Lars
4fcde4abfb
Reverts all feature enforcement changes (commits3745ebd,cbad50a,cd4d912,8415509) to restore original working functionality. Issues caused by feature enforcement implementation: - Export buttons disappeared and never reappeared - KI analysis counter not incrementing - New analyses not saving - Pipeline appearing twice - Many core features broken Restored files to working state before enforcement implementation (commit0210844): - Backend: auth.py, insights.py, exportdata.py, importdata.py, nutrition.py, activity.py - Frontend: Analysis.jsx, SettingsPage.jsx, api.js - Removed: FeatureGate.jsx, useFeatureAccess.js The original simple AI limit system (ai_enabled, ai_limit_day) is now active again. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
305 lines
14 KiB
Python
305 lines
14 KiB
Python
"""
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Data Export Endpoints for Mitai Jinkendo
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Handles CSV, JSON, and ZIP exports with photos.
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"""
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import os
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import csv
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import io
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import json
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import zipfile
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from pathlib import Path
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from typing import Optional
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from datetime import datetime
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from decimal import Decimal
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from fastapi import APIRouter, HTTPException, Header, Depends
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from fastapi.responses import StreamingResponse, Response
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from db import get_db, get_cursor, r2d
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from auth import require_auth
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from routers.profiles import get_pid
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router = APIRouter(prefix="/api/export", tags=["export"])
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PHOTOS_DIR = Path(os.getenv("PHOTOS_DIR", "./photos"))
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@router.get("/csv")
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def export_csv(x_profile_id: Optional[str]=Header(default=None), session: dict=Depends(require_auth)):
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"""Export all data as CSV."""
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pid = get_pid(x_profile_id)
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# Check export permission
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with get_db() as conn:
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cur = get_cursor(conn)
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cur.execute("SELECT export_enabled FROM profiles WHERE id=%s", (pid,))
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prof = cur.fetchone()
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if not prof or not prof['export_enabled']:
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raise HTTPException(403, "Export ist für dieses Profil deaktiviert")
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# Build CSV
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output = io.StringIO()
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writer = csv.writer(output)
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# Header
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writer.writerow(["Typ", "Datum", "Wert", "Details"])
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# Weight
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with get_db() as conn:
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cur = get_cursor(conn)
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cur.execute("SELECT date, weight, note FROM weight_log WHERE profile_id=%s ORDER BY date", (pid,))
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for r in cur.fetchall():
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writer.writerow(["Gewicht", r['date'], f"{float(r['weight'])}kg", r['note'] or ""])
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# Circumferences
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cur.execute("SELECT date, c_waist, c_belly, c_hip FROM circumference_log WHERE profile_id=%s ORDER BY date", (pid,))
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for r in cur.fetchall():
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details = f"Taille:{float(r['c_waist'])}cm Bauch:{float(r['c_belly'])}cm Hüfte:{float(r['c_hip'])}cm"
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writer.writerow(["Umfänge", r['date'], "", details])
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# Caliper
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cur.execute("SELECT date, body_fat_pct, lean_mass FROM caliper_log WHERE profile_id=%s ORDER BY date", (pid,))
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for r in cur.fetchall():
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writer.writerow(["Caliper", r['date'], f"{float(r['body_fat_pct'])}%", f"Magermasse:{float(r['lean_mass'])}kg"])
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# Nutrition
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cur.execute("SELECT date, kcal, protein_g FROM nutrition_log WHERE profile_id=%s ORDER BY date", (pid,))
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for r in cur.fetchall():
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writer.writerow(["Ernährung", r['date'], f"{float(r['kcal'])}kcal", f"Protein:{float(r['protein_g'])}g"])
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# Activity
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cur.execute("SELECT date, activity_type, duration_min, kcal_active FROM activity_log WHERE profile_id=%s ORDER BY date", (pid,))
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for r in cur.fetchall():
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writer.writerow(["Training", r['date'], r['activity_type'], f"{float(r['duration_min'])}min {float(r['kcal_active'])}kcal"])
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output.seek(0)
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return StreamingResponse(
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iter([output.getvalue()]),
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media_type="text/csv",
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headers={"Content-Disposition": f"attachment; filename=mitai-export-{pid}.csv"}
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)
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@router.get("/json")
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def export_json(x_profile_id: Optional[str]=Header(default=None), session: dict=Depends(require_auth)):
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"""Export all data as JSON."""
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pid = get_pid(x_profile_id)
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# Check export permission
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with get_db() as conn:
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cur = get_cursor(conn)
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cur.execute("SELECT export_enabled FROM profiles WHERE id=%s", (pid,))
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prof = cur.fetchone()
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if not prof or not prof['export_enabled']:
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raise HTTPException(403, "Export ist für dieses Profil deaktiviert")
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# Collect all data
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data = {}
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with get_db() as conn:
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cur = get_cursor(conn)
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cur.execute("SELECT * FROM profiles WHERE id=%s", (pid,))
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data['profile'] = r2d(cur.fetchone())
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cur.execute("SELECT * FROM weight_log WHERE profile_id=%s ORDER BY date", (pid,))
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data['weight'] = [r2d(r) for r in cur.fetchall()]
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cur.execute("SELECT * FROM circumference_log WHERE profile_id=%s ORDER BY date", (pid,))
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data['circumferences'] = [r2d(r) for r in cur.fetchall()]
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cur.execute("SELECT * FROM caliper_log WHERE profile_id=%s ORDER BY date", (pid,))
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data['caliper'] = [r2d(r) for r in cur.fetchall()]
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cur.execute("SELECT * FROM nutrition_log WHERE profile_id=%s ORDER BY date", (pid,))
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data['nutrition'] = [r2d(r) for r in cur.fetchall()]
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cur.execute("SELECT * FROM activity_log WHERE profile_id=%s ORDER BY date", (pid,))
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data['activity'] = [r2d(r) for r in cur.fetchall()]
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cur.execute("SELECT * FROM ai_insights WHERE profile_id=%s ORDER BY created DESC", (pid,))
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data['insights'] = [r2d(r) for r in cur.fetchall()]
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def decimal_handler(obj):
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if isinstance(obj, Decimal):
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return float(obj)
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return str(obj)
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json_str = json.dumps(data, indent=2, default=decimal_handler)
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return Response(
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content=json_str,
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media_type="application/json",
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headers={"Content-Disposition": f"attachment; filename=mitai-export-{pid}.json"}
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)
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@router.get("/zip")
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def export_zip(x_profile_id: Optional[str]=Header(default=None), session: dict=Depends(require_auth)):
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"""Export all data as ZIP (CSV + JSON + photos) per specification."""
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pid = get_pid(x_profile_id)
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# Check export permission & get profile
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with get_db() as conn:
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cur = get_cursor(conn)
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cur.execute("SELECT * FROM profiles WHERE id=%s", (pid,))
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prof = r2d(cur.fetchone())
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if not prof or not prof.get('export_enabled'):
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raise HTTPException(403, "Export ist für dieses Profil deaktiviert")
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# Helper: CSV writer with UTF-8 BOM + semicolon
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def write_csv(zf, filename, rows, columns):
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if not rows:
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return
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output = io.StringIO()
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writer = csv.writer(output, delimiter=';')
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writer.writerow(columns)
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for r in rows:
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writer.writerow([
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'' if r.get(col) is None else
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(float(r[col]) if isinstance(r.get(col), Decimal) else r[col])
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for col in columns
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])
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# UTF-8 with BOM for Excel
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csv_bytes = '\ufeff'.encode('utf-8') + output.getvalue().encode('utf-8')
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zf.writestr(f"data/{filename}", csv_bytes)
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# Create ZIP
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zip_buffer = io.BytesIO()
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export_date = datetime.now().strftime('%Y-%m-%d')
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profile_name = prof.get('name', 'export')
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with zipfile.ZipFile(zip_buffer, 'w', zipfile.ZIP_DEFLATED) as zf:
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with get_db() as conn:
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cur = get_cursor(conn)
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# 1. README.txt
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readme = f"""Mitai Jinkendo – Datenexport
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Version: 2
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Exportiert am: {export_date}
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Profil: {profile_name}
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Inhalt:
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- profile.json: Profildaten und Einstellungen
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- data/*.csv: Messdaten (Semikolon-getrennt, UTF-8)
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- insights/: KI-Auswertungen (JSON)
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- photos/: Progress-Fotos (JPEG)
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Import:
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Dieser Export kann in Mitai Jinkendo unter
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Einstellungen → Import → "Mitai Backup importieren"
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wieder eingespielt werden.
