog f ON f.id = m.food_id
"""
conds, params = [], []
if global_only:
conds.append("m.profile_id IS NULL")
elif profile_id:
conds.append("m.profile_id = %s")
params.append(profile_id)
if conds:
q += " WHERE " + " AND ".join(conds)
q += " ORDER BY m.source_name_normalized"
cur.execute(q, params)
return [r2d(r) for r in cur.fetchall()]
@router.get("/stats/coverage")
def mapping_coverage(session: dict = Depends(require_admin)):
with get_db() as conn:
cur = get_cursor(conn)
cur.execute(
"""
SELECT
COUNT(*) AS total_items,
COUNT(food_id) AS mapped_items,
COUNT(*) - COUNT(food_id) AS unmapped_items,
COUNT(DISTINCT source_name_normalized) AS unique_names,
COUNT(DISTINCT CASE WHEN food_id IS NULL THEN source_name_normalized END) AS unmapped_names
FROM nutrition_items
"""
)
return r2d(cur.fetchone())
@router.post("")
def create_food_mapping(body: FoodMappingCreate, session: dict = Depends(require_admin)):
with get_db() as conn:
cur = get_cursor(conn)
cur.execute("SELECT id FROM food_catalog WHERE id = %s", (body.food_id,))
if not cur.fetchone():
raise HTTPException(404, "Lebensmittel nicht gefunden")
mid = upsert_food_mapping(
cur,
source_name_raw=body.source_name,
food_id=body.food_id,
profile_id=body.profile_id or None,
source="admin",
source_system=body.source_system,
)
cur.execute(
"""
SELECT m.*, f.name_de AS food_name_de, f.bls_code
FROM food_name_mappings m
JOIN food_catalog f ON f.id = m.food_id
WHERE m.id = %s
""",
(mid,),
)
return r2d(cur.fetchone())
@router.delete("/{mapping_id}")
def delete_food_mapping(mapping_id: int, session: dict = Depends(require_admin)):
with get_db() as conn:
cur = get_cursor(conn)
cur.execute("DELETE FROM food_name_mappings WHERE id = %s RETURNING id", (mapping_id,))
if not cur.fetchone():
raise HTTPException(404, "Mapping nicht gefunden")
return {"ok": True}

146
backend/routers/bls.py Normal file
View File

@ -0,0 +1,146 @@
"""Authenticated catalog search and user-owned foods / mappings."""
from __future__ import annotations
from typing import Optional
from fastapi import APIRouter, Depends, HTTPException
from pydantic import BaseModel
from auth import require_auth
from data_layer.food_mapping import (
apply_mapping_to_items,
clear_mapping_from_items,
normalize_food_name,
suggest_catalog_foods,
upsert_food_mapping,
)
from data_layer.nutrition_items import dates_for_normalized_name, rebuild_daily_nutrients
from db import get_cursor, get_db, r2d
from routers.profiles import get_pid
router = APIRouter(prefix="/api/bls", tags=["bls"])
class UserFoodCreate(BaseModel):
name_de: str
name_en: Optional[str] = None
macros_per_100g: Optional[dict] = None
class MappingUpsert(BaseModel):
source_name: str
food_id: str
source_system: str = "fddb"
@router.get("/foods")
def search_foods(
q: str = "",
limit: int = 20,
session: dict = Depends(require_auth),
):
pid = session["profile_id"]
with get_db() as conn:
cur = get_cursor(conn)
return suggest_catalog_foods(cur, q, pid, limit=min(max(limit, 1), 50))
@router.post("/foods/manual")
def create_user_food(body: UserFoodCreate, session: dict = Depends(require_auth)):
from routers.admin_bls import _write_manual_macros
pid = session["profile_id"]
name = (body.name_de or "").strip()
if not name:
raise HTTPException(400, "Name fehlt")
with get_db() as conn:
cur = get_cursor(conn)
cur.execute(
"""
INSERT INTO food_catalog
(name_de, name_en, catalog_kind, owner_profile_id, source, external_key)
VALUES (%s, %s, 'manual_user', %s, 'manual', %s)
RETURNING *
""",
(name, body.name_en, pid, f"man-user-{normalize_food_name(name)[:40]}"),
)
food = r2d(cur.fetchone())
_write_manual_macros(cur, food["id"], body.macros_per_100g)
return food
@router.get("/mappings")
def list_my_mappings(session: dict = Depends(require_auth)):
pid = session["profile_id"]
with get_db() as conn:
cur = get_cursor(conn)
cur.execute(
"""
SELECT m.id, m.source_name_raw, m.source_name_normalized, m.food_id, m.source,
f.name_de AS food_name_de, f.bls_code, f.catalog_kind
FROM food_name_mappings m
JOIN food_catalog f ON f.id = m.food_id
WHERE m.profile_id = %s
ORDER BY m.source_name_normalized
""",
(pid,),
)
return [r2d(r) for r in cur.fetchall()]
@router.post("/mappings")
def upsert_my_mapping(body: MappingUpsert, session: dict = Depends(require_auth)):
pid = session["profile_id"]
with get_db() as conn:
cur = get_cursor(conn)
cur.execute(
"""
SELECT id FROM food_catalog
WHERE id = %s AND is_active = true
AND (owner_profile_id IS NULL OR owner_profile_id = %s)
""",
(body.food_id, pid),
)
if not cur.fetchone():
raise HTTPException(404, "Lebensmittel nicht gefunden")
mid = upsert_food_mapping(
cur,
source_name_raw=body.source_name,
food_id=body.food_id,
profile_id=pid,
source="bulk",
source_system=body.source_system,
)
norm = normalize_food_name(body.source_name)
n = apply_mapping_to_items(cur, pid, norm, body.food_id, mid)
for d in dates_for_normalized_name(cur, pid, norm):
rebuild_daily_nutrients(cur, pid, d)
return {"mapping_id": mid, "items_updated": n, "source_name_normalized": norm}
@router.delete("/mappings/{mapping_id}")
def delete_my_mapping(mapping_id: int, session: dict = Depends(require_auth)):
pid = session["profile_id"]
with get_db() as conn:
cur = get_cursor(conn)
cur.execute(
"""
SELECT source_name_normalized FROM food_name_mappings
WHERE id = %s AND profile_id = %s
""",
(mapping_id, pid),
)
row = cur.fetchone()
if not row:
raise HTTPException(404, "Mapping nicht gefunden")
norm = row["source_name_normalized"]
dates = dates_for_normalized_name(cur, pid, norm)
clear_mapping_from_items(cur, pid, norm)
cur.execute("DELETE FROM food_name_mappings WHERE id = %s AND profile_id = %s", (mapping_id, pid))
for d in dates:
rebuild_daily_nutrients(cur, pid, d)
return {"ok": True}
# keep get_pid imported for consistency with other routers
_ = get_pid

View File

@ -35,6 +35,7 @@ from csv_parser.type_converter import build_row_after_mapping, diagnose_row_mapp
from csv_parser.field_units import source_unit_choices_for_field
from csv_parser.import_errors import enrich_row_error
from csv_parser.module_registry import get_module_definition, list_modules, validate_field_mappings
from csv_parser.template_validator import validate_csv_template
from data_layer.activity_persistence_orchestrator import merge_activity_csv_module_fields
from csv_parser.sleep_apple_import import detect_apple_sleep_csv_format
@ -50,6 +51,38 @@ def _load_import_limits() -> dict[str, int]:
return get_csv_import_limits(r2d(row) if row else None)
def _mapping_column_signature(m: dict) -> list[str] | None:
sig = m.get("column_signature")
if not sig:
return None
return list(sig)
def _validate_mapping_config(cur, m: dict) -> dict:
"""Strukturelle Vorlagen-Prüfung (wie Admin validate / Create)."""
return validate_csv_template(
m["module"],
m.get("field_mappings") or {},
m.get("type_conversions"),
m.get("import_row_processing"),
_mapping_column_signature(m),
cur=cur,
)
def _ensure_mapping_valid(cur, m: dict) -> dict:
report = _validate_mapping_config(cur, m)
if not report.get("valid"):
raise HTTPException(
status_code=422,
detail={
"message": "CSV-Vorlage ist strukturell ungültig.",
"validation": report,
},
)
return report
def _mapping_to_summary(m: dict) -> dict:
return {
"id": m["id"],
@ -184,6 +217,16 @@ def copy_csv_mapping(
n += 1
name = f"{base_name} {n}"
validation = _validate_mapping_config(cur, src)
if not validation.get("valid"):
raise HTTPException(
status_code=422,
detail={
"message": "Quell-Vorlage ist ungültig — Kopie abgebrochen.",
"validation": validation,
},
)
cur.execute(
"""
INSERT INTO csv_field_mappings (
@ -213,7 +256,21 @@ def copy_csv_mapping(
),
)
new_id = cur.fetchone()["id"]
return {"new_mapping_id": new_id, "mapping_name": name}
return {"new_mapping_id": new_id, "mapping_name": name, "validation": validation}
@router.get("/mappings/{mapping_id}/validate")
def validate_csv_mapping(
mapping_id: int,
session: dict = Depends(require_auth),
):
"""Strukturprüfung einer gespeicherten Vorlage (System oder eigenes Profil-Mapping)."""
pid = str(session["profile_id"])
with get_db() as conn:
cur = get_cursor(conn)
m = _fetch_mapping_row(cur, mapping_id, pid)
report = _validate_mapping_config(cur, m)
return {"mapping_id": mapping_id, "mapping_name": m.get("mapping_name"), **report}
@router.post("/analyze")
@ -538,6 +595,7 @@ async def csv_import_execute(
)
_check_module_feature_access(pid, exec_module)
_ensure_mapping_valid(cur, m)
cur.execute(
"""
@ -654,6 +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"],
}

