feat: Trading Bot V1.8 - Aggressive Mode + Infrastructure
## Major Features - Session Filter: NY-only trading (13:00-21:00 UTC) - SQLite Database: Structured trade logging - Telegram Bot: Real-time notifications (@Xausd_digger_bot) - Streamlit Dashboard: Visual monitoring & analytics - JSON Import: Historical data migration ## Infrastructure - trading_database.py: SQLite trade storage - telegram_notifier.py: Telegram integration - infrastructure_patch.py: Combined DB + Telegram - trading_dashboard.py: Real-time web dashboard - import_json_to_db.py: JSON to SQLite migration ## Session Filter (V1.8 Aggressive Mode) - session_filter_patch.py: Whitelist-based filter - Blocks: Asian, London, Overlap sessions - Active: NY session only (best performance: 47.6% WR) - Base confidence: 60% ## Documentation - V1.8_AGGRESSIVE_MODE_AKTIVIERT.md - FIX_DUPLICATE_SCHEDULER.md - DASHBOARD_WINDOWS_SERVER.md - SQLITE_TELEGRAM_SETUP.md - PROJECT_CLEANUP.md ## Cleanup - Archived old V1.1-V1.7 versions - Removed obsolete analysis scripts (replaced by dashboard) - Added .gitignore for secrets and temp files ## Breaking Changes - Requires telegram_config.json (use template) - Requires Python packages: streamlit, plotly 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
Claude
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# 🗄️📱 SQLite + Telegram Integration Guide
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**Version:** V1.8+
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**Datum:** 26. November 2025
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**Features:** Database Logging + Mobile Notifications
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---
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## 🎯 Was wird implementiert?
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### 1. **SQLite Database** 🗄️
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- Strukturiertes Trade Logging (statt JSON)
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- Schnelle Performance-Queries
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- Session/Confidence-basierte Analysen
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- Historische Datenbank
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### 2. **Telegram Notifications** 📱
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- Live Trade Entry/Exit Benachrichtigungen
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- Tägliche Performance Reports (22:00 UTC)
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- Wöchentliche Summaries (Sonntag 23:00 UTC)
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- Error Alerts
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- Bot Status Updates
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---
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## 📦 Neue Dateien
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| Datei | Beschreibung |
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|-------|--------------|
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| `trading_database.py` | SQLite Database Core |
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| `telegram_notifier.py` | Telegram Integration |
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| `infrastructure_patch.py` | Integration mit TradingBot |
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| `telegram_config.json` | Telegram Konfiguration (erstellen!) |
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| `trading_bot.db` | SQLite Database (automatisch erstellt) |
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---
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## 🚀 Setup Guide - Schritt für Schritt
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### **PHASE 1: Telegram Bot erstellen (5 Minuten)**
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#### Schritt 1.1: Bot erstellen bei @BotFather
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1. Öffne Telegram
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2. Suche nach `@BotFather`
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3. Sende `/newbot`
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4. Folge den Anweisungen:
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- Bot Name: z.B. "My Trading Bot"
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- Bot Username: z.B. "mytrading_bot" (muss auf "_bot" enden)
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5. **Kopiere den Bot Token** (z.B. `1234567890:ABCdefGHIjklMNOpqrsTUVwxyz`)
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#### Schritt 1.2: Chat ID herausfinden
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1. Suche nach `@userinfobot` in Telegram
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2. Sende `/start`
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3. **Kopiere deine User ID** (z.B. `987654321`)
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#### Schritt 1.3: Telegram Config erstellen
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Erstelle eine neue Datei `telegram_config.json`:
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```json
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{
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"bot_token": "1234567890:ABCdefGHIjklMNOpqrsTUVwxyz",
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"chat_id": "987654321",
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"notifications": {
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"trade_entry": true,
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"trade_exit": true,
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"daily_report": true,
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"weekly_report": true,
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"error_alerts": true
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},
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"daily_report_time": "22:00",
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"weekly_report_day": "Sunday"
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}
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```
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**Wichtig:** Ersetze `bot_token` und `chat_id` mit deinen echten Werten!
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#### Schritt 1.4: Bot testen
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```bash
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python telegram_notifier.py
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```
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**Erwartete Ausgabe:**
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```
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✅ Telegram Bot connected: @mytrading_bot
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✅ Created telegram_config_template.json
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```
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Wenn erfolgreich, sende eine Test-Nachricht:
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```python
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from telegram_notifier import TelegramNotifier
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notifier = TelegramNotifier(
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bot_token='YOUR_BOT_TOKEN',
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chat_id='YOUR_CHAT_ID'
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)
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notifier.send_message("🎉 Telegram Bot Test erfolgreich!")
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```
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Du solltest die Nachricht auf deinem Handy bekommen! 📱
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---
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### **PHASE 2: SQLite Database einrichten (2 Minuten)**
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#### Schritt 2.1: Database erstellen
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```bash
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python trading_database.py
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```
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**Erwartete Ausgabe:**
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```
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🗄️ TRADING DATABASE - System Check
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======================================================================
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📊 Tables created: 3
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✅ trades
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✅ performance_summary
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✅ bot_status
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📈 Overall Statistics:
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Total Trades: 0
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Win Rate: 0%
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Net Profit: $0
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======================================================================
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✅ Database ready!
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```
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#### Schritt 2.2: Existierende JSON Daten migrieren (optional)
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Wenn du bereits JSON Performance-Dateien hast:
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```python
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from trading_database import TradingDatabase
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db = TradingDatabase("trading_bot.db")
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# Migriere alle JSON Files
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import glob
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json_files = glob.glob("trade_performance_*.json")
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for json_file in json_files:
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print(f"Migrating {json_file}...")
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db.migrate_from_json(json_file)
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db.close()
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```
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#### Schritt 2.3: Database prüfen
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```python
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from trading_database import TradingDatabase
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db = TradingDatabase("trading_bot.db")
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# Zeige alle Trades
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trades = db.get_recent_trades(limit=10)
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print(f"Total trades in DB: {len(trades)}")
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# Session Performance
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session_perf = db.get_session_performance(days=30)
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for session, stats in session_perf.items():
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print(f"{session}: {stats['total_profit']} profit, {stats['win_rate']}% WR")
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db.close()
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```
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---
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### **PHASE 3: Integration mit TradingBot (10 Minuten)**
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#### Schritt 3.1: Imports hinzufügen
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**Am Anfang deines Notebooks** (nach den MT5 Imports):
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```python
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# ==========================================
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# INFRASTRUCTURE IMPORTS (NEU!)
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# ==========================================
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from infrastructure_patch import (
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TradingInfrastructure,
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create_scheduled_reports
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)
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from trading_database import TradingDatabase
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from telegram_notifier import TelegramNotifier
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```
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#### Schritt 3.2: Infrastructure initialisieren
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**Nach der MT5 Verbindung und VOR dem Scheduler**:
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```python
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# ==========================================
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# INITIALIZE INFRASTRUCTURE
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# ==========================================
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print("🔧 Initializing Infrastructure...")
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infra = TradingInfrastructure(
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db_path="trading_bot.db",
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enable_telegram=True, # Telegram aktivieren
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enable_database=True # SQLite aktivieren
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)
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# Send Bot Started Notification
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from session_filter_patch import SESSION_WHITELIST_CONFIG
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bot_config = {
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'version': 'V1.8',
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'enabled_sessions': SESSION_WHITELIST_CONFIG['enabled_sessions'],
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'base_confidence': SESSION_WHITELIST_CONFIG['base_confidence'],
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'max_risk_per_trade': SESSION_WHITELIST_CONFIG['max_risk_per_trade']
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}
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infra.send_bot_started(bot_config)
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print("✅ Infrastructure ready!")