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Format-Version 2 (ab v9b):
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Alle CSV-Dateien sind UTF-8 mit BOM kodiert.
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Trennzeichen: Semikolon (;)
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Datumsformat: YYYY-MM-DD
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"""
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zf.writestr("README.txt", readme.encode('utf-8'))
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# 2. profile.json (ohne Passwort-Hash)
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cur.execute("SELECT COUNT(*) as c FROM weight_log WHERE profile_id=%s", (pid,))
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w_count = cur.fetchone()['c']
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cur.execute("SELECT COUNT(*) as c FROM nutrition_log WHERE profile_id=%s", (pid,))
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n_count = cur.fetchone()['c']
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cur.execute("SELECT COUNT(*) as c FROM activity_log WHERE profile_id=%s", (pid,))
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a_count = cur.fetchone()['c']
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cur.execute("SELECT COUNT(*) as c FROM photos WHERE profile_id=%s", (pid,))
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p_count = cur.fetchone()['c']
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profile_data = {
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"export_version": "2",
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"export_date": export_date,
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"app": "Mitai Jinkendo",
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"profile": {
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"name": prof.get('name'),
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"email": prof.get('email'),
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"sex": prof.get('sex'),
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"height": float(prof['height']) if prof.get('height') else None,
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"birth_year": prof['dob'].year if prof.get('dob') else None,
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"goal_weight": float(prof['goal_weight']) if prof.get('goal_weight') else None,
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"goal_bf_pct": float(prof['goal_bf_pct']) if prof.get('goal_bf_pct') else None,
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"avatar_color": prof.get('avatar_color'),
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"auth_type": prof.get('auth_type'),
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"session_days": prof.get('session_days'),
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"ai_enabled": prof.get('ai_enabled'),
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"tier": prof.get('tier')
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},
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"stats": {
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"weight_entries": w_count,
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"nutrition_entries": n_count,
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"activity_entries": a_count,
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"photos": p_count
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}
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}
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zf.writestr("profile.json", json.dumps(profile_data, indent=2, ensure_ascii=False).encode('utf-8'))
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# 3-7. CSV exports (weight, circumferences, caliper, nutrition, activity)
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cur.execute("SELECT id, date, weight, note, source, created FROM weight_log WHERE profile_id=%s ORDER BY date", (pid,))
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write_csv(zf, "weight.csv", [r2d(r) for r in cur.fetchall()], ['id','date','weight','note','source','created'])
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cur.execute("SELECT id, date, c_waist, c_hip, c_chest, c_neck, c_arm, c_thigh, c_calf, notes, created FROM circumference_log WHERE profile_id=%s ORDER BY date", (pid,))
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rows = [r2d(r) for r in cur.fetchall()]
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for r in rows:
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r['waist'] = r.pop('c_waist', None); r['hip'] = r.pop('c_hip', None)
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r['chest'] = r.pop('c_chest', None); r['neck'] = r.pop('c_neck', None)
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r['upper_arm'] = r.pop('c_arm', None); r['thigh'] = r.pop('c_thigh', None)
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r['calf'] = r.pop('c_calf', None); r['forearm'] = None; r['note'] = r.pop('notes', None)
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write_csv(zf, "circumferences.csv", rows, ['id','date','waist','hip','chest','neck','upper_arm','thigh','calf','forearm','note','created'])
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cur.execute("SELECT id, date, sf_chest, sf_abdomen, sf_thigh, sf_triceps, sf_subscap, sf_suprailiac, sf_axilla, sf_method, body_fat_pct, notes, created FROM caliper_log WHERE profile_id=%s ORDER BY date", (pid,))
