Lars
df0165bee3
- Introduced `c_arm_relaxed` to the CircumferenceEntry model for tracking relaxed arm measurements. - Updated database schema to include `c_arm_relaxed` in the circumference_log table. - Implemented calculation for 28-day relaxed arm circumference change with `calculate_arm_relaxed_28d_delta`. - Enhanced placeholder resolver and registration to support new relaxed arm measurement. - Updated frontend components to accommodate the new measurement, including forms and CSV exports. - Improved documentation and guide data to reflect the addition of relaxed arm measurements.
295 lines
14 KiB
Python
295 lines
14 KiB
Python
"""
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Data Import Endpoints for Mitai Jinkendo
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Handles ZIP import with validation and rollback support.
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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 uuid
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import logging
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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 fastapi import APIRouter, HTTPException, UploadFile, File, Header, Depends
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from db import get_db, get_cursor
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from auth import require_auth, check_feature_access, increment_feature_usage
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from routers.profiles import get_pid
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from feature_logger import log_feature_usage
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router = APIRouter(prefix="/api/import", tags=["import"])
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logger = logging.getLogger(__name__)
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PHOTOS_DIR = Path(os.getenv("PHOTOS_DIR", "./photos"))
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@router.post("/zip")
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async def import_zip(
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file: UploadFile = File(...),
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x_profile_id: Optional[str] = Header(default=None),
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session: dict = Depends(require_auth)
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):
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"""
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Import data from ZIP export file.
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- Validates export format
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- Imports missing entries only (ON CONFLICT DO NOTHING)
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- Imports photos
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- Returns import summary
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- Full rollback on error
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"""
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pid = get_pid(x_profile_id)
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# Phase 4: Check feature access and ENFORCE
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access = check_feature_access(pid, 'data_import')
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log_feature_usage(pid, 'data_import', access, 'import_zip')
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if not access['allowed']:
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logger.warning(
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f"[FEATURE-LIMIT] User {pid} blocked: "
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f"data_import {access['reason']} (used: {access['used']}, limit: {access['limit']})"
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)
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raise HTTPException(
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status_code=403,
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detail=f"Limit erreicht: Du hast das Kontingent für Daten-Importe überschritten ({access['used']}/{access['limit']}). "
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f"Bitte kontaktiere den Admin oder warte bis zum nächsten Reset."
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)
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# Read uploaded file
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content = await file.read()
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zip_buffer = io.BytesIO(content)
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try:
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with zipfile.ZipFile(zip_buffer, 'r') as zf:
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# 1. Validate profile.json
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if 'profile.json' not in zf.namelist():
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raise HTTPException(400, "Ungültiger Export: profile.json fehlt")
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profile_data = json.loads(zf.read('profile.json').decode('utf-8'))
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export_version = profile_data.get('export_version', '1')
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# Stats tracker
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stats = {
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'weight': 0,
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'circumferences': 0,
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'caliper': 0,
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'nutrition': 0,
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'activity': 0,
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'photos': 0,
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'insights': 0
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}
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with get_db() as conn:
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cur = get_cursor(conn)
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try:
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# 2. Import weight.csv
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if 'data/weight.csv' in zf.namelist():
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csv_data = zf.read('data/weight.csv').decode('utf-8-sig')
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reader = csv.DictReader(io.StringIO(csv_data), delimiter=';')
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for row in reader:
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cur.execute("""
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INSERT INTO weight_log (profile_id, date, weight, note, source, created)
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VALUES (%s, %s, %s, %s, %s, %s)
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ON CONFLICT (profile_id, date) DO NOTHING
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""", (
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pid,
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row['date'],
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float(row['weight']) if row['weight'] else None,
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row.get('note', ''),
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row.get('source', 'import'),
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row.get('created', datetime.now())
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))
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if cur.rowcount > 0:
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stats['weight'] += 1
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# 3. Import circumferences.csv
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if 'data/circumferences.csv' in zf.namelist():
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csv_data = zf.read('data/circumferences.csv').decode('utf-8-sig')
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reader = csv.DictReader(io.StringIO(csv_data), delimiter=';')
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for row in reader:
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_ua_contr = (
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row.get('upper_arm_contracted')
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or row.get('upper_arm')
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)
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_ua_rel = row.get('upper_arm_relaxed')
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cur.execute("""
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INSERT INTO circumference_log (
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profile_id, date, c_waist, c_hip, c_chest, c_neck,
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c_arm, c_arm_relaxed, c_thigh, c_calf, notes, created
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)
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VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
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ON CONFLICT (profile_id, date) DO NOTHING
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""", (
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pid,
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row['date'],
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float(row['waist']) if row.get('waist') else None,
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float(row['hip']) if row.get('hip') else None,
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float(row['chest']) if row.get('chest') else None,
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float(row['neck']) if row.get('neck') else None,
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float(_ua_contr) if _ua_contr not in (None, '') else None,
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float(_ua_rel) if _ua_rel not in (None, '') else None,
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float(row['thigh']) if row.get('thigh') else None,
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float(row['calf']) if row.get('calf') else None,
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row.get('note', ''),
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row.get('created', datetime.now())
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))
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if cur.rowcount > 0:
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stats['circumferences'] += 1
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# 4. Import caliper.csv
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if 'data/caliper.csv' in zf.namelist():
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csv_data = zf.read('data/caliper.csv').decode('utf-8-sig')
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reader = csv.DictReader(io.StringIO(csv_data), delimiter=';')
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for row in reader:
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cur.execute("""
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INSERT INTO caliper_log (
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profile_id, date, sf_chest, sf_abdomen, sf_thigh,