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```
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**Du solltest jetzt auf Telegram eine "Bot Started" Nachricht bekommen!** 📱🚀
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#### Schritt 3.3: Trade Logging hinzufügen
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**Modifiziere deine `execute_trade_v2_adaptive` Funktion:**
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**VORHER** (ca. Zeile wo Position geöffnet wird):
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```python
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result = mt.order_send(request)
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if result.retcode == mt.TRADE_RETCODE_DONE:
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logger.info(f"✅ {trade_type} position opened")
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# ... existing code ...
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```
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**NACHHER** (mit Infrastructure Logging):
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```python
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result = mt.order_send(request)
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if result.retcode == mt.TRADE_RETCODE_DONE:
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logger.info(f"✅ {trade_type} position opened")
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# ==========================================
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# LOG TRADE ENTRY (NEU!)
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# ==========================================
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try:
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# Hole Position Info
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positions = mt.positions_get(symbol=symbol)
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if positions:
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position = positions[0]
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# Erstelle Trade Data
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trade_data = {
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'ticket': position.ticket,
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'position_id': position.identifier,
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'symbol': symbol,
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'strategy_name': strategy_name,
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'type': 'BUY' if trade_type == 'BUY' else 'SELL',
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'volume': volume,
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'entry_price': position.price_open,
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'sl_price': position.sl,
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'tp_price': position.tp,
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'entry_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S'),
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'session': rhythm_manager.get_current_session(),
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'regime': regime,
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'quality': quality,
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'confidence': confidence,
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'timeframe_alignment': timeframe_alignment,
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'risk_amount': risk_amount,
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'risk_pct': max_risk_per_trade
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}
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# Log to Database + Telegram
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infra.log_trade_entry(trade_data)
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except Exception as e:
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logger.error(f"⚠️ Infrastructure logging failed: {e}")
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# ==========================================
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# ... existing code continues ...
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```
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#### Schritt 3.4: Exit Logging hinzufügen
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**Wenn Trade geschlossen wird** (z.B. durch SL/TP):
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Dies hängt davon ab, wie dein Bot Exits erkennt. Falls du einen Position Monitor hast:
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```python
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# Wenn Position geschlossen wurde
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if position_closed:
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exit_data = {
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'exit_price': close_price,
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'exit_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S'),
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'duration_hours': (close_time - open_time).total_seconds() / 3600,
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'profit': profit,
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'commission': commission,
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'swap': swap,
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'net_profit': net_profit,
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'profit_pct': (net_profit / risk_amount) * 100 if risk_amount else 0,
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'rr_ratio': abs(net_profit / risk_amount) if risk_amount else 0,
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'exit_reason': 'tp' if hit_tp else 'sl' if hit_sl else 'manual'
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}
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# Log Exit
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infra.log_trade_exit(ticket, exit_data)
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```
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#### Schritt 3.5: Scheduled Reports hinzufügen
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**Nach dem Scheduler Setup**:
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```python
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# ==========================================
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# SCHEDULER SETUP (existing)
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# ==========================================
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scheduler = BackgroundScheduler()
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# ... existing jobs ...
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# ==========================================
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# ADD SCHEDULED REPORTS (NEU!)
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# ==========================================
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create_scheduled_reports(infra, scheduler)
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# Start Scheduler
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scheduler.start()
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```
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---
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### **PHASE 4: Testing (5 Minuten)**
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#### Test 1: Infrastructure Status
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```python
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# Prüfe ob alles läuft
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print("\n🔍 Infrastructure Status:")
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print(f" Database: {'✅' if infra.enable_database else '❌'}")
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print(f" Telegram: {'✅' if infra.enable_telegram else '❌'}")
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# Prüfe DB Stats
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if infra.db:
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stats = infra.db.get_overall_statistics(days=7)
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print(f"\n📊 Last 7 Days:")
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print(f" Trades: {stats.get('total_trades', 0)}")
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print(f" Win Rate: {stats.get('win_rate', 0)}%")
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print(f" Net Profit: ${stats.get('net_profit', 0):.2f}")
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```
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#### Test 2: Manual Telegram Test
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```python
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# Sende Test Notification
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if infra.telegram:
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infra.telegram.send_message("🧪 Test: Infrastructure is working!")
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```
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#### Test 3: Database Query
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```python
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# Query recent trades
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if infra.db:
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trades = infra.db.get_recent_trades(limit=5)
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print(f"\n📝 Recent Trades: {len(trades)}")
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for trade in trades:
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print(f" {trade['symbol']} {trade['type']} @ {trade['entry_price']}")
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```
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---
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## 📱 Was du auf Telegram sehen wirst
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### Bot Started (sofort)
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```
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🚀 TradingBot Started
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Version: V1.8
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Time: 2025-11-26 14:30:00 UTC
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⚙️ Configuration:
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Active Sessions: NY
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Confidence Threshold: 60%
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Max Risk/Trade: 1.0%
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✅ Bot is now monitoring the market
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```
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### Trade Entry (bei jedem Trade)
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```
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🟢 Trade Opened
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Symbol: XAUUSD
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Type: BUY
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Entry: 2650.50
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SL: 2645.50 | TP: 2660.50
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Risk: $50.00 (1.0%)
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Volume: 0.1 lots
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🇺🇸 Session: NY
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📊 Confidence: 72.5%
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🎯 Quality: EXCELLENT
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⏰ 2025-11-26 17:15:00 UTC
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```
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### Trade Exit (bei jedem Close)
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```
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✅ Trade Closed 🟢
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Symbol: XAUUSD
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Type: BUY
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Entry: 2650.50
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Exit: 2660.50
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Profit: +$100.00
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Duration: 2.5h
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Exit Reason: TP
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R:R Ratio: 2.00
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⏰ 2025-11-26 19:45:00 UTC
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```
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### Daily Report (täglich 22:00 UTC)
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```
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📊 Daily Trading Report
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📅 2025-11-26
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━━━━━━━━━━━━━━━━━━━━
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Trades: 3
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Wins: 2 | Losses: 1
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🎯 Win Rate: 66.7%
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💰 Net Profit: $150.00
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Gross Profit: $200.00
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Gross Loss: $-50.00
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Avg Trade: $50.00
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━━━━━━━━━━━━━━━━━━━━
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✅ Bot Status: Running
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```
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### Weekly Report (Sonntag 23:00 UTC)
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```
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📈 Weekly Trading Report
