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Version 9b #1

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Lars merged 34 commits from develop into main 2026-03-19 08:04:02 +01:00
Conversation 1 Commits 34 Files Changed 18 +40 -25
1 changed files with 40 additions and 25 deletions
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backend/main.py
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@ -2,6 +2,7 @@ import os, csv, io, uuid, json, zipfile
from pathlib import Path
from typing import Optional
from datetime import datetime
from decimal import Decimal
from fastapi import FastAPI, HTTPException, UploadFile, File, Header, Query, Depends
from fastapi.middleware.cors import CORSMiddleware
@ -268,9 +269,9 @@ def weight_stats(x_profile_id: Optional[str]=Header(default=None), session: dict
cur.execute("SELECT date,weight FROM weight_log WHERE profile_id=%s ORDER BY date DESC LIMIT 90", (pid,))
rows = cur.fetchall()
if not rows: return {"count":0,"latest":None,"prev":None,"min":None,"max":None,"avg_7d":None}
w=[r['weight'] for r in rows]
return {"count":len(rows),"latest":{"date":rows[0]['date'],"weight":rows[0]['weight']},
"prev":{"date":rows[1]['date'],"weight":rows[1]['weight']} if len(rows)>1 else None,
w=[float(r['weight']) for r in rows]
return {"count":len(rows),"latest":{"date":rows[0]['date'],"weight":float(rows[0]['weight'])},
"prev":{"date":rows[1]['date'],"weight":float(rows[1]['weight'])} if len(rows)>1 else None,
"min":min(w),"max":max(w),"avg_7d":round(sum(w[:7])/min(7,len(w)),2)}
# ── Circumferences ────────────────────────────────────────────────────────────
@ -428,13 +429,14 @@ def activity_stats(x_profile_id: Optional[str]=Header(default=None), session: di
"SELECT * FROM activity_log WHERE profile_id=%s ORDER BY date DESC LIMIT 30", (pid,))
rows = [r2d(r) for r in cur.fetchall()]
if not rows: return {"count":0,"total_kcal":0,"total_min":0,"by_type":{}}
total_kcal=sum(r.get('kcal_active') or 0 for r in rows)
total_min=sum(r.get('duration_min') or 0 for r in rows)
total_kcal=sum(float(r.get('kcal_active') or 0) for r in rows)
total_min=sum(float(r.get('duration_min') or 0) for r in rows)
by_type={}
for r in rows:
t=r['activity_type']; by_type.setdefault(t,{'count':0,'kcal':0,'min':0})
by_type[t]['count']+=1; by_type[t]['kcal']+=r.get('kcal_active') or 0
by_type[t]['min']+=r.get('duration_min') or 0
by_type[t]['count']+=1
by_type[t]['kcal']+=float(r.get('kcal_active') or 0)
by_type[t]['min']+=float(r.get('duration_min') or 0)
return {"count":len(rows),"total_kcal":round(total_kcal),"total_min":round(total_min),"by_type":by_type}
@app.post("/api/activity/import-csv")
@ -590,11 +592,13 @@ def nutrition_correlations(x_profile_id: Optional[str]=Header(default=None), ses
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:nutr[d][k] for k in ['kcal','protein_g','fat_g','carbs_g']})
if d in wlog: row['weight']=wlog[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:
row['lean_mass']=cal_by_date[d].get('lean_mass')
row['body_fat_pct']=cal_by_date[d].get('body_fat_pct')
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
@ -613,7 +617,7 @@ def nutrition_weekly(weeks: int=16, x_profile_id: Optional[str]=Header(default=N
result=[]
for wk in sorted(wm):
en=wm[wk]; n=len(en)
def avg(k): return round(sum(e.get(k) or 0 for e in en)/n,1)
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
@ -768,10 +772,10 @@ def _prepare_template_vars(data: dict) -> dict:
"name": prof.get('name', 'Nutzer'),
"geschlecht": "männlich" if prof.get('sex') == 'm' else "weiblich",
"height": prof.get('height', 178),
"goal_weight": prof.get('goal_weight') or "nicht gesetzt",
"goal_bf_pct": prof.get('goal_bf_pct') or "nicht gesetzt",
"weight_aktuell": weight[0]['weight'] if weight else "keine Daten",
"kf_aktuell": caliper[0]['body_fat_pct'] if caliper and caliper[0].get('body_fat_pct') else "unbekannt",
"goal_weight": float(prof.get('goal_weight')) if prof.get('goal_weight') else "nicht gesetzt",
"goal_bf_pct": float(prof.get('goal_bf_pct')) if prof.get('goal_bf_pct') else "nicht gesetzt",
"weight_aktuell": float(weight[0]['weight']) if weight else "keine Daten",
"kf_aktuell": float(caliper[0]['body_fat_pct']) if caliper and caliper[0].get('body_fat_pct') else "unbekannt",
}
# Calculate age from dob
@ -798,7 +802,8 @@ def _prepare_template_vars(data: dict) -> dict:
# Caliper summary
if caliper:
c = caliper[0]
vars['caliper_summary'] = f"KF: {c.get('body_fat_pct','?')}%, Methode: {c.get('sf_method','?')}"
bf = float(c.get('body_fat_pct')) if c.get('body_fat_pct') else '?'