View File

@ -31,8 +31,13 @@ def _pf(s):
# ── Endpoints ─────────────────────────────────────────────────────────────────
@router.post("/import-csv")
async def import_nutrition_csv(file: UploadFile=File(...), x_profile_id: Optional[str]=Header(default=None), session: dict=Depends(require_auth)):
"""Import FDDB nutrition CSV."""
async def import_nutrition_csv(
file: UploadFile = File(...),
overwrite_existing: bool = False,
x_profile_id: Optional[str] = Header(default=None),
session: dict = Depends(require_auth),
):
"""Import FDDB nutrition CSV (optional item persist + conflict policy)."""
pid = get_pid(x_profile_id)
# Phase 4: Check feature access and ENFORCE
@ -56,48 +61,97 @@ async def import_nutrition_csv(file: UploadFile=File(...), x_profile_id: Optiona
except: text = raw.decode('latin-1')
if text.startswith('\ufeff'): text = text[1:]
if not text.strip(): raise HTTPException(400,"Leere Datei")
from data_layer.nutrition_items import get_import_policy, replace_csv_items_for_dates
overwrite = bool(overwrite_existing)
reader = csv.DictReader(io.StringIO(text), delimiter=';')
item_rows = []
days: dict = {}
count = 0
for row in reader:
rd = row.get('datum_tag_monat_jahr_stunde_minute','').strip().strip('"')
if not rd: continue
try:
p = rd.split(' ')[0].split('.')
parts = rd.split(' ')
p = parts[0].split('.')
iso = f"{p[2]}-{p[1]}-{p[0]}"
except: continue
days.setdefault(iso,{'kcal':0,'fat_g':0,'carbs_g':0,'protein_g':0})
days[iso]['kcal'] += _pf(row.get('kj',0))/4.184
days[iso]['fat_g'] += _pf(row.get('fett_g',0))
days[iso]['carbs_g'] += _pf(row.get('kh_g',0))
days[iso]['protein_g'] += _pf(row.get('protein_g',0))
count+=1
inserted=0
new_entries=0
logged_at = None
if len(parts) > 1:
try:
logged_at = datetime.strptime(rd.strip(), '%d.%m.%Y %H:%M')
except ValueError:
logged_at = None
except Exception:
continue
kcal = _pf(row.get('kj', 0)) / 4.184
fat = _pf(row.get('fett_g', 0))
carbs = _pf(row.get('kh_g', 0))
prot = _pf(row.get('protein_g', 0))
days.setdefault(iso, {'kcal': 0, 'fat_g': 0, 'carbs_g': 0, 'protein_g': 0})
days[iso]['kcal'] += kcal
days[iso]['fat_g'] += fat
days[iso]['carbs_g'] += carbs
days[iso]['protein_g'] += prot
name = (row.get('bezeichnung') or '').strip().strip('"')
if name:
item_rows.append({
"date": iso,
"logged_at": logged_at,
"food_name": name,
"quantity_raw": (row.get('menge') or '').strip() or None,
"kcal": kcal,
"protein_g": prot,
"fat_g": fat,
"carbs_g": carbs,
})
count += 1
inserted = 0
new_entries = 0
ingest_result = {"conflicts": [], "items_written": 0, "policy": "prompt"}
with get_db() as conn:
cur = get_cursor(conn)
for iso,vals in days.items():
kcal=round(vals['kcal'],1); fat=round(vals['fat_g'],1)
carbs=round(vals['carbs_g'],1); prot=round(vals['protein_g'],1)
cur.execute("SELECT id FROM nutrition_log WHERE profile_id=%s AND date=%s",(pid,iso))
is_new = not cur.fetchone()
if not is_new:
# UPDATE existing
cur.execute("UPDATE nutrition_log SET kcal=%s,protein_g=%s,fat_g=%s,carbs_g=%s WHERE profile_id=%s AND date=%s",
(kcal,prot,fat,carbs,pid,iso))
else:
# INSERT new
cur.execute("INSERT INTO nutrition_log (id,profile_id,date,kcal,protein_g,fat_g,carbs_g,source,created) VALUES (%s,%s,%s,%s,%s,%s,%s,'csv',CURRENT_TIMESTAMP)",
(str(uuid.uuid4()),pid,iso,kcal,prot,fat,carbs))
new_entries += 1
inserted+=1
policy = get_import_policy(cur, pid)
override = "overwrite_catalog" if overwrite else None
if item_rows:
ingest_result = replace_csv_items_for_dates(
cur, pid, item_rows, policy=policy, policy_override=override,
)
new_entries = ingest_result.get("new_log_days") or 0
inserted = ingest_result.get("days_written") or 0
else:
for iso, vals in days.items():
kcal = round(vals['kcal'], 1)
fat = round(vals['fat_g'], 1)
carbs = round(vals['carbs_g'], 1)
prot = round(vals['protein_g'], 1)
cur.execute("SELECT id FROM nutrition_log WHERE profile_id=%s AND date=%s", (pid, iso))
is_new = not cur.fetchone()
if not is_new:
if policy in ("overwrite_catalog", "overwrite_fddb") or overwrite:
cur.execute(
"UPDATE nutrition_log SET kcal=%s,protein_g=%s,fat_g=%s,carbs_g=%s,source='csv',macro_origin='fddb' WHERE profile_id=%s AND date=%s",
(kcal, prot, fat, carbs, pid, iso),
)
else:
cur.execute(
"INSERT INTO nutrition_log (id,profile_id,date,kcal,protein_g,fat_g,carbs_g,source,macro_origin,created) VALUES (%s,%s,%s,%s,%s,%s,%s,'csv','fddb',CURRENT_TIMESTAMP)",
(str(uuid.uuid4()), pid, iso, kcal, prot, fat, carbs),
)
new_entries += 1
inserted += 1
# Phase 2: Increment usage counter for each new entry created
for _ in range(new_entries):
increment_feature_usage(pid, 'nutrition_entries')
return {"rows_parsed":count,"days_imported":inserted,"new_entries":new_entries,
"date_range":{"from":min(days) if days else None,"to":max(days) if days else None}}
return {
"rows_parsed": count,
"days_imported": inserted,
"new_entries": new_entries,
"items_written": ingest_result.get("items_written", 0),
"conflicts": ingest_result.get("conflicts") or [],
"policy": ingest_result.get("policy", "prompt"),
"date_range": {"from": min(days) if days else None, "to": max(days) if days else None},
}
@router.post("")
@ -122,7 +176,7 @@ def create_nutrition(date: str, kcal: float, protein_g: float, fat_g: float, car
# UPDATE existing entry
cur.execute("""
UPDATE nutrition_log
SET kcal=%s, protein_g=%s, fat_g=%s, carbs_g=%s, source='manual'
SET kcal=%s, protein_g=%s, fat_g=%s, carbs_g=%s, source='manual', macro_origin='manual'
WHERE id=%s AND profile_id=%s
""", (round(kcal,1), round(protein_g,1), round(fat_g,1), round(carbs_g,1), existing['id'], pid))
return {"success": True, "mode": "updated", "id": existing['id']}
@ -145,8 +199,8 @@ def create_nutrition(date: str, kcal: float, protein_g: float, fat_g: float, car
# INSERT new entry
new_id = str(uuid.uuid4())
cur.execute("""
INSERT INTO nutrition_log (id, profile_id, date, kcal, protein_g, fat_g, carbs_g, source, created)
VALUES (%s, %s, %s, %s, %s, %s, %s, 'manual', CURRENT_TIMESTAMP)
INSERT INTO nutrition_log (id, profile_id, date, kcal, protein_g, fat_g, carbs_g, source, macro_origin, created)
VALUES (%s, %s, %s, %s, %s, %s, %s, 'manual', 'manual', CURRENT_TIMESTAMP)
""", (new_id, pid, date, round(kcal,1), round(protein_g,1), round(fat_g,1), round(carbs_g,1)))
# Phase 2: Increment usage counter
@ -162,8 +216,34 @@ def list_nutrition(limit: int=365, x_profile_id: Optional[str]=Header(default=No
with get_db() as conn:
cur = get_cursor(conn)
cur.execute(
"SELECT * FROM nutrition_log WHERE profile_id=%s ORDER BY date DESC LIMIT %s", (pid,limit))
return [r2d(r) for r in cur.fetchall()]
"""
SELECT n.*, m.mark_type, m.note AS mark_note
FROM nutrition_log n
LEFT JOIN nutrition_day_marks m
ON m.profile_id = n.profile_id AND m.date = n.date
WHERE n.profile_id=%s
ORDER BY n.date DESC
LIMIT %s
""",
(pid, limit),
)
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}")
@ -228,6 +308,155 @@ def import_history(x_profile_id: Optional[str]=Header(default=None), session: di
return [r2d(r) for r in cur.fetchall()]
@router.get("/items")
def list_nutrition_items(
date: Optional[str] = None,
limit: int = 200,
x_profile_id: Optional[str] = Header(default=None),
session: dict = Depends(require_auth),
):
pid = get_pid(x_profile_id)
with get_db() as conn:
cur = get_cursor(conn)
if date:
cur.execute(
"""
SELECT i.*, f.name_de AS food_name_de, f.bls_code, f.catalog_kind
FROM nutrition_items i
LEFT JOIN food_catalog f ON f.id = i.food_id
WHERE i.profile_id=%s AND i.date=%s
ORDER BY i.logged_at NULLS LAST, i.source_name_raw
""",
(pid, date),
)
else:
cur.execute(
"""
SELECT i.*, f.name_de AS food_name_de, f.bls_code, f.catalog_kind
FROM nutrition_items i
LEFT JOIN food_catalog f ON f.id = i.food_id
WHERE i.profile_id=%s
ORDER BY i.date DESC, i.logged_at NULLS LAST
LIMIT %s
""",
(pid, min(limit, 500)),
)
return [r2d(r) for r in cur.fetchall()]
@router.get("/unmapped")
def list_unmapped_foods(
x_profile_id: Optional[str] = Header(default=None),
session: dict = Depends(require_auth),
):
pid = get_pid(x_profile_id)
with get_db() as conn:
cur = get_cursor(conn)
cur.execute(
"""
SELECT source_name_raw, source_name_normalized,
COUNT(*) AS count, MIN(date) AS first_date, MAX(date) AS last_date
FROM nutrition_items
WHERE profile_id=%s AND food_id IS NULL
GROUP BY source_name_raw, source_name_normalized
ORDER BY count DESC, source_name_normalized
""",
(pid,),
)
return [r2d(r) for r in cur.fetchall()]
@router.post("/import-conflicts/resolve")
def resolve_import_conflicts(
body: dict,
x_profile_id: Optional[str] = Header(default=None),
session: dict = Depends(require_auth),
):
from data_layer.nutrition_items import (
apply_nutrition_day_macros,
compute_day_macro_sums,
resolve_choice_macros,
)
pid = get_pid(x_profile_id)
decisions = body.get("decisions") or []
applied = 0
with get_db() as conn:
cur = get_cursor(conn)
for dec in decisions:
day = dec.get("date")
choice = dec.get("choice")
if not day or not choice:
continue
sums = compute_day_macro_sums(cur, pid, day)
if not sums.get("existing") and choice == "existing":
continue
macros, origin = resolve_choice_macros(sums, choice)
apply_nutrition_day_macros(
cur, pid, day, macros, macro_origin=origin, source="csv", confirm=True,
)
applied += 1
return {"applied": applied}
@router.put("/days/{day}/mark")
def upsert_day_mark(
day: str,
body: dict,
x_profile_id: Optional[str] = Header(default=None),
session: dict = Depends(require_auth),
):
pid = get_pid(x_profile_id)
mark_type = (body or {}).get("mark_type")
note = (body or {}).get("note")
if mark_type not in ("fasting", "incomplete"):
raise HTTPException(400, "mark_type muss fasting oder incomplete sein")
with get_db() as conn:
cur = get_cursor(conn)
cur.execute(
"""
INSERT INTO nutrition_day_marks (profile_id, date, mark_type, note, source, updated_at)
VALUES (%s, %s, %s, %s, 'manual', NOW())
ON CONFLICT (profile_id, date)
DO UPDATE SET mark_type = EXCLUDED.mark_type, note = EXCLUDED.note, updated_at = NOW()
RETURNING *
""",
(pid, day, mark_type, note),
)
return r2d(cur.fetchone())
@router.delete("/days/{day}/mark")
def delete_day_mark(
day: str,
x_profile_id: Optional[str] = Header(default=None),
session: dict = Depends(require_auth),
):
pid = get_pid(x_profile_id)
with get_db() as conn:
cur = get_cursor(conn)
cur.execute(
"DELETE FROM nutrition_day_marks WHERE profile_id=%s AND date=%s",
(pid, day),
)
return {"ok": True}
@router.get("/marks")
def list_day_marks(
x_profile_id: Optional[str] = Header(default=None),
session: dict = Depends(require_auth),
):
pid = get_pid(x_profile_id)
with get_db() as conn:
cur = get_cursor(conn)
cur.execute(
"SELECT * FROM nutrition_day_marks WHERE profile_id=%s ORDER BY date DESC",
(pid,),
)
return [r2d(r) for r in cur.fetchall()]
@router.put("/{entry_id}")
def update_nutrition(entry_id: str, kcal: float, protein_g: float, fat_g: float, carbs_g: float,
x_profile_id: Optional[str]=Header(default=None), session: dict=Depends(require_auth)):
@ -242,7 +471,7 @@ def update_nutrition(entry_id: str, kcal: float, protein_g: float, fat_g: float,
cur.execute("""
UPDATE nutrition_log
SET kcal=%s, protein_g=%s, fat_g=%s, carbs_g=%s
SET kcal=%s, protein_g=%s, fat_g=%s, carbs_g=%s, source='manual', macro_origin='manual'
WHERE id=%s AND profile_id=%s
""", (round(kcal,1), round(protein_g,1), round(fat_g,1), round(carbs_g,1), entry_id, pid))

View File

@ -109,9 +109,17 @@ def update_profile(pid: str, p: ProfileUpdate, session=Depends(require_auth)):
data["verification_expires"] = None
nullable_keys = {"goal_weight", "goal_bf_pct", "dob"}
allowed_nutrition_policy = {
"prompt", "overwrite_catalog", "overwrite_fddb", "keep_existing",
}
for k, v in patch.items():
if k == "email":
continue
if k == "nutrition_import_conflict_policy":
if v not in allowed_nutrition_policy:
raise HTTPException(400, "Ungültige Import-Policy")
data[k] = v
continue
if v is None and k in nullable_keys:
data[k] = None
elif v is not None:

