moen0
107 lines
3.2 KiB
Python
107 lines
3.2 KiB
Python
from fastapi import FastAPI
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from fastapi.middleware.cors import CORSMiddleware
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from data.loader import load_candles, resample_candles
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from indicators.market_structure import find_swing_points, detect_structure
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from indicators.liquidity import find_liquidity_levels
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from indicators.fvg import find_fvgs
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from indicators.order_blocks import find_order_blocks
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import sys
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import os
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sys.path.insert(0, os.path.dirname(os.path.dirname(__file__)))
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app = FastAPI()
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_methods=["*"],
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allow_headers=["*"],
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)
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@app.get("/api/candles")
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def get_candles(timeframe: int = 5):
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candles_1m = load_candles("data/data.csv")
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candles = resample_candles(candles_1m, period=timeframe)
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return {
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"candles": [
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{
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"time": c.time_open.isoformat(),
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"open": c.open,
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"high": c.high,
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"low": c.low,
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"close": c.close
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}
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for c in candles
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]
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}
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@app.get("/api/indicators")
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def get_indicators(timeframe: int = 5):
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candles_1m = load_candles("data/data.csv")
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candles = resample_candles(candles_1m, period=timeframe)
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swings = find_swing_points(candles)
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structure = detect_structure(swings)
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levels = find_liquidity_levels(swings)
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fvgs = find_fvgs(candles)
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obs = find_order_blocks(candles, structure)
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candle_times = [c.time_open.isoformat() for c in candles]
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return {
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"candle_times": candle_times,
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"swings": swings,
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"structure": structure,
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"liquidity": levels,
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"fvgs": fvgs,
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"order_blocks": obs
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}
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@app.get("/api/backtest")
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def get_backtest(timeframe: int = 5, rr: float = 2.5):
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candles_1m = load_candles("data/data.csv")
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candles = resample_candles(candles_1m, period=timeframe)
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from strategies.ict_strategy import ICTStrategy
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strategy = ICTStrategy(
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session="london",
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lookback=7,
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ob_max_age=50,
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atr_mult=2.5,
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use_liquidity_sweep=True,
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sweep_lookback=5,
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)
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from engine.backtester import run_backtest
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trades = run_backtest(candles, strategy, 10000, risk_reward=rr)
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candle_times = [c.time_open.isoformat() for c in candles]
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trades_data = []
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for t in trades:
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trades_data.append({
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"enter_time": t.enter_time.isoformat(),
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"exit_time": t.exit_time.isoformat(),
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"enter_price": t.enter_price,
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"exit_price": t.exit_price,
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"direction": t.direction,
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"pnl": t.pnl,
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})
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total_pnl = sum(t.pnl for t in trades)
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winners = [t for t in trades if t.pnl > 0]
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losers = [t for t in trades if t.pnl <= 0]
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return {
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"trades": trades_data,
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"candle_times": candle_times,
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"stats": {
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"total_trades": len(trades),
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"winners": len(winners),
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"losers": len(losers),
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"win_rate": len(winners) / len(trades) * 100 if trades else 0,
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"total_pnl": total_pnl,
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"avg_win": sum(t.pnl for t in winners) / len(winners) if winners else 0,
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"avg_loss": sum(t.pnl for t in losers) / len(losers) if losers else 0,
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"risk_reward": rr,
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}
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} |