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sf_triceps, sf_subscap, sf_suprailiac, sf_axilla,
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sf_method, body_fat_pct, notes, created
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)
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VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
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ON CONFLICT (profile_id, date) DO NOTHING
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""", (
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pid,
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row['date'],
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float(row['chest']) if row.get('chest') else None,
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float(row['abdomen']) if row.get('abdomen') else None,
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float(row['thigh']) if row.get('thigh') else None,
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float(row['tricep']) if row.get('tricep') else None,
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float(row['subscapular']) if row.get('subscapular') else None,
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float(row['suprailiac']) if row.get('suprailiac') else None,
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float(row['midaxillary']) if row.get('midaxillary') else None,
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row.get('method', 'jackson3'),
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float(row['bf_percent']) if row.get('bf_percent') else None,
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row.get('note', ''),
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row.get('created', datetime.now())
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))
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if cur.rowcount > 0:
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stats['caliper'] += 1
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# 5. Import nutrition.csv
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if 'data/nutrition.csv' in zf.namelist():
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csv_data = zf.read('data/nutrition.csv').decode('utf-8-sig')
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reader = csv.DictReader(io.StringIO(csv_data), delimiter=';')
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for row in reader:
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cur.execute("""
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INSERT INTO nutrition_log (
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profile_id, date, kcal, protein_g, fat_g, carbs_g, source, created
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)
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VALUES (%s, %s, %s, %s, %s, %s, %s, %s)
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ON CONFLICT (profile_id, date) DO NOTHING
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""", (
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pid,
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row['date'],
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float(row['kcal']) if row.get('kcal') else None,
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float(row['protein']) if row.get('protein') else None,
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float(row['fat']) if row.get('fat') else None,
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float(row['carbs']) if row.get('carbs') else None,
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row.get('source', 'import'),
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row.get('created', datetime.now())
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))
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if cur.rowcount > 0:
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stats['nutrition'] += 1
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# 6. Import activity.csv
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if 'data/activity.csv' in zf.namelist():
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csv_data = zf.read('data/activity.csv').decode('utf-8-sig')
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reader = csv.DictReader(io.StringIO(csv_data), delimiter=';')
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for row in reader:
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cur.execute("""
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INSERT INTO activity_log (
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profile_id, date, activity_type, duration_min,
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kcal_active, hr_avg, hr_max, distance_km, notes, source, created
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)
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VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
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""", (
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pid,
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row['date'],
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row.get('type', 'Training'),
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float(row['duration_min']) if row.get('duration_min') else None,
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float(row['kcal']) if row.get('kcal') else None,
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float(row['heart_rate_avg']) if row.get('heart_rate_avg') else None,
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float(row['heart_rate_max']) if row.get('heart_rate_max') else None,
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float(row['distance_km']) if row.get('distance_km') else None,
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row.get('note', ''),
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row.get('source', 'import'),
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row.get('created', datetime.now())
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))
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if cur.rowcount > 0:
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stats['activity'] += 1
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# 7. Import ai_insights.json
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if 'insights/ai_insights.json' in zf.namelist():
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insights_data = json.loads(zf.read('insights/ai_insights.json').decode('utf-8'))
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for insight in insights_data:
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cur.execute("""
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INSERT INTO ai_insights (profile_id, scope, content, created)
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VALUES (%s, %s, %s, %s)
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""", (
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pid,
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insight['scope'],
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insight['result'],
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insight.get('created', datetime.now())
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))
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stats['insights'] += 1
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# 8. Import photos
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photo_files = [f for f in zf.namelist() if f.startswith('photos/') and not f.endswith('/')]
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for photo_file in photo_files:
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# Extract date from filename (format: YYYY-MM-DD_N.jpg)
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filename = Path(photo_file).name
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parts = filename.split('_')
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photo_date = parts[0] if len(parts) > 0 else datetime.now().strftime('%Y-%m-%d')
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# Generate new ID and path
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photo_id = str(uuid.uuid4())
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ext = Path(filename).suffix
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new_filename = f"{photo_id}{ext}"
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target_path = PHOTOS_DIR / new_filename
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# Check if photo already exists for this date
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cur.execute("""
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SELECT id FROM photos
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WHERE profile_id = %s AND date = %s
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""", (pid, photo_date))
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if cur.fetchone() is None:
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# Write photo file
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with open(target_path, 'wb') as f:
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f.write(zf.read(photo_file))
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# Insert DB record
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cur.execute("""
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INSERT INTO photos (id, profile_id, date, path, created)
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VALUES (%s, %s, %s, %s, %s)
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""", (photo_id, pid, photo_date, new_filename, datetime.now()))
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stats['photos'] += 1
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# Commit transaction
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conn.commit()
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except Exception as e:
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# Rollback on any error
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conn.rollback()
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raise HTTPException(500, f"Import fehlgeschlagen: {str(e)}")
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# Phase 2: Increment usage counter
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increment_feature_usage(pid, 'data_import')
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return {
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"ok": True,
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"message": "Import erfolgreich",
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"stats": stats,
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"total": sum(stats.values())
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}
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except zipfile.BadZipFile:
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raise HTTPException(400, "Ungültige ZIP-Datei")
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except Exception as e:
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raise HTTPException(500, f"Import-Fehler: {str(e)}")
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