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📅 2025-11-20 to 2025-11-26
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━━━━━━━━━━━━━━━━━━━━
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📊 Overall Performance
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Total Trades: 21
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Wins: 10 | Losses: 11
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Win Rate: 47.6%
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💰 Net Profit: $660.00
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🟢 Profit Factor: 1.85
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Avg Trade: $31.43
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━━━━━━━━━━━━━━━━━━━━
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📍 Session Performance
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🇺🇸 NY: +$660.00 (47.6% WR) ✅
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━━━━━━━━━━━━━━━━━━━━
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✅ Bot Status: Running
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```
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---
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## 🔍 Nützliche Database Queries
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### Query 1: Session Performance (letzte 30 Tage)
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```python
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from trading_database import TradingDatabase
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db = TradingDatabase("trading_bot.db")
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session_perf = db.get_session_performance(days=30)
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for session, stats in session_perf.items():
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print(f"{session.upper()}:")
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print(f" Trades: {stats['count']}")
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print(f" Win Rate: {stats['win_rate']}%")
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print(f" Profit: ${stats['total_profit']:.2f}")
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print()
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```
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### Query 2: Confidence Analysis
|
||||
```python
|
||||
conf_analysis = db.get_confidence_analysis(days=30)
|
||||
|
||||
for conf_range, stats in conf_analysis.items():
|
||||
print(f"Confidence {conf_range}:")
|
||||
print(f" Trades: {stats['count']}")
|
||||
print(f" Win Rate: {stats['win_rate']}%")
|
||||
print(f" Profit: ${stats['total_profit']:.2f}")
|
||||
print()
|
||||
```
|
||||
|
||||
### Query 3: Best/Worst Trades
|
||||
```python
|
||||
# Best Trades
|
||||
db.cursor.execute("""
|
||||
SELECT symbol, type, entry_price, exit_price, net_profit, session
|
||||
FROM trades
|
||||
WHERE status = 'closed'
|
||||
ORDER BY net_profit DESC
|
||||
LIMIT 5
|
||||
""")
|
||||
|
||||
print("🏆 Top 5 Trades:")
|
||||
for row in db.cursor.fetchall():
|
||||
print(f" {row['symbol']} {row['type']}: ${row['net_profit']:.2f} ({row['session']})")
|
||||
|
||||
# Worst Trades
|
||||
db.cursor.execute("""
|
||||
SELECT symbol, type, entry_price, exit_price, net_profit, session
|
||||
FROM trades
|
||||
WHERE status = 'closed'
|
||||
ORDER BY net_profit ASC
|
||||
LIMIT 5
|
||||
""")
|
||||
|
||||
print("\n💔 Bottom 5 Trades:")
|
||||
for row in db.cursor.fetchall():
|
||||
print(f" {row['symbol']} {row['type']}: ${row['net_profit']:.2f} ({row['session']})")
|
||||
|
||||
db.close()
|
||||
```
|
||||
|
||||
### Query 4: Daily Breakdown
|
||||
```python
|
||||
db.cursor.execute("""
|
||||
SELECT
|
||||
DATE(entry_time) as date,
|
||||
COUNT(*) as trades,
|
||||
SUM(CASE WHEN net_profit > 0 THEN 1 ELSE 0 END) as wins,
|
||||
ROUND(SUM(net_profit), 2) as daily_profit
|
||||
FROM trades
|
||||
WHERE status = 'closed'
|
||||
AND entry_time >= datetime('now', '-30 days')
|
||||
GROUP BY DATE(entry_time)
|
||||
ORDER BY date DESC
|
||||
""")
|
||||
|
||||
print("📅 Daily Performance (Last 30 Days):")
|
||||
for row in db.cursor.fetchall():
|
||||
print(f" {row['date']}: {row['trades']} trades, {row['wins']} wins, ${row['daily_profit']}")
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 🛠️ Troubleshooting
|
||||
|
||||
### Problem 1: Telegram nicht verbunden
|
||||
**Symptom:** `❌ Telegram connection failed`
|
||||
|
||||
**Lösung:**
|
||||
1. Prüfe `telegram_config.json` existiert
|
||||
2. Prüfe Bot Token ist korrekt
|
||||
3. Prüfe Chat ID ist korrekt
|
||||
4. Teste mit: `python telegram_notifier.py`
|
||||
|
||||
### Problem 2: Database locked
|
||||
**Symptom:** `database is locked`
|
||||
|
||||
**Lösung:**
|
||||
```python
|
||||
# Stelle sicher nur eine Connection offen ist
|
||||
db.close()
|
||||
|
||||
# ODER: Benutze Context Manager
|
||||
with TradingDatabase("trading_bot.db") as db:
