feat: trading bot MVP — ICT Order Block + Liquidity Sweep strategy
Full-stack trading bot with: - FastAPI backend with ICT strategy (Order Block + Liquidity Sweep detection) - Backtester engine with rolling window, spread simulation, and performance metrics - Hybrid market data service (yfinance + TwelveData with rate limiting + SQLite cache) - Simulated exchange for paper trading - React/TypeScript frontend with TradingView lightweight-charts v5 - Live dashboard with candlestick chart, OHLC legend, trade markers - Backtest page with configurable parameters, equity curve, and trade table - WebSocket support for real-time updates - Bot runner with asyncio loop for automated trading Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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171
backend/app/core/exchange/oanda.py
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171
backend/app/core/exchange/oanda.py
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from datetime import datetime, timezone
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from typing import Optional
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import pandas as pd
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from oandapyV20 import API
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from oandapyV20.endpoints import accounts, instruments, orders, trades, pricing
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from app.core.config import settings
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from app.core.exchange.base import (
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AbstractExchange,
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AccountInfo,
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OpenTrade,
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OrderResult,
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)
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# Granularités OANDA valides
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GRANULARITIES = {
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"M1", "M5", "M15", "M30",
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"H1", "H2", "H4", "H6", "H8", "H12",
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"D", "W", "M",
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}
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# Nombre max de candles par requête OANDA
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MAX_CANDLES_PER_REQUEST = 5000
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def _parse_time(ts: str) -> datetime:
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"""Parse RFC3339 timestamp OANDA → datetime UTC."""
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return datetime.fromisoformat(ts.replace("Z", "+00:00"))
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class OandaExchange(AbstractExchange):
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def __init__(self) -> None:
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env = "practice" if settings.oanda_environment == "practice" else "live"
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self._client = API(
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access_token=settings.oanda_api_key,
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environment=env,
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)
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self._account_id = settings.oanda_account_id
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async def get_candles(
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self,
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instrument: str,
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granularity: str = "H1",
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count: int = 200,
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from_time: Optional[datetime] = None,
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to_time: Optional[datetime] = None,
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) -> pd.DataFrame:
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if granularity not in GRANULARITIES:
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raise ValueError(f"Granularité invalide: {granularity}. Valides: {GRANULARITIES}")
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params: dict = {"granularity": granularity, "price": "M"}
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if from_time and to_time:
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params["from"] = from_time.strftime("%Y-%m-%dT%H:%M:%SZ")
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params["to"] = to_time.strftime("%Y-%m-%dT%H:%M:%SZ")
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else:
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params["count"] = min(count, MAX_CANDLES_PER_REQUEST)
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r = instruments.InstrumentsCandles(instrument, params=params)
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self._client.request(r)
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candles = r.response.get("candles", [])
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rows = []
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for c in candles:
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if c.get("complete", True):
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mid = c["mid"]
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rows.append({
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"time": _parse_time(c["time"]),
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"open": float(mid["o"]),
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"high": float(mid["h"]),
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"low": float(mid["l"]),
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"close": float(mid["c"]),
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"volume": int(c.get("volume", 0)),
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})
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df = pd.DataFrame(rows)
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if not df.empty:
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df.sort_values("time", inplace=True)
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df.reset_index(drop=True, inplace=True)
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return df
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async def place_order(
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self,
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instrument: str,
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units: float,
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stop_loss: float,
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take_profit: float,
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) -> OrderResult:
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data = {
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"order": {
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"type": "MARKET",
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"instrument": instrument,
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"units": str(int(units)),
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"stopLossOnFill": {"price": f"{stop_loss:.5f}"},
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"takeProfitOnFill": {"price": f"{take_profit:.5f}"},
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"timeInForce": "FOK",
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}
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}
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r = orders.OrderCreate(self._account_id, data=data)
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self._client.request(r)
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resp = r.response
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fill = resp.get("orderFillTransaction") or resp.get("relatedTransactionIDs", {})
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trade_id = resp.get("orderFillTransaction", {}).get("tradeOpened", {}).get("tradeID", "unknown")
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entry_price = float(resp.get("orderFillTransaction", {}).get("price", 0))
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direction = "buy" if units > 0 else "sell"
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return OrderResult(
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trade_id=trade_id,
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instrument=instrument,
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direction=direction,
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units=abs(units),
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entry_price=entry_price,
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stop_loss=stop_loss,
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take_profit=take_profit,
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opened_at=datetime.now(timezone.utc),
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)
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async def close_trade(self, trade_id: str) -> float:
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r = trades.TradeClose(self._account_id, tradeID=trade_id)
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self._client.request(r)
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pnl = float(r.response.get("orderFillTransaction", {}).get("pl", 0))
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return pnl
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async def get_open_trades(self) -> list[OpenTrade]:
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r = trades.OpenTrades(self._account_id)
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self._client.request(r)
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result = []
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for t in r.response.get("trades", []):
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units = float(t["currentUnits"])
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direction = "buy" if units > 0 else "sell"
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sl = float(t.get("stopLoss", {}).get("price", 0)) if t.get("stopLoss") else 0.0
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tp = float(t.get("takeProfit", {}).get("price", 0)) if t.get("takeProfit") else 0.0
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result.append(OpenTrade(
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trade_id=t["id"],
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instrument=t["instrument"],
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direction=direction,
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units=abs(units),
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entry_price=float(t["price"]),
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stop_loss=sl,
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take_profit=tp,
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unrealized_pnl=float(t.get("unrealizedPL", 0)),
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opened_at=_parse_time(t["openTime"]),
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))
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return result
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async def get_account_info(self) -> AccountInfo:
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r = accounts.AccountSummary(self._account_id)
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self._client.request(r)
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acc = r.response["account"]
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return AccountInfo(
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balance=float(acc["balance"]),
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nav=float(acc["NAV"]),
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unrealized_pnl=float(acc.get("unrealizedPL", 0)),
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currency=acc.get("currency", "USD"),
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)
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async def get_price(self, instrument: str) -> float:
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r = pricing.PricingInfo(
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self._account_id,
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params={"instruments": instrument},
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)
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self._client.request(r)
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prices = r.response.get("prices", [])
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if not prices:
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raise ValueError(f"Aucun prix pour {instrument}")
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bid = float(prices[0]["bids"][0]["price"])
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ask = float(prices[0]["asks"][0]["price"])
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return (bid + ask) / 2
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