View File

@ -0,0 +1,110 @@
"""Feature-Enforcement für Legacy Activity CSV-Import (#37)."""
import asyncio
from unittest.mock import AsyncMock, patch
import pytest
from fastapi import HTTPException
from routers.activity import import_activity_csv
def test_import_activity_csv_blocks_when_limit_reached():
upload = AsyncMock()
upload.read = AsyncMock(return_value=b"Workout Type,Start\n")
with patch("routers.activity.get_pid", return_value="profile-1"), patch(
"routers.activity.check_feature_access",
return_value={
"allowed": False,
"reason": "limit_exceeded",
"used": 30,
"limit": 30,
},
), patch("routers.activity.log_feature_usage"):
with pytest.raises(HTTPException) as exc:
asyncio.run(
import_activity_csv(
file=upload,
x_profile_id=None,
session={"profile_id": "profile-1"},
)
)
assert exc.value.status_code == 403
def test_import_activity_csv_increments_usage_per_insert(monkeypatch):
upload = AsyncMock()
upload.read = AsyncMock(
return_value=(
"Workout Type,Start,Duration,Aktive Energie (kJ),Ruheeinträge (kJ),"
"Durchschn. Herzfrequenz (count/min),Max. Herzfrequenz (count/min),Distanz (km),End\n"
"Running,2026-07-22 10:00:00 +0200,0:45:00,1000,500,140,160,5.0,\n"
).encode("utf-8")
)
increments = []
class FakeCursor:
def execute(self, *args, **kwargs):
return None
def fetchone(self):
return None
class FakeConn:
def __enter__(self):
return self
def __exit__(self, *args):
return False
fake_cur = FakeCursor()
monkeypatch.setattr("routers.activity.get_pid", lambda _h: "profile-1")
monkeypatch.setattr(
"routers.activity.check_feature_access",
lambda *_a, **_k: {"allowed": True, "reason": "ok", "used": 0, "limit": 100},
)
monkeypatch.setattr("routers.activity.log_feature_usage", lambda *_a, **_k: None)
monkeypatch.setattr("routers.activity.get_db", lambda: FakeConn())
monkeypatch.setattr("routers.activity.get_cursor", lambda _c: fake_cur)
monkeypatch.setattr(
"routers.activity.normalize_activity_start",
lambda _s: ("2026-07-22", "10:00:00"),
)
monkeypatch.setattr(
"routers.activity.get_training_type_for_activity",
lambda *_a, **_k: (1, "cardio", None),
)
monkeypatch.setattr(
"routers.activity.find_activity_duplicate_id",
lambda *_a, **_k: None,
)
monkeypatch.setattr(
"routers.activity.new_activity_id",
lambda: "new-id",
)
monkeypatch.setattr(
"routers.activity.insert_activity_csv_minimal",
lambda *_a, **_k: None,
)
monkeypatch.setattr(
"routers.activity.run_activity_post_write_hooks_import",
lambda *_a, **_k: None,
)
monkeypatch.setattr(
"routers.activity.increment_feature_usage",
lambda _pid, feature: increments.append(feature),
)
result = asyncio.run(
import_activity_csv(
file=upload,
x_profile_id=None,
session={"profile_id": "profile-1"},
)
)
assert result["inserted"] == 1
assert increments == ["activity_entries"]

View File

@ -0,0 +1,65 @@
import time
from io import BytesIO
from openpyxl import Workbook
from bls.import_service import should_persist_value
from bls.jobs import create_and_check, get_job
from bls.parser import parse_components_xlsx, parse_foods_xlsx
def _xlsx(rows):
wb = Workbook()
ws = wb.active
for row in rows:
ws.append(row)
buf = BytesIO()
wb.save(buf)
return buf.getvalue()
def test_parse_components_dynamic():
data = _xlsx([
["Code", "Name_DE", "Name_EN", "Einheit"],
["ENERCC", "Energie", "Energy", "kcal/100g"],
["NA", "Natrium", "Sodium", "mg/100g"],
])
attrs = parse_components_xlsx(data)
keys = {a["attr_key"] for a in attrs}
assert "ENERCC" in keys
assert "NA" in keys
def test_parse_foods_keeps_bls_code():
data = _xlsx([
["BLS Code", "Name", "Food name", "ENERCC Energie [kcal/100g]", "ENERCC Herkunft", "ENERCC Referenz"],
["C131000", "Hafer roh", "Oats raw", 350, "Analyse", "MRI"],
])
parsed = parse_foods_xlsx(data)
assert parsed["foods"][0]["bls_code"] == "C131000"
assert parsed["foods"][0]["name_de"] == "Hafer roh"
vals = {v["attr_key"]: v["value_num"] for v in parsed["foods"][0]["values"]}
assert vals.get("ENERCC") == 350
def test_persist_only_numeric_or_trace():
assert should_persist_value({"value_num": 1.2, "is_trace": False})
assert should_persist_value({"value_num": None, "is_trace": True})
assert not should_persist_value({"value_num": None, "is_trace": False})
def test_import_job_check_does_not_need_http():
data = _xlsx([
["BLS Code", "Name", "Food name", "ENERCC Energie [kcal/100g]", "ENERCC Herkunft", "ENERCC Referenz"],
["C131000", "Hafer roh", "Oats raw", 350, "Analyse", "MRI"],
])
job_id = create_and_check("foods", data)
job = None
for _ in range(80):
job = get_job(job_id)
if job and job["status"] in ("checked", "error"):
break
time.sleep(0.05)
assert job is not None
assert job["status"] == "checked", job.get("error")
assert job["check"]["foods"] == 1

View File

@ -0,0 +1,26 @@
"""Tests für CSV-Vorlagen-Validierung (#71)."""
from csv_parser.template_validator import validate_csv_template
def test_validate_csv_template_rejects_invalid_row_processing():
report = validate_csv_template(
"nutrition",
{"Datum": "date", "kcal": "kcal"},
None,
{"group_by": ["date"], "aggregates": {"kcal": "not_an_op"}},
["Datum", "kcal"],
)
assert report["valid"] is False
assert any(e.get("code") == "invalid_import_row_processing" for e in report["errors"])
def test_validate_csv_template_accepts_nutrition_aggregation():
report = validate_csv_template(
"nutrition",
{"Datum": "date", "kcal": "kcal", "protein": "protein_g"},
None,
{"group_by": ["date"], "aggregates": {"kcal": "sum", "protein_g": "sum"}},
["Datum", "kcal", "protein"],
)
assert report["valid"] is True

View File

@ -0,0 +1,29 @@
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
def test_normalize_strips_leading_quantity():
assert normalize_food_name("50 g Hähnchen") == "hähnchen"
assert normalize_food_name(" Vollmilch 3,5% ") == "vollmilch 3.5%"
def test_parse_quantity_g():
assert parse_quantity_g("150 g") == 150.0
assert parse_quantity_g("150") == 150.0
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})

View File

@ -7,9 +7,9 @@ Semantic Versioning: MAJOR.MINOR.PATCH
- PATCH: Bugfix, kleine Änderung, Refactor
"""
APP_VERSION = "0.9t"
BUILD_DATE = "2026-04-20"
DB_SCHEMA_VERSION = "20260409c" # 048/049 vitals_baseline.source csv + SAVEPOINT Import
APP_VERSION = "0.9v"
BUILD_DATE = "2026-09-12"
DB_SCHEMA_VERSION = "20260912" # 062 BLS catalog + nutrition items/marks
MODULE_VERSIONS = {
"auth": "1.2.0",
@ -19,8 +19,9 @@ MODULE_VERSIONS = {
"weight": "1.0.3",
"circumference": "1.0.1",
"caliper": "1.0.1",
"activity": "1.2.0", # GET /activity: optional days= window + limit
"nutrition": "1.0.2",
"activity": "1.2.1", # Legacy CSV import: activity_entries feature enforcement
"nutrition": "1.1.0", # BLS mapping, items, day marks, import policy
"bls": "1.0.1",
"photos": "1.0.0",
"insights": "1.3.0",
"prompts": "1.1.0",
@ -31,11 +32,30 @@ MODULE_VERSIONS = {
"membership": "2.1.0",
"workflow": "0.7.0", # Part 3: Inline Prompts (reference + inline mode)
"app_dashboard": "1.17.1", # history_overview_viz: Bereichs-Kacheln einzeln per show_section_*
"csv_import": "0.3.2", # Import-Fehler: enrich_row_error / freundlichere 500-Hinweise
"admin_csv_templates": "0.3.0", # POST /validate + Speichern nur bei valid (422 + warnings in Response)
"csv_import": "0.4.0", # Mapping validation on copy/import; validate endpoint; error_details UI
"admin_csv_templates": "0.3.1", # Format check includes import_row_processing parity
}
CHANGELOG = [
{
"version": "0.9v",
"date": "2026-09-12",
"changes": [
"BLS 4.0 Stammdaten (dynamische Attribute, Upsert über bls_code)",
"Lernendes FDDB-Mapping ohne KI, änder- und löschbar",
"Optionale nutrition_items, Import-Policy, Fasten-/Lücken-Marken",
"BLS-Import als Hintergrundjob (kein Proxy-504)",
],
},
{
"version": "0.9u",
"date": "2026-07-24",
"changes": [
"Gitea #37: Activity legacy CSV import — activity_entries feature enforcement + UsageBadge UI",
"Gitea #38: Nutrition FDDB import — UsageBadge + deaktivierte Import-Zone bei Limit",
"Gitea #71: Universal CSV — Dry-Run/Format-Check Parität import_row_processing; Mapping-Validierung bei Copy/Import; strukturierte error_details in Nutzer-UI",
],
},
{
"version": "0.9t",
"date": "2026-04-20",

View File

@ -26,7 +26,7 @@
|---------|--------|
| Hauptnavigation | `frontend/src/config/appNav.js` (`getMainNavItems`) |
| Active-State Bottom + Sidebar | `frontend/src/App.jsx` (`navItemActive`), `frontend/src/components/DesktopSidebar.jsx` |
| Admin Shell & Routing | `frontend/src/layouts/AdminShell.jsx`, `frontend/src/layouts/RequireAdmin.jsx`, `frontend/src/config/adminNav.js` (`ADMIN_GROUPS`, Hubs) |
| Admin Shell & Routing | `frontend/src/layouts/AdminShell.jsx`, `frontend/src/layouts/RequireAdmin.jsx`, `frontend/src/config/adminNav.js` (`ADMIN_GROUPS`, Hubs; Gruppe **Ernährung**: BLS-Import, Katalog, Attribute, FDDB-Mappings) |
| Admin-Seiten | `frontend/src/pages/AdminHomePage.jsx`, `AdminGroupHubPage.jsx`, `AdminUsersPage.jsx`, `AdminSystemPage.jsx`, … |
| Einstellungen Profil | `frontend/src/pages/SettingsPage.jsx`, `.settings-page__field` in `app.css` |
| KI-Analyse Layout | `frontend/src/pages/Analysis.jsx` + `.analysis-split*` in `app.css` |

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@ -0,0 +1,25 @@
## Ziel
Verlässliche Lebensmittel-Stammdaten (BLS 4.0, frei) plus lernendes FDDB-Mapping. Tagesmakros bleiben First Class.
## Umsetzung (develop)
- Migration 062: Katalog, dynamische Attribute, Mappings, `nutrition_items`, Tages-Rollup, Fasten-/Lücken-Marken, Import-Policy
- Admin-Gruppe Ernährung, Nutzer-Tab Zuordnen, Settings-Policy, Initialimport-Checkbox
- Mapping ohne KI, dauerhaft, änder- und löschbar
- BLS-Code bleibt stabile Identität
## Specs
- `.claude/docs/functional/BLS_FOOD_REFERENCE.md`
- `.claude/docs/technical/BLS_FOOD_REFERENCE.md`
- `docs/issues/issue-bls-food-mapping.md`
## Folge
Gitea #75 (Zucker/Ballaststoffe/Qualität, Platzhalter Mikros + Esszeitpunkte)
## Tests
- Unit: `backend/tests/test_food_mapping.py`, `backend/tests/test_bls_parser.py`
- Playwright: Ernährung-Tabs, Import-Checkbox, Settings-Policy, API unmapped/marks/bls-Suche

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@ -0,0 +1,16 @@
# BLS-Stammdaten, FDDB-Mapping, Item-Tagebuch
**Status:** in Umsetzung · **Gitea:** [#106](http://192.168.2.144:3000/Lars/mitai-jinkendo/issues/106) · **Folge:** #75 (Zucker/Ballaststoffe/Qualität)
## Ziel
Verlässliche Lebensmittel-Stammdaten (BLS 4.0 + manuelle Erweiterung), lernendes Mapping aus FDDB, optionale Item-Ebene. Tagesmakros bleiben ohne Katalog nutzbar.
## Abnahme Phase 1
- BLS-XLSX-Import (Dry-Run + Apply), Codes bleiben erhalten
- Manuelle Foods gekennzeichnet
- Mapping: Lookup, Bestätigen, Ändern, Löschen; keine KI
- FDDB-Import speichert Zeilen; Makro-Konflikt laut Policy
- Fasten-/Lücken-Marken unabhängig vom Import
- Einzelerfassung nur Makros unverändert

View File

@ -7,10 +7,10 @@ server {
proxy_pass http://backend:8000/api/;
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
client_max_body_size 20M;
proxy_read_timeout 300s;
client_max_body_size 50M;
proxy_read_timeout 600s;
proxy_connect_timeout 60s;
proxy_send_timeout 60s;
proxy_send_timeout 600s;
}
location / {

View File

@ -57,6 +57,10 @@ import CustomGoalsPage from './pages/CustomGoalsPage'
import UniversalCsvImportPage from './pages/UniversalCsvImportPage'
import AdminCsvTemplatesPage from './pages/AdminCsvTemplatesPage'
import AdminCsvTemplateEditorPage from './pages/AdminCsvTemplateEditorPage'
import AdminBlsImportPage from './pages/AdminBlsImportPage'
import AdminBlsFoodsPage from './pages/AdminBlsFoodsPage'
import AdminFoodMappingsPage from './pages/AdminFoodMappingsPage'
import AdminFoodAttributesPage from './pages/AdminFoodAttributesPage'
import WorkflowEditorPage from './pages/WorkflowEditorPage'
import DesktopSidebar from './components/DesktopSidebar'
import { getMainNavItems } from './config/appNav'
@ -267,6 +271,10 @@ function AppShell() {
<Route path="reference-value-types" element={<AdminReferenceValueTypesPage/>}/>
<Route path="csv-templates" element={<AdminCsvTemplatesPage />} />
<Route path="csv-templates/:id" element={<AdminCsvTemplateEditorPage />} />
<Route path="bls-import" element={<AdminBlsImportPage />} />
<Route path="bls-foods" element={<AdminBlsFoodsPage />} />
<Route path="food-attributes" element={<AdminFoodAttributesPage />} />
<Route path="food-mappings" element={<AdminFoodMappingsPage />} />
</Route>
</Route>
<Route path="/workflow-editor/:id" element={<WorkflowEditorPage/>}/>

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@ -0,0 +1,76 @@
/**
* Strukturierte Zeilenfehler aus Universal-CSV-Import (error_details mit hint/code).
*/
export default function CsvImportErrorDetails({ errors, title, defaultOpen = true, maxVisible = 20 }) {
if (!errors?.length) return null
const shown = errors.slice(0, maxVisible)
const rest = errors.length - shown.length
return (
<details
className="card"
style={{ marginBottom: 16, padding: 16, cursor: 'pointer' }}
open={defaultOpen}
>
<summary style={{ fontWeight: 600, color: 'var(--text1)' }}>
{title || `Zeilenfehler (${errors.length})`}
</summary>
<ul
style={{
margin: '12px 0 0 0',
padding: 0,
listStyle: 'none',
fontSize: 13,
lineHeight: 1.5,
}}
>
{shown.map((err, i) => {
const row = err.row ?? err.row_index
const message = err.error ?? err.message ?? (typeof err === 'string' ? err : JSON.stringify(err))
return (
<li
key={i}
style={{
padding: '10px 12px',
marginBottom: 8,
background: 'var(--surface2)',
borderRadius: 8,
borderLeft: '3px solid var(--danger)',
}}
>
<div style={{ color: 'var(--text1)' }}>
{row != null && (
<strong style={{ marginRight: 6 }}>Zeile {row}:</strong>
)}
{message}
{err.code && (
<code
style={{
marginLeft: 8,
fontSize: 11,
color: 'var(--text3)',
background: 'var(--surface)',
padding: '1px 6px',
borderRadius: 4,
}}
>
{err.code}
</code>
)}
</div>
{err.hint && (
<div style={{ marginTop: 6, fontSize: 12, color: 'var(--text2)' }}>{err.hint}</div>
)}
</li>
)
})}
</ul>
{rest > 0 && (
<p style={{ fontSize: 12, color: 'var(--text3)', margin: '8px 0 0' }}>
und {rest} weitere Fehler (Details in der Import-Historie).
</p>
)}
</details>
)
}

View File

@ -0,0 +1,144 @@
import { useEffect, useState } from 'react'
import { api } from '../utils/api'
export default function NutritionFoodMap({ onChanged }) {
const [unmapped, setUnmapped] = useState([])
const [learned, setLearned] = useState([])
const [error, setError] = useState(null)
const [query, setQuery] = useState({})
const [hits, setHits] = useState({})
const [saving, setSaving] = useState(null)
const load = async () => {
try {
const [u, m] = await Promise.all([api.listUnmappedFoods(), api.listMyFoodMappings()])
setUnmapped(u)
setLearned(m)
} catch (e) {
setError(e.message)
}
}
useEffect(() => { load() }, [])
const search = async (key, q) => {
setQuery((s) => ({ ...s, [key]: q }))
if (!q || q.length < 2) {
setHits((s) => ({ ...s, [key]: [] }))
return
}
try {
const rows = await api.searchBlsFoods(q)
setHits((s) => ({ ...s, [key]: rows }))
} catch (e) {
setError(e.message)
}
}
const assign = async (sourceName, foodId, key) => {
setSaving(key)
setError(null)
try {
await api.upsertMyFoodMapping({ source_name: sourceName, food_id: foodId })
setHits((s) => ({ ...s, [key]: [] }))
await load()
onChanged?.()
} catch (e) {
setError(e.message)
} finally {
setSaving(null)
}
}
const remove = async (id) => {
if (!confirm('Zuordnung wirklich löschen?')) return
try {
await api.deleteMyFoodMapping(id)
await load()
onChanged?.()
} catch (e) {
setError(e.message)
}
}
return (
<div className="card section-gap">
<div className="card-title">Lebensmittel zuordnen</div>
<p style={{ fontSize: 13, color: 'var(--text2)', lineHeight: 1.6, marginBottom: 12 }}>
Einmal bestätigt, bleibt die Zuordnung erhalten und gilt für spätere Importe.
Du kannst sie jederzeit ändern oder löschen. Keine automatische KI-Zuordnung.
</p>
{error && <div style={{ color: 'var(--danger)', fontSize: 13, marginBottom: 10 }}>{error}</div>}
<h3 style={{ fontSize: 14, margin: '12px 0 8px' }}>Offen ({unmapped.length})</h3>
{unmapped.length === 0 && <p className="muted">Keine ungemappten Bezeichner.</p>}
{unmapped.map((u) => {
const key = u.source_name_normalized
return (
<div key={key} style={{ borderTop: '1px solid var(--border)', padding: '10px 0' }}>
<div style={{ fontWeight: 600 }}>{u.source_name_raw}</div>
<div style={{ fontSize: 12, color: 'var(--text3)' }}>
{u.count}× · {u.first_date} {u.last_date}
</div>
<input
className="form-input"
style={{ marginTop: 6 }}
placeholder="BLS-Code oder Name suchen…"
value={query[key] || ''}
onChange={(e) => search(key, e.target.value)}
/>
{(hits[key] || []).map((h) => (
<button
key={h.id}
type="button"
className="btn btn-secondary"
style={{ marginTop: 6, marginRight: 6 }}
disabled={saving === key}
onClick={() => assign(u.source_name_raw, h.id, key)}
>
{h.bls_code ? `${h.bls_code} · ` : ''}{h.name_de}
{h.catalog_kind !== 'official_bls' ? ' (manuell)' : ''}
</button>
))}
</div>
)
})}
<h3 style={{ fontSize: 14, margin: '20px 0 8px' }}>Gelernt ({learned.length})</h3>
{learned.map((m) => (
<div key={m.id} style={{ display: 'flex', justifyContent: 'space-between', gap: 8, padding: '8px 0', borderTop: '1px solid var(--border)' }}>
<div>
<div style={{ fontWeight: 500 }}>{m.source_name_raw}</div>
<div style={{ fontSize: 12, color: 'var(--text3)' }}>
{m.bls_code ? `${m.bls_code} · ` : ''}{m.food_name_de}
{m.catalog_kind !== 'official_bls' ? ' (manuell)' : ''}
</div>
</div>
<button type="button" className="btn btn-secondary" onClick={() => remove(m.id)}>Löschen</button>
</div>
))}
</div>
)
}
export function DayMarkButtons({ date, markType, onChanged }) {
const setMark = async (type) => {
try {
if (markType === type) await api.deleteNutritionDayMark(date)
else await api.putNutritionDayMark(date, { mark_type: type })
onChanged?.()
} catch (e) {
alert(e.message)
}
}
return (
<span style={{ display: 'inline-flex', gap: 4 }}>
<button type="button" className="btn btn-secondary" style={{ fontSize: 11, padding: '4px 8px' }} onClick={() => setMark('fasting')}>
{markType === 'fasting' ? '✓ Fasten' : 'Fasten'}
</button>
<button type="button" className="btn btn-secondary" style={{ fontSize: 11, padding: '4px 8px' }} onClick={() => setMark('incomplete')}>
{markType === 'incomplete' ? '✓ Lücke' : 'Lücke'}
</button>
</span>
)
}

View File

@ -115,6 +115,33 @@ export const ADMIN_GROUPS = [
},
],
},
{
id: 'nutrition',
label: 'Ernährung',
description: 'BLS-Stammdaten, Attribute und FDDB-Mappings.',
items: [
{
to: '/admin/bls-import',
label: 'BLS importieren',
description: 'Offizielle BLS-4.0-XLSX (Components + Daten).',
},
{
to: '/admin/bls-foods',
label: 'Lebensmittelkatalog',
description: 'Suche inkl. BLS-Code, manuelle Einträge.',
},
{
to: '/admin/food-attributes',
label: 'Stoffe & Attribute',
description: 'BLS-Komponenten und Erweiterungen (Histamin, Gluten).',
},
{
to: '/admin/food-mappings',
label: 'FDDB-Mappings',
description: 'Globale Standardzuordnungen und Coverage.',
},
],
},
{
id: 'system',
label: 'Basiseinstellungen',

View File

@ -364,13 +364,15 @@ function SessionMetricsFields({ schema, values, setValues, metrics }) {
}
// Import Panel
function ImportPanel({ onImported }) {
function ImportPanel({ onImported, usage = null }) {
const fileRef = useRef()
const [status, setStatus] = useState(null)
const [error, setError] = useState(null)
const [dragging, setDragging] = useState(false)
const atLimit = usage && !usage.allowed
const runImport = async (file) => {
if (atLimit) return
setStatus('loading'); setError(null)
try {
const result = await api.importActivityCsv(file)
@ -382,24 +384,29 @@ function ImportPanel({ onImported }) {
return (
<div className="card section-gap">
<div className="card-title">📥 Apple Health Import</div>
<div className="card-title badge-container-right">
<span>📥 Apple Health Import</span>
{usage && <UsageBadge {...usage} />}
</div>
<p style={{fontSize:13,color:'var(--text2)',marginBottom:10,lineHeight:1.6}}>
<strong>Health Auto Export App</strong> Workouts exportieren CSV hier hochladen.<br/>
Nur die <em>Workouts-csv</em> Datei wird benötigt (nicht die Detaildateien).
</p>
<input ref={fileRef} type="file" accept=".csv" style={{display:'none'}}
disabled={atLimit}
onChange={e=>{ const f=e.target.files[0]; if(f) runImport(f); e.target.value='' }}/>
<div
onDragOver={e=>{e.preventDefault();setDragging(true)}}
onDragOver={e=>{ if(!atLimit){ e.preventDefault(); setDragging(true) }}}
onDragLeave={()=>setDragging(false)}
onDrop={e=>{e.preventDefault();setDragging(false);const f=e.dataTransfer.files[0];if(f)runImport(f)}}
onClick={()=>fileRef.current.click()}
onDrop={e=>{ e.preventDefault(); setDragging(false); if(atLimit) return; const f=e.dataTransfer.files[0]; if(f) runImport(f) }}
onClick={()=>{ if(!atLimit) fileRef.current?.click() }}
title={atLimit ? `Limit erreicht (${usage.used}/${usage.limit})` : ''}
style={{border:`2px dashed ${dragging?'var(--accent)':'var(--border2)'}`,borderRadius:10,
padding:'20px 16px',textAlign:'center',background:dragging?'var(--accent-light)':'var(--surface2)',
cursor:'pointer',transition:'all 0.15s'}}>
cursor:atLimit?'not-allowed':'pointer',opacity:atLimit?0.65:1,transition:'all 0.15s'}}>
<Upload size={24} style={{color:dragging?'var(--accent)':'var(--text3)',marginBottom:6}}/>
<div style={{fontSize:13,color:dragging?'var(--accent-dark)':'var(--text2)'}}>
{dragging?'Datei loslassen…':'CSV hierher ziehen oder tippen'}
{atLimit ? '🔒 Limit erreicht — Import nicht möglich' : dragging ? 'Datei loslassen…' : 'CSV hierher ziehen oder tippen'}
</div>
</div>
{status==='loading' && (
@ -945,7 +952,12 @@ export default function ActivityPage() {
</div>
)}
{tab==='import' && <ImportPanel onImported={load}/>}
{tab==='import' && (
<ImportPanel
usage={activityUsage}
onImported={() => { load(); loadUsage() }}
/>
)}
{tab==='categorize' && (
<div className="card section-gap">

View File

@ -0,0 +1,57 @@
import { useState } from 'react'
import { api } from '../utils/api'
export default function AdminBlsFoodsPage() {
const [q, setQ] = useState('')
const [rows, setRows] = useState([])
const [detail, setDetail] = useState(null)
const [error, setError] = useState(null)
const search = async () => {
try {
setRows(await api.adminBlsFoods(q))
} catch (e) {
setError(e.message)
}
}
return (
<div className="card">
<h1 className="page-title">Lebensmittelkatalog</h1>
{error && <p style={{ color: 'var(--danger)' }}>{error}</p>}
<div className="form-row">
<input className="form-input" value={q} onChange={(e) => setQ(e.target.value)} placeholder="Name oder BLS-Code" />
<button type="button" className="btn btn-primary" onClick={search}>Suchen</button>
</div>
{rows.map((r) => (
<button
key={r.id}
type="button"
className="btn btn-secondary btn-full"
style={{ marginTop: 6, textAlign: 'left' }}
onClick={() => api.adminBlsFoodDetail(r.id).then(setDetail).catch((e) => setError(e.message))}
>
{r.bls_code ? `${r.bls_code} · ` : ''}{r.name_de}
{r.catalog_kind !== 'official_bls' ? ' · manuell' : ''}
</button>
))}
{detail && (
<div style={{ marginTop: 16 }}>
<h3>{detail.bls_code} {detail.name_de}</h3>
<p style={{ fontSize: 12, color: 'var(--text3)' }}>{detail.catalog_kind} · {detail.bls_version || '—'}</p>
<table style={{ width: '100%', fontSize: 12 }}>
<tbody>
{(detail.attributes || []).filter((a) => a.value_num != null || a.is_trace).slice(0, 40).map((a) => (
<tr key={a.attr_key}>
<td>{a.attr_key}</td>
<td>{a.name_de}</td>
<td>{a.is_trace ? 'Spuren' : a.value_num} {a.unit || ''}</td>
</tr>
))}
</tbody>
</table>
</div>
)}
</div>
)
}

View File

@ -0,0 +1,148 @@
import { useEffect, useRef, useState } from 'react'
import { api } from '../utils/api'
function summarizeCheck(kind, check) {
if (!check) return ''
if (kind === 'components') return `${check.attributes ?? 0} Stoffe erkannt`
return `${check.foods ?? 0} Lebensmittel, ${check.attribute_columns ?? 0} Stoffspalten`
}
function sleep(ms) {
return new Promise((resolve) => setTimeout(resolve, ms))
}
async function waitForJob(jobId, doneStatuses, onTick) {
for (;;) {
const job = await api.adminBlsImportJob(jobId)
onTick?.(job)
if (job.status === 'error') {
throw new Error(job.error || 'Import fehlgeschlagen')
}
if (doneStatuses.includes(job.status)) return job
await sleep(1200)
}
}
function FileImportBlock({ label, kind, onImported }) {
const inputRef = useRef(null)
const [file, setFile] = useState(null)
const [job, setJob] = useState(null)
const [error, setError] = useState(null)
const [busy, setBusy] = useState(null)
const checkFile = async (nextFile) => {
setError(null)
setJob(null)
if (!nextFile) return
setBusy('check')
try {
const started = await api.adminBlsImportStart(kind, nextFile)
const done = await waitForJob(started.id, ['checked'], setJob)
setJob(done)
} catch (e) {
setError(e.message)
} finally {
setBusy(null)
}
}
const applyImport = async () => {
if (!job?.id || job.status !== 'checked') return
setBusy('apply')
setError(null)
try {
await api.adminBlsImportApply(job.id)
const done = await waitForJob(job.id, ['done'], setJob)
setJob(done)
onImported?.()
} catch (e) {
setError(e.message)
} finally {
setBusy(null)
}
}
const progress = job?.progress
const result = job?.result
return (
<div className="settings-page__field">
<label className="settings-page__field-label">{label}</label>
<input
ref={inputRef}
type="file"
accept=".xlsx"
disabled={!!busy}
style={{ display: 'none' }}
onChange={(e) => {
const next = e.target.files?.[0] || null
setFile(next)
checkFile(next)
}}
/>
<button
type="button"
className="btn btn-secondary btn-full"
disabled={!!busy}
onClick={() => inputRef.current?.click()}
>
{file ? file.name : 'Datei auswählen'}
</button>
{busy === 'check' && <p style={{ fontSize: 13, color: 'var(--text2)', margin: 0 }}>Prüfe</p>}
{busy === 'apply' && (
<p style={{ fontSize: 13, color: 'var(--text2)', margin: 0 }}>
Importiere{progress?.total ? ` ${progress.current}/${progress.total}` : ''}
</p>
)}
{error && <p style={{ color: 'var(--danger)', margin: 0 }}>{error}</p>}
{job?.status === 'checked' && !error && (
<p style={{ fontSize: 13, color: 'var(--text2)', margin: 0 }}>
Prüfung: {summarizeCheck(kind, job.check)}
</p>
)}
{job?.status === 'done' && result && (
<p style={{ fontSize: 13, color: 'var(--text2)', margin: 0 }}>
{(result.inserted ?? result.foods_inserted) ?? 0} neu · {(result.updated ?? result.foods_updated) ?? 0} aktualisiert
{result.values_written != null ? ` · ${result.values_written} Werte` : ''}
</p>
)}
<button
type="button"
className="btn btn-primary btn-full"
disabled={job?.status !== 'checked' || !!error || !!busy}
onClick={applyImport}
>
{job?.status === 'done' ? 'Importiert' : 'Importieren'}
</button>
</div>
)
}
export default function AdminBlsImportPage() {
const [status, setStatus] = useState(null)
const [error, setError] = useState(null)
const load = () => {
api.adminBlsStatus().then(setStatus).catch((e) => setError(e.message))
}
useEffect(() => { load() }, [])
return (
<div className="card">
<h1 className="page-title">BLS 4.0 importieren</h1>
<p style={{ fontSize: 13, color: 'var(--text2)', lineHeight: 1.6 }}>
Offizielle Dateien von blsdb.de (frei verfügbar, MRI). Codes bleiben erhalten.
Datei wählen prüft automatisch. Danach Importieren. Zuerst Components, dann Daten.
</p>
{status && (
<p style={{ fontSize: 13 }}>
{status.official_foods} offizielle Lebensmittel · {status.official_attributes} Stoffe ·
{status.manual_foods} manuell · {status.source}
</p>
)}
{error && <p style={{ color: 'var(--danger)' }}>{error}</p>}
<FileImportBlock label="Components XLSX" kind="components" onImported={load} />
<FileImportBlock label="Daten XLSX" kind="foods" onImported={load} />
</div>
)
}

View File

@ -122,6 +122,68 @@ function buildImportRowProcessingSimple(modFields, fm, groupBy, mode, multiRowPo
return out
}
/** Gleiche Logik wie beim Speichern — für Formatprüfung und Create/Update. */
function resolveEditorImportRowProcessing({
aggregateSleepImport,
rowAggUseCustom,
rowAggIrregular,
rowAggJsonText,
rowAggGroupBy,
rowAggMode,
rowAggMultiRowPolicy,
rowAggDedupeIdentical,
modFields,
fieldMappings,
assignedTargets,
}) {
if (aggregateSleepImport || !rowAggUseCustom) {
return { import_row_processing: null, error: null }
}
if (rowAggIrregular) {
try {
const import_row_processing = JSON.parse(rowAggJsonText || '{}')
if (!import_row_processing || typeof import_row_processing !== 'object') {
return { import_row_processing: null, error: 'Zeilenaggregation: ungültiges JSON.' }
}
const gb = import_row_processing.group_by
if (!Array.isArray(gb) || !gb.length) {
return {
import_row_processing: null,
error: 'Zeilenaggregation (JSON): „group_by“ muss eine nicht-leere Liste sein.',
}
}
return { import_row_processing, error: null }
} catch {
return { import_row_processing: null, error: 'Zeilenaggregation: ungültiges JSON.' }
}
}
if (!rowAggGroupBy.length) {
return { import_row_processing: null, error: 'Zeilenaggregation: mindestens ein Schlüsselfeld auswählen.' }
}
if (!rowAggMode) {
return { import_row_processing: null, error: 'Zeilenaggregation: eine Funktion wählen (Summe, Mittelwert, …).' }
}
for (const g of rowAggGroupBy) {
if (!assignedTargets.has(g)) {
return {
import_row_processing: null,
error: `Zeilenaggregation: Schlüsselfeld „${g}“ muss einer CSV-Spalte zugeordnet sein.`,
}
}
}
return {
import_row_processing: buildImportRowProcessingSimple(
modFields,
fieldMappings,
rowAggGroupBy,
rowAggMode,
rowAggMultiRowPolicy,
rowAggDedupeIdentical,
),
error: null,
}
}
/** Erlaubt Eingaben wie 1,03 oder 1.03 während des Tippens; Finale normalisiert bei Blur/Speichern. */
function normalizeDecimalInputString(raw) {
let s = String(raw).trim().replace(/\s/g, '')
@ -621,11 +683,28 @@ export default function AdminCsvTemplateEditorPage() {
}
setValidating(true)
try {
const { import_row_processing, error: irpError } = resolveEditorImportRowProcessing({
aggregateSleepImport,
rowAggUseCustom,
rowAggIrregular,
rowAggJsonText,
rowAggGroupBy,
rowAggMode,
rowAggMultiRowPolicy,
rowAggDedupeIdentical,
modFields: modMeta?.fields,
fieldMappings,
assignedTargets,
})
if (irpError) {
setError(irpError)
return
}
const r = await api.adminValidateCsvTemplate({
module,
field_mappings: fieldMappings,
type_conversions: tc,
import_row_processing: null,
import_row_processing,
column_signature: columnSignature.length ? columnSignature : null,
})
setValidationReport(r)
@ -692,44 +771,25 @@ export default function AdminCsvTemplateEditorPage() {
}
let import_row_processing = null
if (!aggregateSleepImport && rowAggUseCustom) {
if (rowAggIrregular) {
try {
import_row_processing = JSON.parse(rowAggJsonText || '{}')
if (!import_row_processing || typeof import_row_processing !== 'object') throw new Error('bad')
} catch {
setError('Zeilenaggregation: ungültiges JSON.')
return
}
const gb = import_row_processing.group_by
if (!Array.isArray(gb) || !gb.length) {
setError('Zeilenaggregation (JSON): „group_by“ muss eine nicht-leere Liste sein.')
return
}
} else {
if (!rowAggGroupBy.length) {
setError('Zeilenaggregation: mindestens ein Schlüsselfeld auswählen.')
return
}
if (!rowAggMode) {
setError('Zeilenaggregation: eine Funktion wählen (Summe, Mittelwert, …).')
return
}
for (const g of rowAggGroupBy) {
if (!assignedTargets.has(g)) {
setError(`Zeilenaggregation: Schlüsselfeld „${g}“ muss einer CSV-Spalte zugeordnet sein.`)
return
}
}
import_row_processing = buildImportRowProcessingSimple(
modMeta?.fields,
fieldMappings,
rowAggGroupBy,
rowAggMode,
rowAggMultiRowPolicy,
rowAggDedupeIdentical,
)
{
const resolved = resolveEditorImportRowProcessing({
aggregateSleepImport,
rowAggUseCustom,
rowAggIrregular,
rowAggJsonText,
rowAggGroupBy,
rowAggMode,
rowAggMultiRowPolicy,
rowAggDedupeIdentical,
modFields: modMeta?.fields,
fieldMappings,
assignedTargets,
})
if (resolved.error) {
setError(resolved.error)
return
}
import_row_processing = resolved.import_row_processing
}
const payload = {
@ -1494,12 +1554,13 @@ export default function AdminCsvTemplateEditorPage() {
{validationReport.valid ? <span style={{ color: 'var(--accent)' }}> speicherfähig</span> : <span style={{ color: 'var(--danger)' }}> Fehler beheben</span>}
</div>
<p style={{ fontSize: 12, color: 'var(--text3)', marginBottom: 10 }}>
Ohne Zeilenaggregations-JSON; vollständige Prüfung inkl. Aggregation beim Speichern. Warnungen blockieren nicht.
Inkl. Zeilenaggregation (wie beim Speichern). Warnungen blockieren nicht.
</p>
{validationReport.errors?.length ? (
<ul style={{ margin: '0 0 12px 1rem', color: 'var(--danger)', fontSize: 14 }}>
{validationReport.errors.map((e, i) => (
<li key={`e-${i}`}>
{e.code ? <code style={{ fontSize: 11, marginRight: 6 }}>{e.code}</code> : null}
{e.message}
{e.hint ? <span style={{ display: 'block', fontSize: 12, color: 'var(--text2)', marginTop: 4 }}>{e.hint}</span> : null}
</li>
@ -1510,6 +1571,7 @@ export default function AdminCsvTemplateEditorPage() {
<ul style={{ margin: '0 0 0 1rem', color: 'var(--text2)', fontSize: 13 }}>
{validationReport.warnings.map((w, i) => (
<li key={`w-${i}`}>
{w.code ? <code style={{ fontSize: 11, marginRight: 6 }}>{w.code}</code> : null}
{w.message}
{w.hint ? <span style={{ display: 'block', fontSize: 12, color: 'var(--text3)', marginTop: 4 }}>{w.hint}</span> : null}
</li>