|
||||
# queries...
|
||||
pass # automatisch geschlossen
|
||||
```
|
||||
|
||||
### Problem 3: Keine Notifications
|
||||
**Symptom:** Bot läuft, aber keine Telegram Nachrichten
|
||||
|
||||
**Lösung:**
|
||||
1. Prüfe `infra.enable_telegram` ist `True`
|
||||
2. Sende Test-Nachricht manuell
|
||||
3. Prüfe Bot ist nicht von @BotFather blockiert
|
||||
4. Starte eine Konversation mit deinem Bot (sende `/start`)
|
||||
|
||||
### Problem 4: Alte Trades nicht in DB
|
||||
**Symptom:** Database zeigt 0 Trades
|
||||
|
||||
**Lösung:**
|
||||
```python
|
||||
# Migriere JSON Daten
|
||||
from infrastructure_patch import TradingInfrastructure
|
||||
|
||||
infra = TradingInfrastructure()
|
||||
infra.migrate_json_files(".") # Migriert alle JSON Files
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 📊 Performance Vorteile
|
||||
|
||||
### Vorher (nur JSON):
|
||||
- ❌ Schwer zu analysieren
|
||||
- ❌ Manuelle Performance-Berechnung
|
||||
- ❌ Keine Live Updates
|
||||
- ❌ Keine Session-Analyse
|
||||
|
||||
### Nachher (SQLite + Telegram):
|
||||
- ✅ Instant Queries
|
||||
- ✅ Automatische Reports
|
||||
- ✅ Mobile Benachrichtigungen
|
||||
- ✅ Session/Confidence Analytics
|
||||
- ✅ Historische Datenbank
|
||||
|
||||
---
|
||||
|
||||
## 🎯 Nächste Schritte
|
||||
|
||||
### Nach erfolgreicher Integration:
|
||||
|
||||
1. **1 Woche monitoren:**
|
||||
- Prüfe tägliche Telegram Reports
|
||||
- Verifiziere Database logging
|
||||
- Teste Queries
|
||||
|
||||
2. **Performance analysieren:**
|
||||
```python
|
||||
# Nach 1 Woche
|
||||
stats = infra.get_performance_summary(days=7)
|
||||
print(stats)
|
||||
```
|
||||
|
||||
3. **Optional - Custom Queries:**
|
||||
- Erstelle eigene Performance-Metriken
|
||||
- Exportiere Daten für Excel/Charts
|
||||
- Backtesting mit historischen Daten
|
||||
|
||||
4. **Phase 2 Features** (später):
|
||||
- Position Scaling basierend auf Confidence
|
||||
- ML Signal Filter
|
||||
- Multi-Symbol Support
|
||||
|
||||
---
|
||||
|
||||
## ✅ Checklist - Ist alles fertig?
|
||||
|
||||
- [ ] Telegram Bot erstellt (@BotFather)
|
||||
- [ ] Chat ID erhalten (@userinfobot)
|
||||
- [ ] `telegram_config.json` erstellt mit echten Werten
|
||||
- [ ] `python telegram_notifier.py` läuft ohne Fehler
|
||||
- [ ] `python trading_database.py` erstellt DB
|
||||
- [ ] Alte JSON Daten migriert (optional)
|
||||
- [ ] Infrastructure im Notebook initialisiert
|
||||
- [ ] Trade Entry Logging hinzugefügt
|
||||
- [ ] Trade Exit Logging hinzugefügt (wenn möglich)
|
||||
- [ ] Scheduled Reports aktiviert
|
||||
- [ ] Test-Trade durchgeführt → Telegram Notification erhalten
|
||||
- [ ] Database Query funktioniert
|
||||
- [ ] Bot auf VPS deployed
|
||||
|
||||
---
|
||||
|
||||
## 🎉 Zusammenfassung
|
||||
|
||||
Mit **SQLite + Telegram** hast du jetzt:
|
||||
|
||||
🗄️ **Strukturierte Datenbank** für alle Trades
|
||||
📱 **Live Mobile Notifications** für jeden Trade
|
||||
📊 **Automatische Performance Reports** täglich & wöchentlich
|
||||
🔍 **Schnelle Analytics** mit SQL Queries
|
||||
📈 **Historische Daten** für Backtesting
|
||||
⚠️ **Error Alerts** wenn etwas schief geht
|
||||
|
||||
**V1.8 ist jetzt eine professionelle Trading-Platform!** 🚀
|
||||
|
||||
Bei Fragen oder Problemen: Check Troubleshooting oder frag nach! 💪
|
||||
Reference in New Issue
Block a user