feat: apply #28B smart breakeven + #31B H1 EMA20 filter, add backtests #26-#32
Live trading optimizations (cumulative: $2,807 net, 81.8% WR, Sharpe 3.97): - #28B: Smart breakeven locks profit at entry + 0.5x ATR instead of fixed $2 - #31B: H1 Price vs EMA20 filter — BUY only when H1 bullish, SELL only when bearish Backtests #26-#32 (7 scripts testing sell improvement, regime-aware entry, confluence scoring, dynamic RR, multi-TF H1, and ML exit optimizer). Winners: #28B (+$229), #31B (+$343). Failed: #26, #27, #29, #30, #32. Also includes: web dashboard redesign, Docker setup, startup scripts. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
GifariKemal
co-authored by
Claude Opus 4.6
Claude Opus 4.6
parent
53d8cd26a2
commit
214b64945d
+59
-258
@@ -1,42 +1,21 @@
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"""
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FastAPI Backend for Web Dashboard
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=================================
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FastAPI Backend for Web Dashboard (Docker-compatible)
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=====================================================
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Serves trading bot status data to the web frontend.
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Reads from data/bot_status.json which is written by main_live.py.
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This allows the API to run in Docker without needing MT5 (Windows-only).
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"""
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import sys
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import json
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from pathlib import Path
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from datetime import datetime
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from zoneinfo import ZoneInfo
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from collections import deque
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import asyncio
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from typing import Optional
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import json
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# Add parent directory to path for imports
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sys.path.insert(0, str(Path(__file__).parent.parent.parent))
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from fastapi import FastAPI, WebSocket, WebSocketDisconnect
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from fastapi import FastAPI
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from fastapi.middleware.cors import CORSMiddleware
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from pydantic import BaseModel
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from dotenv import load_dotenv
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load_dotenv()
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# Import bot components
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try:
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from src.mt5_connector import MT5Connector
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from src.smc_polars import SMCAnalyzer
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from src.ml_model import TradingModel
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from src.regime_detector import MarketRegimeDetector
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from src.session_filter import SessionFilter
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from src.feature_eng import FeatureEngineer
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from src.config import TradingConfig
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except ImportError as e:
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print(f"Import error: {e}")
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print("Make sure you're running from the correct directory")
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app = FastAPI(title="Trading Bot API", version="1.0.0")
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app = FastAPI(title="Trading Bot API", version="2.0.0")
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# CORS for frontend
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app.add_middleware(
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@@ -47,246 +26,68 @@ app.add_middleware(
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allow_headers=["*"],
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)
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# Global state
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class BotState:
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def __init__(self):
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self.mt5: Optional[MT5Connector] = None
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self.smc: Optional[SMCAnalyzer] = None
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self.ml: Optional[TradingModel] = None
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self.hmm: Optional[MarketRegimeDetector] = None
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self.session: Optional[SessionFilter] = None
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self.feature_eng: Optional[FeatureEngineer] = None
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self.config: Optional[TradingConfig] = None
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self.connected = False
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# Status file path (mounted as volume in Docker)
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STATUS_FILE = Path("/app/data/bot_status.json")
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# History buffers
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self.price_history = deque(maxlen=120)
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self.equity_history = deque(maxlen=120)
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self.balance_history = deque(maxlen=120)
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self.logs = deque(maxlen=50)
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# Last known values
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self.last_price = 0.0
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self.last_update = None
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state = BotState()
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def add_log(level: str, message: str):
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"""Add log entry to buffer"""
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now = datetime.now(ZoneInfo("Asia/Jakarta"))
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state.logs.append({
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"time": now.strftime("%H:%M:%S"),
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"level": level,
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"message": message
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})
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@app.on_event("startup")
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async def startup():
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"""Initialize bot components on startup"""
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add_log("info", "Starting API server...")
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try:
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state.config = TradingConfig()
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state.mt5 = MT5Connector(
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login=state.config.mt5_login,
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password=state.config.mt5_password,
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server=state.config.mt5_server,
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path=state.config.mt5_path,
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)
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if state.mt5.connect():
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state.connected = True
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add_log("info", "MT5 connected successfully")
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# Initialize components
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state.smc = SMCAnalyzer()
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state.ml = TradingModel(model_path="models/xgboost_model")
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state.ml.load()
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state.hmm = MarketRegimeDetector(model_path="models/hmm_regime")
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state.hmm.load()
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state.session = SessionFilter()
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state.feature_eng = FeatureEngineer()
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add_log("info", f"ML Model loaded ({len(state.ml.feature_names)} features)")
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else:
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add_log("error", "Failed to connect to MT5")
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except Exception as e:
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add_log("error", f"Startup error: {e}")
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@app.on_event("shutdown")
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async def shutdown():
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"""Cleanup on shutdown"""
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if state.mt5:
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state.mt5.disconnect()
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add_log("info", "API server stopped")
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# Default empty response
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DEFAULT_STATUS = {
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"timestamp": "00:00:00",
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"connected": False,
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"price": 0.0,
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"spread": 0.0,
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"priceChange": 0.0,
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"priceHistory": [],
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"balance": 0.0,
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"equity": 0.0,
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"profit": 0.0,
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"equityHistory": [],
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"balanceHistory": [],
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"session": "Unknown",
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"isGoldenTime": False,
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"canTrade": False,
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"dailyLoss": 0.0,
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"dailyProfit": 0.0,
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"consecutiveLosses": 0,
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"riskPercent": 0.0,
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"smc": {"signal": "", "confidence": 0.0, "reason": ""},
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"ml": {"signal": "", "confidence": 0.0, "buyProb": 0.0, "sellProb": 0.0},
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"regime": {"name": "", "volatility": 0.0, "confidence": 0.0},
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"positions": [],
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"logs": [],
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}
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@app.get("/api/status")
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async def get_status():
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"""Get current trading status"""
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wib = ZoneInfo("Asia/Jakarta")
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now = datetime.now(wib)
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result = {
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"timestamp": now.strftime("%H:%M:%S"),
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"connected": state.connected,
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"price": 0.0,
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"spread": 0.0,
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"priceChange": 0.0,
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"priceHistory": list(state.price_history),
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"balance": 0.0,
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"equity": 0.0,
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"profit": 0.0,
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"equityHistory": list(state.equity_history),
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"balanceHistory": list(state.balance_history),
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"session": "Unknown",
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"isGoldenTime": 19 <= now.hour < 23,
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"canTrade": False,
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"dailyLoss": 0.0,
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"dailyProfit": 0.0,
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"consecutiveLosses": 0,
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"riskPercent": 0.0,
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"smc": {"signal": "", "confidence": 0.0, "reason": ""},
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"ml": {"signal": "", "confidence": 0.0, "buyProb": 0.0, "sellProb": 0.0},
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"regime": {"name": "", "volatility": 0.0, "confidence": 0.0},
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"positions": [],
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"logs": list(state.logs),
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}
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if not state.connected or not state.mt5:
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return result
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try:
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# Price
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tick = state.mt5.get_tick(state.config.symbol)
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if tick:
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price = (tick.bid + tick.ask) / 2
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spread = (tick.ask - tick.bid) * 100
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# Calculate change
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price_change = price - state.last_price if state.last_price > 0 else 0
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state.last_price = price
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# Update history
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state.price_history.append(price)
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result["price"] = price
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result["spread"] = spread
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result["priceChange"] = price_change
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result["priceHistory"] = list(state.price_history)
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# Account
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balance = state.mt5.account_balance or 0
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equity = state.mt5.account_equity or 0
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profit = equity - balance
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state.equity_history.append(equity)
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state.balance_history.append(balance)
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result["balance"] = balance
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result["equity"] = equity
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result["profit"] = profit
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result["equityHistory"] = list(state.equity_history)
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result["balanceHistory"] = list(state.balance_history)
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# Session
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if state.session:
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session_info = state.session.get_status_report()
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if session_info:
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result["session"] = session_info.get('current_session', 'Unknown')
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can_trade, _, _ = state.session.can_trade()
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result["canTrade"] = can_trade
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# Risk state from file
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risk_file = Path("data/risk_state.txt")
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if risk_file.exists():
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content = risk_file.read_text()
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for line in content.strip().split('\n'):
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if ':' in line:
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key, value = line.split(':', 1)
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key = key.strip()
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value = value.strip()
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if key == 'daily_loss':
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result["dailyLoss"] = float(value)
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elif key == 'daily_profit':
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result["dailyProfit"] = float(value)
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elif key == 'consecutive_losses':
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result["consecutiveLosses"] = int(value)
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# Calculate risk percent
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max_loss = state.config.capital * (state.config.risk.max_daily_loss / 100)
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if max_loss > 0:
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result["riskPercent"] = (result["dailyLoss"] / max_loss) * 100
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# Signals
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df = state.mt5.get_market_data(state.config.symbol, state.config.execution_timeframe, 200)
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if df is not None and len(df) > 50:
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# Feature engineering
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df = state.feature_eng.calculate_all(df, include_ml_features=True)
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df = state.smc.calculate_all(df)
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# Regime
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if state.hmm:
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df = state.hmm.predict(df)
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regime = state.hmm.get_current_state(df)
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if regime:
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result["regime"] = {
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"name": regime.regime.value.replace('_', ' ').title(),
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"volatility": regime.volatility,
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"confidence": regime.confidence,
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}
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# SMC Signal
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smc_signal = state.smc.generate_signal(df)
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if smc_signal:
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result["smc"] = {
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"signal": smc_signal.signal_type,
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"confidence": smc_signal.confidence,
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"reason": smc_signal.reason or "",
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}
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# ML Prediction
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if state.ml and state.ml.fitted:
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available_features = [f for f in state.ml.feature_names if f in df.columns]
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ml_pred = state.ml.predict(df, available_features)
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if ml_pred:
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result["ml"] = {
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"signal": ml_pred.signal,
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"confidence": ml_pred.confidence,
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"buyProb": ml_pred.probability,
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"sellProb": 1.0 - ml_pred.probability,
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}
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# Positions
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positions = state.mt5.get_open_positions(state.config.symbol)
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if positions is not None and not positions.is_empty():
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pos_list = []
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for row in positions.iter_rows(named=True):
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pos_list.append({
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"ticket": row.get('ticket', 0),
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"type": "BUY" if row.get('type', 0) == 0 else "SELL",
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"volume": row.get('volume', 0),
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"priceOpen": row.get('price_open', 0),
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"profit": row.get('profit', 0),
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})
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result["positions"] = pos_list
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state.last_update = now
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except Exception as e:
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add_log("error", f"Status error: {str(e)[:50]}")
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"""Get current trading status from bot's status file."""
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# Try local path first (non-Docker), then Docker path
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for path in [STATUS_FILE, Path("data/bot_status.json")]:
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if path.exists():
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try:
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data = json.loads(path.read_text())
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return data
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except (json.JSONDecodeError, OSError):
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continue
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# No status file — bot not running
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now = datetime.now(ZoneInfo("Asia/Jakarta"))
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result = DEFAULT_STATUS.copy()
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result["timestamp"] = now.strftime("%H:%M:%S")
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result["logs"] = [
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{
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"time": now.strftime("%H:%M:%S"),
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"level": "warning",
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"message": "Bot is not running — waiting for bot_status.json",
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}
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]
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return result
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@app.get("/api/health")
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async def health():
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"""Health check endpoint"""
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return {"status": "ok", "connected": state.connected}
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"""Health check endpoint."""
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bot_running = STATUS_FILE.exists() or Path("data/bot_status.json").exists()
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return {"status": "ok", "bot_running": bot_running}
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if __name__ == "__main__":
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@@ -1,4 +1,2 @@
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fastapi>=0.109.0
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uvicorn>=0.27.0
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python-dotenv>=1.0.0
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pydantic>=2.5.0
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uvicorn[standard]>=0.27.0
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