mitai-jinkendo/backend/routers/nutrition.py
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feat: implement v9c feature enforcement system
Backend:
- Add feature access checks to insights, export, import endpoints
- Enforce ai_calls, ai_pipeline, data_export, csv_import limits
- Return HTTP 403 (disabled) or 429 (limit exceeded)

Frontend:
- Create useFeatureAccess hook for feature checking
- Create FeatureGate/FeatureBadge components
- Gate KI-Analysen in Analysis page
- Gate Export/Import in Settings page
- Show usage counters (e.g. "3/10")

Docs:
- Update CLAUDE.md with implementation status

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-20 12:43:41 +01:00

149 lines
6.8 KiB
Python

"""
Nutrition Tracking Endpoints for Mitai Jinkendo
Handles nutrition data, FDDB CSV import, correlations, and weekly aggregates.
"""
import csv
import io
import uuid
from typing import Optional
from datetime import datetime
from fastapi import APIRouter, HTTPException, UploadFile, File, Header, Depends
from db import get_db, get_cursor, r2d
from auth import require_auth, check_feature_access, increment_feature_usage
from routers.profiles import get_pid
router = APIRouter(prefix="/api/nutrition", tags=["nutrition"])
# ── Helper ────────────────────────────────────────────────────────────────────
def _pf(s):
"""Parse float from string (handles comma decimal separator)."""
try: return float(str(s).replace(',','.').strip())
except: return 0.0
# ── 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."""
pid = get_pid(x_profile_id)
# Check feature access (v9c feature system)
access = check_feature_access(pid, 'csv_import')
if not access['allowed']:
if access['reason'] == 'feature_disabled':
raise HTTPException(403, "CSV-Import ist für dein Tier nicht verfügbar")
elif access['reason'] == 'limit_exceeded':
raise HTTPException(429, f"Monatliches Import-Limit erreicht ({access['limit']} Imports)")
else:
raise HTTPException(403, f"Zugriff verweigert: {access['reason']}")
raw = await file.read()
try: text = raw.decode('utf-8')
except: text = raw.decode('latin-1')
if text.startswith('\ufeff'): text = text[1:]
if not text.strip(): raise HTTPException(400,"Leere Datei")
reader = csv.DictReader(io.StringIO(text), delimiter=';')
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('.')
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
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))
if cur.fetchone():
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:
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))
inserted+=1
# Increment import usage counter (v9c feature system)
increment_feature_usage(pid, 'csv_import')
return {"rows_parsed":count,"days_imported":inserted,
"date_range":{"from":min(days) if days else None,"to":max(days) if days else None}}
@router.get("")
def list_nutrition(limit: int=365, x_profile_id: Optional[str]=Header(default=None), session: dict=Depends(require_auth)):
"""Get nutrition entries for current profile."""
pid = get_pid(x_profile_id)
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()]
@router.get("/correlations")
def nutrition_correlations(x_profile_id: Optional[str]=Header(default=None), session: dict=Depends(require_auth)):
"""Get nutrition data correlated with weight and body fat."""
pid = get_pid(x_profile_id)
with get_db() as conn:
cur = get_cursor(conn)
cur.execute("SELECT * FROM nutrition_log WHERE profile_id=%s ORDER BY date",(pid,))
nutr={r['date']:r2d(r) for r in cur.fetchall()}
cur.execute("SELECT date,weight FROM weight_log WHERE profile_id=%s ORDER BY date",(pid,))
wlog={r['date']:r['weight'] for r in cur.fetchall()}
cur.execute("SELECT date,lean_mass,body_fat_pct FROM caliper_log WHERE profile_id=%s ORDER BY date",(pid,))
cals=sorted([r2d(r) for r in cur.fetchall()],key=lambda x:x['date'])
all_dates=sorted(set(list(nutr)+list(wlog)))
mi,last_cal,cal_by_date=0,{},{}
for d in all_dates:
while mi<len(cals) and cals[mi]['date']<=d: last_cal=cals[mi]; mi+=1
if last_cal: cal_by_date[d]=last_cal
result=[]
for d in all_dates:
if d not in nutr and d not in wlog: continue
row={'date':d}
if d in nutr: row.update({k:float(nutr[d][k]) if nutr[d][k] is not None else None for k in ['kcal','protein_g','fat_g','carbs_g']})
if d in wlog: row['weight']=float(wlog[d])
if d in cal_by_date:
lm = cal_by_date[d].get('lean_mass')
bf = cal_by_date[d].get('body_fat_pct')
row['lean_mass']=float(lm) if lm is not None else None
row['body_fat_pct']=float(bf) if bf is not None else None
result.append(row)
return result
@router.get("/weekly")
def nutrition_weekly(weeks: int=16, x_profile_id: Optional[str]=Header(default=None), session: dict=Depends(require_auth)):
"""Get nutrition data aggregated by week."""
pid = get_pid(x_profile_id)
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,weeks*7))
rows=[r2d(r) for r in cur.fetchall()]
if not rows: return []
wm={}
for d in rows:
wk=datetime.strptime(d['date'],'%Y-%m-%d').strftime('%Y-W%V')
wm.setdefault(wk,[]).append(d)
result=[]
for wk in sorted(wm):
en=wm[wk]; n=len(en)
def avg(k): return round(sum(float(e.get(k) or 0) for e in en)/n,1)
result.append({'week':wk,'days':n,'kcal':avg('kcal'),'protein_g':avg('protein_g'),'fat_g':avg('fat_g'),'carbs_g':avg('carbs_g')})
return result