View File

@ -0,0 +1,44 @@
import { useEffect, useState } from 'react'
import { api } from '../utils/api'
export default function AdminFoodAttributesPage() {
const [rows, setRows] = useState([])
const [form, setForm] = useState({ attr_key: '', name_de: '', unit: '', data_type: 'num_per_100g' })
const [error, setError] = useState(null)
const load = () => api.adminBlsAttributes().then(setRows).catch((e) => setError(e.message))
useEffect(() => { load() }, [])
return (
<div className="card">
<h1 className="page-title">Stoffe & Attribute</h1>
<p style={{ fontSize: 13, color: 'var(--text2)' }}>
Offizielle BLS-Codes kommen aus dem Import. Erweiterungen (Histamin, Gluten, ) hier anlegen ohne Migration.
</p>
{error && <p style={{ color: 'var(--danger)' }}>{error}</p>}
<div className="form-row">
<input className="form-input" placeholder="KEY" value={form.attr_key} onChange={(e) => setForm({ ...form, attr_key: e.target.value })} />
<input className="form-input" placeholder="Name DE" value={form.name_de} onChange={(e) => setForm({ ...form, name_de: e.target.value })} />
<input className="form-input" placeholder="Einheit" value={form.unit} onChange={(e) => setForm({ ...form, unit: e.target.value })} />
<select className="form-input" value={form.data_type} onChange={(e) => setForm({ ...form, data_type: e.target.value })}>
<option value="num_per_100g">Zahl / 100g</option>
<option value="boolean">Ja/Nein</option>
<option value="text">Text</option>
<option value="enum">Auswahl</option>
</select>
<button type="button" className="btn btn-primary" onClick={async () => {
try {
await api.adminCreateBlsAttribute(form)
setForm({ attr_key: '', name_de: '', unit: '', data_type: 'num_per_100g' })
load()
} catch (e) { setError(e.message) }
}}>Anlegen</button>
</div>
{rows.map((r) => (
<div key={r.id} style={{ fontSize: 13, padding: '6px 0', borderTop: '1px solid var(--border)' }}>
<strong>{r.attr_key}</strong> · {r.name_de} · {r.data_type} · {r.origin}
</div>
))}
</div>
)
}

View File

@ -0,0 +1,68 @@
import { useEffect, useState } from 'react'
import { api } from '../utils/api'
export default function AdminFoodMappingsPage() {
const [rows, setRows] = useState([])
const [coverage, setCoverage] = useState(null)
const [name, setName] = useState('')
const [foodQ, setFoodQ] = useState('')
const [hits, setHits] = useState([])
const [foodId, setFoodId] = useState('')
const [error, setError] = useState(null)
const load = () => {
Promise.all([api.adminListFoodMappings(false), api.adminFoodMappingCoverage()])
.then(([m, c]) => { setRows(m); setCoverage(c) })
.catch((e) => setError(e.message))
}
useEffect(() => { load() }, [])
return (
<div className="card">
<h1 className="page-title">FDDBBLS Mappings</h1>
{error && <p style={{ color: 'var(--danger)' }}>{error}</p>}
{coverage && (
<p style={{ fontSize: 13 }}>
{coverage.mapped_items}/{coverage.total_items} Zeilen gemappt ·
{coverage.unmapped_names} ungemappte Namen
</p>
)}
<div className="form-row">
<input className="form-input" placeholder="FDDB-Bezeichner" value={name} onChange={(e) => setName(e.target.value)} />
</div>
<div className="form-row">
<input className="form-input" placeholder="Lebensmittel suchen" value={foodQ} onChange={async (e) => {
setFoodQ(e.target.value)
if (e.target.value.length > 1) setHits(await api.searchBlsFoods(e.target.value))
}} />
</div>
{hits.map((h) => (
<button key={h.id} type="button" className="btn btn-secondary" style={{ margin: 4 }} onClick={() => { setFoodId(h.id); setFoodQ(h.name_de) }}>
{h.bls_code} {h.name_de}
</button>
))}
<button
type="button"
className="btn btn-primary"
disabled={!name || !foodId}
onClick={async () => {
try {
await api.adminCreateFoodMapping({ source_name: name, food_id: foodId })
setName(''); setFoodId(''); setFoodQ(''); load()
} catch (e) { setError(e.message) }
}}
>
Globales Mapping anlegen
</button>
{rows.map((r) => (
<div key={r.id} style={{ display: 'flex', justifyContent: 'space-between', padding: '8px 0', borderTop: '1px solid var(--border)' }}>
<div>
{r.source_name_raw} {r.bls_code} {r.food_name_de}
<div style={{ fontSize: 11, color: 'var(--text3)' }}>{r.profile_id ? 'user' : 'global'}</div>
</div>
<button type="button" className="btn btn-secondary" onClick={async () => { await api.adminDeleteFoodMapping(r.id); load() }}>Löschen</button>
</div>
))}
</div>
)
}

View File

@ -1,5 +1,7 @@
import { useState, useEffect, useRef } from 'react'
import { Upload, CheckCircle, TrendingUp, Info } from 'lucide-react'
import UsageBadge from '../components/UsageBadge'
import NutritionFoodMap, { DayMarkButtons } from '../components/NutritionFoodMap'
import {
LineChart, Line, BarChart, Bar, XAxis, YAxis, Tooltip,
ResponsiveContainer, CartesianGrid, Legend, ReferenceLine, ScatterChart, Scatter
@ -193,6 +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({})
@ -323,9 +368,19 @@ function DataTab({ entries, onUpdate }) {
</div>
{e.source && (
<div style={{fontSize:10, color:'var(--text3)', marginTop:4}}>
Quelle: {e.source}
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>
</>
) : (
<>
@ -433,20 +488,25 @@ function ImportHistory() {
}
// Import Panel
function ImportPanel({ onImported }) {
function ImportPanel({ onImported, usage = null }) {
const fileRef = useRef()
const [status, setStatus] = useState(null)
const [error, setError] = useState(null)
const [dragging,setDragging]= useState(false)
const [tab, setTab] = useState('file') // 'file' | 'paste'
const [pasteText, setPasteText] = useState('')
const [overwrite, setOverwrite] = useState(false)
const [conflicts, setConflicts] = useState([])
const atLimit = usage && !usage.allowed
const runImport = async (file) => {
setStatus('loading'); setError(null)
if (atLimit) return
setStatus('loading'); setError(null); setConflicts([])
try {
const result = await nutritionApi.importCsv(file)
const result = await nutritionApi.importCsv(file, overwrite)
if (result.days_imported === undefined) throw new Error(JSON.stringify(result))
setStatus(result)
setConflicts(result.conflicts || [])
onImported()
} catch(err) {
setError('Import fehlgeschlagen: ' + err.message)
@ -468,7 +528,7 @@ function ImportPanel({ onImported }) {
}
const handlePasteImport = async () => {
if (!pasteText.trim()) return
if (!pasteText.trim() || atLimit) return
const blob = new Blob([pasteText], { type: 'text/csv' })
const file = new File([blob], 'paste.csv', { type: 'text/csv' })
await runImport(file)
@ -476,10 +536,18 @@ function ImportPanel({ onImported }) {
return (
<div className="card section-gap">
<div className="card-title">📥 FDDB CSV Import</div>
<div className="card-title badge-container-right">
<span>📥 FDDB CSV Import</span>
{usage && <UsageBadge {...usage} />}
</div>
<p style={{fontSize:13,color:'var(--text2)',marginBottom:10,lineHeight:1.6}}>
In FDDB: <strong>Mein Tagebuch Exportieren CSV</strong> dann hier importieren.
Zeilen (Name, Menge, Uhrzeit) werden gespeichert, wenn die CSV sie enthält.
</p>
<label style={{display:'flex',alignItems:'center',gap:8,fontSize:13,marginBottom:10}}>
<input type="checkbox" checked={overwrite} onChange={(e)=>setOverwrite(e.target.checked)} />
Vorhandene Tagesmakros überschreiben (Initialimport)
</label>
{/* Tab switcher */}
<div style={{display:'flex',gap:6,marginBottom:12}}>
@ -498,23 +566,26 @@ function ImportPanel({ onImported }) {
<>
{/* Drag & Drop Zone */}
<div
onDragOver={e=>{e.preventDefault();setDragging(true)}}
onDragOver={e=>{ if(!atLimit){ e.preventDefault(); setDragging(true) }}}
onDragLeave={()=>setDragging(false)}
onDrop={handleDrop}
onClick={()=>fileRef.current.click()}
onDrop={e=>{ e.preventDefault(); setDragging(false); if(atLimit) return; handleDrop(e) }}
onClick={()=>{ if(!atLimit) fileRef.current?.click() }}
title={atLimit ? `Limit erreicht (${usage.used}/${usage.limit})` : ''}
style={{
border:`2px dashed ${dragging?'var(--accent)':'var(--border2)'}`,
borderRadius:10, padding:'24px 16px', textAlign:'center',
background: dragging?'var(--accent-light)':'var(--surface2)',
cursor:'pointer', transition:'all 0.15s',
cursor:atLimit?'not-allowed':'pointer', opacity:atLimit?0.65:1, transition:'all 0.15s',
}}>
<Upload size={28} style={{color:dragging?'var(--accent)':'var(--text3)',marginBottom:8}}/>
<div style={{fontSize:14,fontWeight:500,color:dragging?'var(--accent-dark)':'var(--text2)'}}>
{dragging ? 'Datei loslassen…' : 'CSV hierher ziehen oder tippen zum Auswählen'}
{atLimit
? '🔒 Limit erreicht — Import nicht möglich'
: dragging ? 'Datei loslassen…' : 'CSV hierher ziehen oder tippen zum Auswählen'}
</div>
<div style={{fontSize:11,color:'var(--text3)',marginTop:4}}>.csv Dateien</div>
</div>
<input ref={fileRef} type="file" accept=".csv" style={{display:'none'}} onChange={handleFile}/>
<input ref={fileRef} type="file" accept=".csv" style={{display:'none'}} disabled={atLimit} onChange={handleFile}/>
</>
)}
@ -523,14 +594,20 @@ function ImportPanel({ onImported }) {
<textarea
style={{width:'100%',minHeight:120,padding:10,fontFamily:'monospace',fontSize:11,
background:'var(--surface2)',border:'1.5px solid var(--border2)',borderRadius:8,
color:'var(--text1)',resize:'vertical',boxSizing:'border-box'}}
color:'var(--text1)',resize:'vertical',boxSizing:'border-box',
opacity:atLimit?0.65:1}}
placeholder="datum_tag_monat_jahr_stunde_minute;bezeichnung;&#10;13.03.2026 21:54;50 g Hähnchen;..."
value={pasteText}
onChange={e=>setPasteText(e.target.value)}
disabled={atLimit}
/>
<button className="btn btn-primary btn-full" style={{marginTop:8}}
onClick={handlePasteImport} disabled={status==='loading'||!pasteText.trim()}>
{status==='loading'
onClick={handlePasteImport}
disabled={status==='loading'||!pasteText.trim()||atLimit}
title={atLimit ? `Limit erreicht (${usage.used}/${usage.limit})` : ''}>
{atLimit
? '🔒 Limit erreicht'
: status==='loading'
? <><div className="spinner" style={{width:14,height:14}}/> Importiere</>
: <><Upload size={15}/> CSV-Text importieren</>}
</button>
@ -552,7 +629,7 @@ function ImportPanel({ onImported }) {
<div style={{display:'flex',alignItems:'center',gap:6,marginBottom:4}}>
<CheckCircle size={15}/><strong>Import erfolgreich</strong>
</div>
<div>{status.days_imported} Tage importiert · {status.rows_parsed} Einträge verarbeitet</div>
<div>{status.days_imported} Tage · {status.rows_parsed} Zeilen{status.items_written ? ` · ${status.items_written} Items` : ''}</div>
{status.date_range?.from && (
<div style={{fontSize:11,marginTop:2}}>
{dayjs(status.date_range.from).format('DD.MM.YYYY')} {dayjs(status.date_range.to).format('DD.MM.YYYY')}
@ -560,6 +637,45 @@ function ImportPanel({ onImported }) {
)}
</div>
)}
{conflicts.length > 0 && (
<ConflictDialog conflicts={conflicts} onDone={() => { setConflicts([]); onImported() }} />
)}
</div>
)
}
function ConflictDialog({ conflicts, onDone }) {
const [choices, setChoices] = useState({})
const [busy, setBusy] = useState(false)
const setC = (date, choice) => setChoices((s) => ({ ...s, [date]: choice }))
const save = async () => {
setBusy(true)
try {
const decisions = conflicts.map((c) => ({ date: c.date, choice: choices[c.date] || 'existing' }))
await nutritionApi.resolveNutritionConflicts(decisions)
onDone()
} catch (e) {
alert(e.message)
} finally {
setBusy(false)
}
}
return (
<div style={{marginTop:12,padding:12,border:'1px solid var(--border)',borderRadius:8}}>
<strong>Abweichende Tagesmakros</strong>
{conflicts.map((c) => (
<div key={c.date} style={{marginTop:10,fontSize:12}}>
<div>{c.date}</div>
<div>Ist {c.existing?.kcal} · FDDB {c.fddb?.kcal} · Katalog {c.catalog?.kcal} kcal</div>
{['existing','fddb','catalog'].map((k) => (
<label key={k} style={{marginRight:10}}>
<input type="radio" name={`c-${c.date}`} checked={(choices[c.date]||'existing')===k} onChange={()=>setC(c.date,k)} />
{k === 'existing' ? 'behalten' : k === 'fddb' ? 'FDDB' : 'Katalog'}
</label>
))}
</div>
))}
<button type="button" className="btn btn-primary" style={{marginTop:10}} disabled={busy} onClick={save}>Übernehmen</button>
</div>
)
}
@ -781,30 +897,49 @@ export default function NutritionPage() {
const [loading, setLoad] = useState(true)
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 => {
const nutritionFeature = features.find(f => f.feature_id === 'nutrition_entries')
setNutritionUsage(nutritionFeature ?? null)
}).catch(err => console.error('Failed to load usage:', err))
}
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) }
}
useEffect(() => { load() }, [])
useEffect(() => { load(); loadUsage() }, [])
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}}>
@ -814,6 +949,9 @@ export default function NutritionPage() {
<button className={'tab'+(inputTab==='import'?' active':'')} onClick={()=>setInputTab('import')}>
📥 Import
</button>
<button className={'tab'+(inputTab==='map'?' active':'')} onClick={()=>setInputTab('map')}>
Zuordnen{unmappedCount ? ` (${unmappedCount})` : ''}
</button>
</div>
{/* Entry Form */}
@ -822,11 +960,16 @@ export default function NutritionPage() {
{/* Import Panel + History */}
{inputTab==='import' && (
<>
<ImportPanel onImported={() => { load(); setImportHistoryKey(Date.now()) }}/>
<ImportPanel
usage={nutritionUsage}
onImported={() => { load(); loadUsage(); setImportHistoryKey(Date.now()) }}
/>
<ImportHistory key={importHistoryKey}/>
</>
)}
{inputTab==='map' && <NutritionFoodMap onChanged={load} />}
{loading && <div className="empty-state"><div className="spinner"/></div>}
{!loading && !hasData && (

View File

@ -458,6 +458,33 @@ export default function SettingsPage() {
</Link>
</div>
<div className="card section-gap">
<div className="card-title">Ernährungs-Import</div>
<p style={{ fontSize: 13, color: 'var(--text2)', marginBottom: 12, lineHeight: 1.6 }}>
Wenn für einen Tag schon Makros existieren: nachfragen, Katalog-/FDDB-Summe schreiben oder die bestehenden Werte behalten.
Für den einmaligen FDDB-Reimport kannst du auch die Checkbox am Import nutzen.
</p>
<select
className="form-input"
value={activeProfile?.nutrition_import_conflict_policy || 'prompt'}
onChange={async (e) => {
try {
await api.updateActiveProfile({ nutrition_import_conflict_policy: e.target.value })
await refreshProfiles()
setSaved(true)
setTimeout(() => setSaved(false), 2000)
} catch (err) {
setProfileErr(err.message)
}
}}
>
<option value="prompt">Bei Abweichung nachfragen</option>
<option value="overwrite_catalog">Immer Katalog-/BLS-Summe</option>
<option value="overwrite_fddb">Immer FDDB-Rohsumme</option>
<option value="keep_existing">Bestehende Makros behalten</option>
</select>
</div>
{/* Auth actions */}
<div className="card section-gap">
<div className="card-title">🔐 Konto</div>

View File

@ -3,6 +3,7 @@ import { useNavigate } from 'react-router-dom'
import { ArrowLeft, FileSpreadsheet, Loader2, Upload } from 'lucide-react'
import { api } from '../utils/api'
import { csvPreviewTdStyle } from '../utils/csvPreviewCells'
import CsvImportErrorDetails from '../components/CsvImportErrorDetails'
/** Ziele, die der Universal-Executor bereits schreiben kann (ohne manuelle Modul-Wahl). */
const EXECUTOR_READY = new Set([
@ -200,10 +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 ? ` ${extra.join(' · ')}.` : ''),
)
} catch (e) {
setError(e.message || 'Import fehlgeschlagen')
@ -288,29 +293,11 @@ export default function UniversalCsvImportPage() {
)}
{lastImport?.error_details?.length > 0 && (
<details
className="card"
style={{ marginBottom: 16, padding: 16, cursor: 'pointer' }}
open
>
<summary style={{ fontWeight: 600, color: 'var(--text1)' }}>
Zeilenfehler vom letzten Import ({lastImport.error_details.length}) zum Kopieren aufklappen
</summary>
<pre
style={{
marginTop: 12,
fontSize: 12,
overflow: 'auto',
maxHeight: 320,
background: 'var(--surface2)',
padding: 12,
borderRadius: 8,
color: 'var(--text1)',
}}
>
{JSON.stringify(lastImport.error_details, null, 2)}
</pre>
</details>
<CsvImportErrorDetails
errors={lastImport.error_details}
title={`Zeilenfehler vom letzten Import (${lastImport.error_details.length})`}
defaultOpen
/>
)}
<div className="card" style={{ marginBottom: 16, padding: 16 }}>

View File

@ -29,6 +29,13 @@ export function formatFastApiDetail(detail, fallback = '') {
return parts.length ? parts.join(' · ') : fallback || 'Validierungsfehler'
}
if (typeof detail === 'object') {
if (detail.validation?.errors?.length) {
const parts = detail.validation.errors
.map((e) => (e && typeof e === 'object' ? e.message || e.msg || '' : String(e)))
.filter(Boolean)
const prefix = detail.message || 'Vorlage ungültig'
return parts.length ? `${prefix}: ${parts.join(' · ')}` : prefix
}
if (Array.isArray(detail.errors) && detail.errors.length > 0) {
const parts = detail.errors
.map((e) => {
@ -66,6 +73,29 @@ async function req(path, opts={}) {
}
return res.json()
}
async function readJsonResponse(res) {
const text = await res.text()
const trimmed = (text || '').trim()
if (!trimmed) {
throw new Error(res.ok ? 'Leere Antwort' : `HTTP ${res.status}`)
}
if (trimmed.startsWith('<')) {
throw new Error(
`Server lieferte HTML statt JSON (HTTP ${res.status}). Meist Timeout oder Datei zu groß — erneut versuchen.`
)
}
let parsed
try {
parsed = JSON.parse(trimmed)
} catch {
throw new Error(trimmed.slice(0, 180) || `HTTP ${res.status}`)
}
if (!res.ok) {
throw new Error(formatFastApiDetail(parsed.detail, JSON.stringify(parsed)))
}
return parsed
}
const json=(d)=>({method:'POST',headers:{'Content-Type':'application/json'},body:JSON.stringify(d)})
const jput=(d)=>({method:'PUT', headers:{'Content-Type':'application/json'},body:JSON.stringify(d)})
@ -203,11 +233,40 @@ export const api = {
},
// Nutrition
importCsv: async(file)=>{
importCsv: async(file, overwriteExisting=false)=>{
const fd=new FormData();fd.append('file',file)
const r=await fetch(`${BASE}/nutrition/import-csv`,{method:'POST',body:fd,headers:hdrs()})
const qs = overwriteExisting ? '?overwrite_existing=true' : ''
const r=await fetch(`${BASE}/nutrition/import-csv${qs}`,{method:'POST',body:fd,headers:hdrs()})
const d=await r.json();if(!r.ok)throw new Error(formatFastApiDetail(d.detail, JSON.stringify(d)));return d
},
listNutritionItems: (date) => req(date ? `/nutrition/items?date=${date}` : '/nutrition/items'),
listUnmappedFoods: () => req('/nutrition/unmapped'),
listNutritionMarks: () => req('/nutrition/marks'),
putNutritionDayMark: (date, d) => req(`/nutrition/days/${date}/mark`, jput(d)),
deleteNutritionDayMark: (date) => req(`/nutrition/days/${date}/mark`, {method:'DELETE'}),
resolveNutritionConflicts: (decisions) => req('/nutrition/import-conflicts/resolve', json({decisions})),
searchBlsFoods: (q, limit=20) => req(`/bls/foods?q=${encodeURIComponent(q||'')}&limit=${limit}`),
createUserFood: (d) => req('/bls/foods/manual', json(d)),
listMyFoodMappings: () => req('/bls/mappings'),
upsertMyFoodMapping: (d) => req('/bls/mappings', json(d)),
deleteMyFoodMapping: (id) => req(`/bls/mappings/${id}`, {method:'DELETE'}),
adminBlsStatus: () => req('/admin/bls/status'),
adminBlsImportStart: async (kind, file) => {
const fd=new FormData();fd.append('file',file)
const r=await fetch(`${BASE}/admin/bls/import/jobs?kind=${encodeURIComponent(kind)}`,{method:'POST',body:fd,headers:hdrs()})
return readJsonResponse(r)
},
adminBlsImportJob: (id) => req(`/admin/bls/import/jobs/${id}`),
adminBlsImportApply: (id) => req(`/admin/bls/import/jobs/${id}/apply`, {method:'POST'}),
adminBlsFoods: (q, kind) => req(`/admin/bls/foods?${q?('q='+encodeURIComponent(q)+'&'):''}${kind?('kind='+kind):''}`),
adminBlsFoodDetail: (id) => req(`/admin/bls/foods/${id}`),
adminCreateManualFood: (d) => req('/admin/bls/foods/manual', json(d)),
adminBlsAttributes: () => req('/admin/bls/attributes'),
adminCreateBlsAttribute: (d) => req('/admin/bls/attributes', json(d)),
adminListFoodMappings: (globalOnly) => req(`/admin/food-mappings${globalOnly?'?global_only=true':''}`),
adminCreateFoodMapping: (d) => req('/admin/food-mappings', json(d)),
adminDeleteFoodMapping: (id) => req(`/admin/food-mappings/${id}`, {method:'DELETE'}),
adminFoodMappingCoverage: () => req('/admin/food-mappings/stats/coverage'),
listNutrition: (l=365) => req(`/nutrition?limit=${l}`),
nutritionCorrelations: () => req('/nutrition/correlations'),
nutritionWeekly: (w=16) => req(`/nutrition/weekly?weeks=${w}`),
@ -713,6 +772,7 @@ export const api = {
req(module ? `/csv/mappings?module=${encodeURIComponent(module)}` : '/csv/mappings'),
copyCsvMapping: (mappingId, body = null) =>
req(`/csv/mappings/${mappingId}/copy`, body ? json(body) : { method: 'POST' }),
validateCsvMapping: (mappingId) => req(`/csv/mappings/${mappingId}/validate`),
/** Universal-CSV (Issue #21): Zielmodul steckt in der Vorlage; nur file + mapping_id */
/** Import-Diagnose: keine Datenbank-Schreibung, erste Zeilen + Mapping-Auflösung */
diagnoseUniversalCsv: async (file, mappingId, module = null) => {