vars['caliper_summary'] = f"KF: {bf}%, Methode: {c.get('sf_method','?')}"
else:
vars['caliper_summary'] = "keine Daten"
@ -807,7 +812,7 @@ def _prepare_template_vars(data: dict) -> dict:
c = circ[0]
parts = []
for k in ['c_waist', 'c_belly', 'c_hip']:
if c.get(k): parts.append(f"{k.split('_')[1]}: {c[k]}cm")
if c.get(k): parts.append(f"{k.split('_')[1]}: {float(c[k])}cm")
vars['circ_summary'] = ", ".join(parts) if parts else "keine Daten"
else:
vars['circ_summary'] = "keine Daten"
@ -1431,28 +1436,28 @@ def export_csv(x_profile_id: Optional[str]=Header(default=None), session: dict=D
cur = get_cursor(conn)
cur.execute("SELECT date, weight, note FROM weight_log WHERE profile_id=%s ORDER BY date", (pid,))
for r in cur.fetchall():
writer.writerow(["Gewicht", r['date'], f"{r['weight']}kg", r['note'] or ""])
writer.writerow(["Gewicht", r['date'], f"{float(r['weight'])}kg", r['note'] or ""])
# Circumferences
cur.execute("SELECT date, c_waist, c_belly, c_hip FROM circumference_log WHERE profile_id=%s ORDER BY date", (pid,))
for r in cur.fetchall():
details = f"Taille:{r['c_waist']}cm Bauch:{r['c_belly']}cm Hüfte:{r['c_hip']}cm"
details = f"Taille:{float(r['c_waist'])}cm Bauch:{float(r['c_belly'])}cm Hüfte:{float(r['c_hip'])}cm"
writer.writerow(["Umfänge", r['date'], "", details])
# Caliper
cur.execute("SELECT date, body_fat_pct, lean_mass FROM caliper_log WHERE profile_id=%s ORDER BY date", (pid,))
for r in cur.fetchall():
writer.writerow(["Caliper", r['date'], f"{r['body_fat_pct']}%", f"Magermasse:{r['lean_mass']}kg"])
writer.writerow(["Caliper", r['date'], f"{float(r['body_fat_pct'])}%", f"Magermasse:{float(r['lean_mass'])}kg"])
# Nutrition
cur.execute("SELECT date, kcal, protein_g FROM nutrition_log WHERE profile_id=%s ORDER BY date", (pid,))
for r in cur.fetchall():
writer.writerow(["Ernährung", r['date'], f"{r['kcal']}kcal", f"Protein:{r['protein_g']}g"])
writer.writerow(["Ernährung", r['date'], f"{float(r['kcal'])}kcal", f"Protein:{float(r['protein_g'])}g"])
# Activity
cur.execute("SELECT date, activity_type, duration_min, kcal_active FROM activity_log WHERE profile_id=%s ORDER BY date", (pid,))
for r in cur.fetchall():
writer.writerow(["Training", r['date'], r['activity_type'], f"{r['duration_min']}min {r['kcal_active']}kcal"])
writer.writerow(["Training", r['date'], r['activity_type'], f"{float(r['duration_min'])}min {float(r['kcal_active'])}kcal"])
output.seek(0)
return StreamingResponse(
@ -1500,7 +1505,12 @@ def export_json(x_profile_id: Optional[str]=Header(default=None), session: dict=
cur.execute("SELECT * FROM ai_insights WHERE profile_id=%s ORDER BY created DESC", (pid,))
data['insights'] = [r2d(r) for r in cur.fetchall()]
json_str = json.dumps(data, indent=2, default=str)
def decimal_handler(obj):
if isinstance(obj, Decimal):
return float(obj)
return str(obj)
json_str = json.dumps(data, indent=2, default=decimal_handler)
return Response(
content=json_str,
media_type="application/json",
@ -1549,7 +1559,12 @@ def export_zip(x_profile_id: Optional[str]=Header(default=None), session: dict=D
cur.execute("SELECT * FROM ai_insights WHERE profile_id=%s ORDER BY created DESC", (pid,))
data['insights'] = [r2d(r) for r in cur.fetchall()]
zf.writestr("data.json", json.dumps(data, indent=2, default=str))
def decimal_handler(obj):
if isinstance(obj, Decimal):
return float(obj)
return str(obj)
zf.writestr("data.json", json.dumps(data, indent=2, default=decimal_handler))
# Add photos if they exist
with get_db() as conn: