cbazzaandClaude Sonnet 4.5
f6106b8333
This project includes multiple AI/ML-based lottery number generators for German Lotto 6aus49, including pattern analysis, weighted predictions, and hybrid approaches. Features automated weekly tip generation, performance tracking, and Telegram bot integration. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
402 lines
13 KiB
Python
Executable File
402 lines
13 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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Ziehungs-Verifizierer für Lotto 6aus49 und Eurojackpot
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Verifiziert Ziehungen gegen offizielle Datenquellen:
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1. GitHub Lotto Archive (für Lotto 6aus49)
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2. Eurojackpot-zahlen.eu (für Eurojackpot)
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Prüft:
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- Vollständigkeit (fehlende Ziehungen)
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- Korrektheit (falsche Zahlen)
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- Duplikate
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"""
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import pandas as pd
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import requests
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from datetime import datetime, timedelta
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from typing import Dict, List, Tuple, Optional
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import sys
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import os
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class DrawVerifier:
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"""Verifiziert Ziehungen gegen offizielle Quellen."""
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def __init__(self, csv_file: str, lottery_type: str):
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self.csv_file = csv_file
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self.lottery_type = lottery_type
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self.df_local = None
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self.df_official = None
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self.errors = []
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self.warnings = []
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self.info = []
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def load_local_data(self) -> bool:
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"""Lädt lokale CSV-Datei."""
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try:
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if not os.path.exists(self.csv_file):
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self.errors.append(f"❌ Datei existiert nicht: {self.csv_file}")
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return False
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self.df_local = pd.read_csv(self.csv_file, sep=';')
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self.df_local['datum'] = pd.to_datetime(
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self.df_local['datum'],
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format='%Y-%m-%d',
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errors='coerce'
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)
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self.info.append(f"✅ Lokale Daten: {len(self.df_local)} Ziehungen")
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return True
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except Exception as e:
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self.errors.append(f"❌ Fehler beim Laden: {e}")
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return False
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def fetch_official_lotto_data(self) -> bool:
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"""Holt offizielle Lotto 6aus49 Daten von GitHub Archive."""
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try:
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url = 'https://johannesfriedrich.github.io/LottoNumberArchive/Lottonumbers_tidy_complete.json'
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print("🌐 Lade offizielle Lotto-Daten von GitHub Archive...")
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headers = {
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'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36'
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}
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response = requests.get(url, headers=headers, timeout=30)
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response.raise_for_status()
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data = response.json()
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# Parse gruppierte Daten
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draws_by_id = {}
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for entry in data:
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draw_id = entry.get('id')
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if draw_id not in draws_by_id:
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draws_by_id[draw_id] = {
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'date': entry.get('date'),
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'numbers': [],
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'superzahl': None
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}
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variable = entry.get('variable')
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value = entry.get('value')
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if variable == 'Lottozahl':
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draws_by_id[draw_id]['numbers'].append(value)
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elif variable == 'Superzahl':
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draws_by_id[draw_id]['superzahl'] = value
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# Konvertiere zu DataFrame
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official_draws = []
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for draw_id, draw_data in draws_by_id.items():
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try:
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date_str = draw_data['date']
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day, month, year = date_str.split('.')
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date_obj = datetime(int(year), int(month), int(day))
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numbers = sorted(draw_data['numbers'])
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if len(numbers) == 6:
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official_draws.append({
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'datum': date_obj,
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'Z1': numbers[0],
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'Z2': numbers[1],
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'Z3': numbers[2],
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'Z4': numbers[3],
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'Z5': numbers[4],
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'Z6': numbers[5],
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'SZ': draw_data['superzahl']
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})
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except Exception:
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continue
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self.df_official = pd.DataFrame(official_draws)
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self.info.append(f"✅ Offizielle Daten: {len(self.df_official)} Ziehungen")
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return True
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except Exception as e:
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self.errors.append(f"❌ Fehler beim Laden offizieller Daten: {e}")
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return False
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def fetch_official_eurojackpot_data(self) -> bool:
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"""
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Holt offizielle Eurojackpot Daten.
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Note: Da es keine vollständige öffentliche API gibt,
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beschränken wir uns auf Plausibilitätsprüfungen.
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"""
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self.warnings.append("⚠️ Keine vollständige offizielle Eurojackpot-API verfügbar")
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self.warnings.append(" Nur Plausibilitätsprüfungen möglich")
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# Erstelle minimale "offizielle" Daten basierend auf erwarteten Ziehungsterminen
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# Dies ist nur für Vollständigkeitsprüfung
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if len(self.df_local) > 0:
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start_date = self.df_local['datum'].min()
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end_date = datetime.now()
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expected_dates = []
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current = start_date
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while current <= end_date:
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# Eurojackpot: Dienstag (1) und Freitag (4)
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if current.weekday() in [1, 4]:
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expected_dates.append(current)
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current += timedelta(days=1)
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self.df_official = pd.DataFrame({'datum': expected_dates})
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self.info.append(f"ℹ️ Erwartete Ziehungstermine: {len(expected_dates)}")
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return True
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def compare_completeness(self) -> List[datetime]:
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"""Prüft auf fehlende Ziehungen."""
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if self.df_official is None or self.df_local is None:
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return []
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official_dates = set(self.df_official['datum'].dt.date)
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local_dates = set(self.df_local['datum'].dt.date)
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missing = official_dates - local_dates
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extra = local_dates - official_dates
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if missing:
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self.errors.append(f"❌ {len(missing)} fehlende Ziehung(en):")
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for date in sorted(missing)[:10]:
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self.errors.append(f" {date.strftime('%Y-%m-%d')}")
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if len(missing) > 10:
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self.errors.append(f" ... und {len(missing) - 10} weitere")
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if extra:
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self.warnings.append(f"⚠️ {len(extra)} zusätzliche Ziehung(en) (nicht in offiziellen Daten):")
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for date in sorted(extra)[:5]:
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self.warnings.append(f" {date.strftime('%Y-%m-%d')}")
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if len(extra) > 5:
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self.warnings.append(f" ... und {len(extra) - 5} weitere")
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return list(missing)
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def compare_accuracy(self) -> int:
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"""Vergleicht Zahlenwerte mit offiziellen Daten."""
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if self.df_official is None or self.df_local is None:
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return 0
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if self.lottery_type == 'eurojackpot':
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# Keine detaillierten offiziellen Daten verfügbar
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return 0
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mismatches = 0
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# Merge auf Datum
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merged = pd.merge(
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self.df_local,
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self.df_official,
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on='datum',
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suffixes=('_local', '_official'),
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how='inner'
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)
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if self.lottery_type == 'lotto':
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cols_to_check = ['Z1', 'Z2', 'Z3', 'Z4', 'Z5', 'Z6', 'SZ']
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else: # eurojackpot
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cols_to_check = ['Z1', 'Z2', 'Z3', 'Z4', 'Z5', 'SZ1', 'SZ2']
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for idx, row in merged.iterrows():
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mismatch_cols = []
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for col in cols_to_check:
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local_col = f"{col}_local"
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official_col = f"{col}_official"
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if local_col in row and official_col in row:
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# Vergleiche nur wenn beide Werte vorhanden
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if pd.notna(row[local_col]) and pd.notna(row[official_col]):
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if row[local_col] != row[official_col]:
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mismatch_cols.append(
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f"{col}: {int(row[local_col])} ≠ {int(row[official_col])}"
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)
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if mismatch_cols:
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mismatches += 1
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if mismatches == 1:
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self.errors.append("❌ Zahlen-Abweichungen gefunden:")
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if mismatches <= 10:
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date_str = row['datum'].strftime('%Y-%m-%d')
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self.errors.append(f" {date_str}: {', '.join(mismatch_cols)}")
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if mismatches > 10:
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self.errors.append(f" ... und {mismatches - 10} weitere Abweichungen")
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return mismatches
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def check_recent_draws(self, days: int = 30) -> None:
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"""Prüft besonders die letzten N Tage."""
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if self.df_local is None:
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return
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cutoff = datetime.now() - timedelta(days=days)
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recent = self.df_local[self.df_local['datum'] >= cutoff]
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self.info.append(f"ℹ️ Letzte {days} Tage: {len(recent)} Ziehungen")
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if len(recent) == 0:
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self.warnings.append(f"⚠️ Keine Ziehungen in den letzten {days} Tagen!")
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# Erwartete Anzahl berechnen
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if self.lottery_type == 'lotto':
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# 2x pro Woche
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expected = (days / 7) * 2
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else: # eurojackpot
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# 2x pro Woche
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expected = (days / 7) * 2
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if len(recent) < expected * 0.8: # Toleranz 20%
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self.warnings.append(
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f"⚠️ Weniger Ziehungen als erwartet: {len(recent)} vs. ~{int(expected)}"
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)
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def verify_all(self) -> bool:
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"""Führt komplette Verifikation durch."""
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print(f"\n{'='*70}")
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print(f" ZIEHUNGS-VERIFIZIERER")
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print(f" Typ: {self.lottery_type.upper()}")
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print(f"{'='*70}")
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print(f"\n📁 Datei: {os.path.basename(self.csv_file)}")
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# Lade lokale Daten
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if not self.load_local_data():
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return False
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# Lade offizielle Daten
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print()
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if self.lottery_type == 'lotto':
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if not self.fetch_official_lotto_data():
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return False
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else: # eurojackpot
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if not self.fetch_official_eurojackpot_data():
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return False
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print(f"\n🔍 VERIFIKATION")
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print("="*70)
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# Prüfungen
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print("Prüfe Vollständigkeit...")
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missing = self.compare_completeness()
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if self.lottery_type == 'lotto':
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print("Prüfe Zahlenwerte...")
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mismatches = self.compare_accuracy()
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print("Prüfe aktuelle Ziehungen...")
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self.check_recent_draws(30)
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# Statistiken
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print(f"\n📊 STATISTIKEN")
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print("="*70)
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for info in self.info:
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print(info)
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# Zusammenfassung
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if self.df_local is not None and self.df_official is not None:
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if self.lottery_type == 'lotto':
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overlap = len(pd.merge(
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self.df_local,
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self.df_official,
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on='datum',
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how='inner'
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))
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if overlap > 0:
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print(f"\n✅ {overlap} Ziehungen in beiden Quellen")
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# Genauigkeit
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if self.lottery_type == 'lotto':
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accuracy = ((overlap - (mismatches if 'mismatches' in locals() else 0)) / overlap * 100)
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print(f"✅ Genauigkeit: {accuracy:.1f}%")
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# Fehler
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if self.errors:
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print(f"\n❌ FEHLER ({len(self.errors)})")
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print("="*70)
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for error in self.errors:
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print(error)
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# Warnungen
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if self.warnings:
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print(f"\n⚠️ WARNUNGEN ({len(self.warnings)})")
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print("="*70)
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for warning in self.warnings:
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print(warning)
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# Ergebnis
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print(f"\n{'='*70}")
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if not self.errors:
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if self.warnings:
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print("✅ VERIFIKATION OK - Nur Warnungen")
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else:
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print("✅ VERIFIKATION ERFOLGREICH - Alle Ziehungen korrekt!")
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else:
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print("❌ VERIFIKATION FEHLGESCHLAGEN - Fehler gefunden")
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print("="*70)
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return len(self.errors) == 0
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def main():
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"""Hauptfunktion."""
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# Standard-Dateien
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files = {
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'lotto': {
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'path': '/Users/sebastianfrohlich/Library/Mobile Documents/com~apple~CloudDocs/Jupyter Notebooks/Lotto/data/AlleLottozahlen.csv',
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'type': 'lotto'
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},
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'eurojackpot': {
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'path': '/Users/sebastianfrohlich/Library/Mobile Documents/com~apple~CloudDocs/Jupyter Notebooks/AlleEurojackpotzahlen.csv',
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'type': 'eurojackpot'
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}
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}
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if len(sys.argv) > 1:
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# Einzelne Datei
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csv_file = sys.argv[1]
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lottery_type = sys.argv[2] if len(sys.argv) > 2 else 'lotto'
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verifier = DrawVerifier(csv_file, lottery_type)
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success = verifier.verify_all()
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sys.exit(0 if success else 1)
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else:
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# Beide Dateien
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print("\n🎲 Verifiziere beide Lottery-Dateien...\n")
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results = {}
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for name, config in files.items():
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if os.path.exists(config['path']):
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verifier = DrawVerifier(config['path'], config['type'])
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results[name] = verifier.verify_all()
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else:
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print(f"\n⚠️ {name.upper()}: Datei nicht gefunden")
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results[name] = False
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# Gesamtergebnis
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print("\n" + "="*70)
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print(" GESAMTERGEBNIS")
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print("="*70)
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for name, success in results.items():
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status = "✅" if success else "❌"
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print(f"{status} {name.upper()}")
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print("="*70)
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all_success = all(results.values())
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sys.exit(0 if all_success else 1)
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if __name__ == "__main__":
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main()
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