View File

@ -51,8 +51,8 @@ server {
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
proxy_read_timeout 120s; # KI-Calls können länger dauern
client_max_body_size 20M; # CSV + Foto Uploads
proxy_read_timeout 600s; # KI-Calls und BLS-Import
client_max_body_size 50M; # CSV, Foto, BLS-XLSX
}
# Frontend - React PWA

View File

@ -1,12 +1,15 @@
module.exports = {
testDir: './tests',
timeout: 30000,
workers: 1,
globalSetup: require.resolve('./tests/global-setup.js'),
use: {
channel: 'chrome',
headless: true,
viewport: { width: 390, height: 844 },
screenshot: 'only-on-failure',
baseURL: 'https://dev.mitai.jinkendo.de',
storageState: './tests/.auth/user.json',
},
reporter: 'list',
};

View File

@ -1,61 +1,53 @@
const { test, expect } = require('@playwright/test');
const { loginViaForm, clickBottomNav } = require('./helpers');
const TEST_EMAIL = process.env.TEST_EMAIL || 'lars@stommer.com';
const TEST_PASSWORD = process.env.TEST_PASSWORD || '5112';
test.describe('Login-Flow', () => {
test.use({ storageState: { cookies: [], origins: [] } });
async function login(page) {
await page.goto('/');
await page.waitForLoadState('networkidle');
await page.fill('input[type="email"]', TEST_EMAIL);
await page.fill('input[type="password"]', TEST_PASSWORD);
await page.click('button:has-text("Anmelden")');
await page.waitForLoadState('networkidle');
}
test('1. Login funktioniert', async ({ page }) => {
await page.goto('/');
await page.fill('input[type="email"]', TEST_EMAIL);
await page.fill('input[type="password"]', TEST_PASSWORD);
await page.click('button:has-text("Anmelden")');
await page.waitForLoadState('networkidle');
const loginButton = page.locator('button:has-text("Anmelden")');
await expect(loginButton).toHaveCount(0, { timeout: 10000 });
await page.screenshot({ path: 'screenshots/01-nach-login.png' });
console.log('Login erfolgreich');
test('1. Login funktioniert', async ({ page }) => {
await loginViaForm(page);
await page.screenshot({ path: 'screenshots/01-nach-login.png' });
console.log('Login erfolgreich');
});
});
test('2. Dashboard laedt ohne Fehler', async ({ page }) => {
await login(page);
await page.goto('/');
await page.waitForLoadState('networkidle');
await expect(page.locator('.spinner')).toHaveCount(0, { timeout: 10000 });
await page.screenshot({ path: 'screenshots/02-dashboard.png' });
console.log('Dashboard OK');
});
test('3. Erfassung erreichbar', async ({ page }) => {
await login(page);
await page.click('text=Erfassung');
test('3. Erfassen erreichbar', async ({ page }) => {
await page.goto('/');
await page.waitForLoadState('networkidle');
await clickBottomNav(page, 'Erfassen');
await page.waitForLoadState('networkidle');
await expect(page).toHaveURL(/\/capture/);
await page.screenshot({ path: 'screenshots/03-erfassung.png' });
console.log('Erfassung OK');
console.log('Erfassen OK');
});
test('4. Analyse erreichbar', async ({ page }) => {
await login(page);
await page.click('text=Analyse');
await page.goto('/');
await page.waitForLoadState('networkidle');
await clickBottomNav(page, 'Analyse');
await page.waitForLoadState('networkidle');
await expect(page).toHaveURL(/\/analysis/);
await page.screenshot({ path: 'screenshots/04-analyse.png' });
console.log('Analyse OK');
});
test('5. Keine kritischen Console-Fehler', async ({ page }) => {
const errors = [];
page.on('console', msg => {
page.on('console', (msg) => {
if (msg.type() === 'error') errors.push(msg.text());
});
await login(page);
await page.goto('/');
await page.waitForLoadState('networkidle');
const kritisch = errors.filter(e =>
!e.includes('favicon') && !e.includes('sourceMap') && !e.includes('404')
const kritisch = errors.filter(
(e) => !e.includes('favicon') && !e.includes('sourceMap') && !e.includes('404')
);
if (kritisch.length > 0) {
console.log('Console-Fehler:', kritisch.join(', '));
@ -63,3 +55,35 @@ test('5. Keine kritischen Console-Fehler', async ({ page }) => {
console.log('Keine kritischen Console-Fehler');
}
});
test('FEATURE: Ernährung — Einzelerfassung, Import-Policy-Hinweis, Zuordnen', async ({ page }) => {
await page.goto('/nutrition');
await page.waitForLoadState('networkidle');
await expect(page.getByRole('button', { name: /Einzelerfassung/i })).toBeVisible();
await page.getByRole('button', { name: /Import/i }).click();
await expect(page.locator('.card').filter({ hasText: 'FDDB CSV Import' })).toBeVisible();
await expect(page.getByText(/Vorhandene Tagesmakros überschreiben/)).toBeVisible();
await page.getByRole('button', { name: /Zuordnen/i }).click();
await expect(page.getByText(/Lebensmittel zuordnen/)).toBeVisible();
});
test('FEATURE: Settings — Ernährungs-Import-Policy', async ({ page }) => {
await page.goto('/settings');
await page.waitForLoadState('networkidle');
await expect(page.getByText('Ernährungs-Import')).toBeVisible();
await expect(page.locator('select').filter({ has: page.locator('option[value="prompt"]') })).toBeVisible();
});
test('API: nutrition unmapped + marks erreichbar', async ({ page }) => {
await page.goto('/nutrition');
await page.waitForLoadState('networkidle');
const token = await page.evaluate(() => localStorage.getItem('bodytrack_token'));
expect(token).toBeTruthy();
const headers = { 'X-Auth-Token': token };
const unmapped = await page.request.get('/api/nutrition/unmapped', { headers });
expect(unmapped.ok()).toBeTruthy();
const marks = await page.request.get('/api/nutrition/marks', { headers });
expect(marks.ok()).toBeTruthy();
const foods = await page.request.get('/api/bls/foods?q=hafer', { headers });
expect(foods.ok()).toBeTruthy();
});

64
tests/global-setup.js Normal file
View File

@ -0,0 +1,64 @@
const { chromium } = require('@playwright/test');
const fs = require('fs');
const path = require('path');
const TEST_EMAIL = process.env.TEST_EMAIL || 'lars@stommer.com';
const TEST_PASSWORD = process.env.TEST_PASSWORD || '5112';
const AUTH_FILE = path.join(__dirname, '.auth', 'user.json');
async function tryLogin(page, baseURL) {
await page.goto(`${baseURL}/`);
await page.waitForLoadState('networkidle');
const loginBtn = page.locator('button:has-text("Anmelden")');
if ((await loginBtn.count()) === 0) {
return { ok: true, status: 200 };
}
await page.fill('input[type="email"]', TEST_EMAIL);
await page.fill('input[type="password"]', TEST_PASSWORD);
const responsePromise = page
.waitForResponse(
(r) => r.url().includes('/api/auth/login') && r.request().method() === 'POST',
{ timeout: 15000 }
)
.catch(() => null);
await page.click('button:has-text("Anmelden")');
const response = await responsePromise;
await page.waitForLoadState('networkidle');
const loginVisible = await page.locator('button:has-text("Anmelden")').count();
return { ok: loginVisible === 0, status: response?.status() ?? null };
}
module.exports = async (config) => {
fs.mkdirSync(path.dirname(AUTH_FILE), { recursive: true });
const browser = await chromium.launch({ channel: 'chrome', headless: true });
const page = await browser.newPage();
const baseURL = config.projects?.[0]?.use?.baseURL || 'https://dev.mitai.jinkendo.de';
const waits = [0, 15000, 30000, 45000];
let lastStatus = null;
for (let i = 0; i < waits.length; i++) {
if (waits[i] > 0) {
console.log(`Global setup: warte ${waits[i] / 1000}s (Login-Rate-Limit 5/min)…`);
await page.waitForTimeout(waits[i]);
}
const result = await tryLogin(page, baseURL);
lastStatus = result.status;
if (result.ok) {
await page.context().storageState({ path: AUTH_FILE });
await browser.close();
return;
}
}
await browser.close();
throw new Error(
`Global setup: Login fehlgeschlagen (letzter HTTP-Status: ${lastStatus ?? 'unbekannt'})`
);
};

23
tests/helpers.js Normal file
View File

@ -0,0 +1,23 @@
const { expect } = require('@playwright/test');
const TEST_EMAIL = process.env.TEST_EMAIL || 'lars@stommer.com';
const TEST_PASSWORD = process.env.TEST_PASSWORD || '5112';
/** Nutzt storageState aus global-setup; nur für Tests nötig, die explizit Login prüfen. */
async function loginViaForm(page) {
await page.goto('/');
await page.waitForLoadState('networkidle');
await page.fill('input[type="email"]', TEST_EMAIL);
await page.fill('input[type="password"]', TEST_PASSWORD);
await page.click('button:has-text("Anmelden")');
await page.waitForLoadState('networkidle');
await expect(page.locator('button:has-text("Anmelden")')).toHaveCount(0, { timeout: 15000 });
}
async function clickBottomNav(page, label) {
const link = page.locator('nav.bottom-nav a.nav-item').filter({ hasText: label });
await expect(link).toBeVisible({ timeout: 10000 });
await link.click();
}
module.exports = { TEST_EMAIL, TEST_PASSWORD, loginViaForm, clickBottomNav };

52
tests/issue-audit.spec.js Normal file
View File

@ -0,0 +1,52 @@
/**
* Gitea Issue-Audit UI-Verifikation gegen dev.mitai.jinkendo.de
* Einmaliger Audit-Lauf; keine dauerhafte CI-Pflicht.
*/
const { test, expect } = require('@playwright/test');
test.describe('Issue-Audit UI', () => {
test('#40 Logout-Button im Mobile-Header sichtbar', async ({ page }) => {
await page.goto('/');
await page.waitForLoadState('networkidle');
const logoutBtn = page.locator('header.app-header--mobile button[title="Abmelden"]');
await expect(logoutBtn).toBeVisible();
});
test('#25 Goals-Seite erreichbar und rendert Inhalt', async ({ page }) => {
await page.goto('/goals');
await page.waitForLoadState('networkidle');
await expect(page.locator('body')).not.toContainText('404', { timeout: 5000 });
const hasGoalsUi =
(await page.getByText(/Ziel/i).count()) > 0 ||
(await page.locator('.card').count()) > 0;
expect(hasGoalsUi).toBeTruthy();
});
test('#65 Dashboard-Layout-Konfiguration erreichbar', async ({ page }) => {
await page.goto('/settings/dashboard-layout');
await page.waitForLoadState('networkidle');
const body = await page.locator('body').innerText();
expect(body).toMatch(/Widget|Übersicht|Layout|Dashboard/i);
});
test('#30 Desktop-Sidebar bei breitem Viewport', async ({ page }) => {
await page.goto('/');
await page.waitForLoadState('networkidle');
await page.setViewportSize({ width: 1280, height: 800 });
await expect(page.locator('aside.desktop-sidebar')).toBeVisible({ timeout: 10000 });
});
test('#38 Nutrition CSV Import — FDDB-Panel mit Usage-Integration', async ({ page }) => {
await page.goto('/nutrition');
await page.waitForLoadState('networkidle');
await page.getByRole('button', { name: /Import/i }).click();
await page.waitForLoadState('networkidle');
const importCard = page.locator('.card').filter({ hasText: 'FDDB CSV Import' });
await expect(importCard).toBeVisible();
await expect(importCard.getByText(/Vorhandene Tagesmakros überschreiben/)).toBeVisible();
const titleRow = importCard.locator('.card-title.badge-container-right');
if (await titleRow.count()) {
await expect(titleRow).toBeVisible();
}
});
});