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rows = [r2d(r) for r in cur.fetchall()]
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for r in rows:
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r['chest'] = r.pop('sf_chest', None); r['abdomen'] = r.pop('sf_abdomen', None)
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r['thigh'] = r.pop('sf_thigh', None); r['tricep'] = r.pop('sf_triceps', None)
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r['subscapular'] = r.pop('sf_subscap', None); r['suprailiac'] = r.pop('sf_suprailiac', None)
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r['midaxillary'] = r.pop('sf_axilla', None); r['method'] = r.pop('sf_method', None)
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r['bf_percent'] = r.pop('body_fat_pct', None); r['note'] = r.pop('notes', None)
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write_csv(zf, "caliper.csv", rows, ['id','date','chest','abdomen','thigh','tricep','subscapular','suprailiac','midaxillary','method','bf_percent','note','created'])
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cur.execute("SELECT id, date, kcal, protein_g, fat_g, carbs_g, source, created FROM nutrition_log WHERE profile_id=%s ORDER BY date", (pid,))
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rows = [r2d(r) for r in cur.fetchall()]
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for r in rows:
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r['meal_name'] = ''; r['protein'] = r.pop('protein_g', None)
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r['fat'] = r.pop('fat_g', None); r['carbs'] = r.pop('carbs_g', None)
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r['fiber'] = None; r['note'] = ''
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write_csv(zf, "nutrition.csv", rows, ['id','date','meal_name','kcal','protein','fat','carbs','fiber','note','source','created'])
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cur.execute("SELECT id, date, activity_type, duration_min, kcal_active, hr_avg, hr_max, distance_km, notes, source, created FROM activity_log WHERE profile_id=%s ORDER BY date", (pid,))
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rows = [r2d(r) for r in cur.fetchall()]
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for r in rows:
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r['name'] = r['activity_type']; r['type'] = r.pop('activity_type', None)
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r['kcal'] = r.pop('kcal_active', None); r['heart_rate_avg'] = r.pop('hr_avg', None)
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r['heart_rate_max'] = r.pop('hr_max', None); r['note'] = r.pop('notes', None)
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write_csv(zf, "activity.csv", rows, ['id','date','name','type','duration_min','kcal','heart_rate_avg','heart_rate_max','distance_km','note','source','created'])
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# 8. insights/ai_insights.json
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cur.execute("SELECT id, scope, content, created FROM ai_insights WHERE profile_id=%s ORDER BY created DESC", (pid,))
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insights = []
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for r in cur.fetchall():
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rd = r2d(r)
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insights.append({
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"id": rd['id'],
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"scope": rd['scope'],
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"created": rd['created'].isoformat() if hasattr(rd['created'], 'isoformat') else str(rd['created']),
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"result": rd['content']
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})
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if insights:
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zf.writestr("insights/ai_insights.json", json.dumps(insights, indent=2, ensure_ascii=False).encode('utf-8'))
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# 9. photos/
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cur.execute("SELECT * FROM photos WHERE profile_id=%s ORDER BY date", (pid,))
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photos = [r2d(r) for r in cur.fetchall()]
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for i, photo in enumerate(photos):
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photo_path = Path(PHOTOS_DIR) / photo['path']
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if photo_path.exists():
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filename = f"{photo.get('date') or export_date}_{i+1}{photo_path.suffix}"
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zf.write(photo_path, f"photos/{filename}")
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zip_buffer.seek(0)
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filename = f"mitai-export-{profile_name.replace(' ','-')}-{export_date}.zip"
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return StreamingResponse(
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iter([zip_buffer.getvalue()]),
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media_type="application/zip",
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headers={"Content-Disposition": f"attachment; filename={filename}"}
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)
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