mirror of
https://github.com/xavierchuan/FX-ML-Trading-Engine.git
synced 2026-08-14 09:28:06 +00:00
Add files via upload
This commit is contained in:
xiaochuan
@@ -0,0 +1,257 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import time
|
||||
from datetime import datetime
|
||||
from typing import Dict, Any, Optional, Sequence
|
||||
import pandas as pd
|
||||
from queue import Queue
|
||||
import threading
|
||||
from loguru import logger
|
||||
|
||||
from oandapyV20 import API
|
||||
try:
|
||||
from oandapyV20.endpoints.pricing import PricingStream as OandaPricingStream
|
||||
except ImportError: # pragma: no cover
|
||||
OandaPricingStream = None # type: ignore
|
||||
|
||||
from .base import DataFeed, MarketDataEvent
|
||||
|
||||
def _normalize_instrument(symbol: str) -> str:
|
||||
"""规范化交易品种名称"""
|
||||
s = symbol.upper().replace(" ", "").replace("/", "_").replace("-", "_")
|
||||
if "_" in s and len(s) == 7:
|
||||
return s
|
||||
stripped = s.replace("_", "")
|
||||
if len(stripped) == 6:
|
||||
return f"{stripped[:3]}_{stripped[3:]}"
|
||||
return s
|
||||
|
||||
class OANDADataFeed(DataFeed):
|
||||
"""
|
||||
OANDA数据源实现
|
||||
提供实时和历史市场数据
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
instrument: str,
|
||||
timeframe: str,
|
||||
account_id: str,
|
||||
access_token: str,
|
||||
environment: str = "practice",
|
||||
reconnect_wait: float = 5.0,
|
||||
log_heartbeat: bool = False
|
||||
):
|
||||
super().__init__(instrument, timeframe)
|
||||
self.account_id = account_id
|
||||
self.access_token = access_token
|
||||
self.environment = environment
|
||||
self.reconnect_wait = reconnect_wait
|
||||
self.log_heartbeat = log_heartbeat
|
||||
|
||||
self.client = API(access_token=access_token, environment=environment)
|
||||
self._stop = threading.Event()
|
||||
self._thread: Optional[threading.Thread] = None
|
||||
self._callback = None
|
||||
self._latest_data = None
|
||||
self._loop: Optional[asyncio.AbstractEventLoop] = None
|
||||
|
||||
async def get_historical_data(
|
||||
self,
|
||||
start: datetime,
|
||||
end: datetime,
|
||||
**kwargs
|
||||
) -> pd.DataFrame:
|
||||
"""获取历史数据
|
||||
|
||||
Args:
|
||||
start: 开始时间
|
||||
end: 结束时间
|
||||
**kwargs: 额外参数，支持：
|
||||
- granularity: str, 时间周期 (如 "H1", "D")
|
||||
- count: int, 返回的K线数量
|
||||
|
||||
Returns:
|
||||
DataFrame包含以下列：datetime, open, high, low, close, volume
|
||||
"""
|
||||
from oandapyV20 import API
|
||||
import oandapyV20.endpoints.instruments as instruments
|
||||
|
||||
granularity = kwargs.get("granularity", self.timeframe)
|
||||
price = kwargs.get("price", "M")
|
||||
|
||||
# OANDA 的单次请求有最大返回数限制（例如 5000 candles），对长区间需要分段请求
|
||||
MAX_CANDLES = 5000
|
||||
|
||||
# 估算每个candle的时间长度（秒），支持常见的granularity
|
||||
def granularity_seconds(g: str) -> int:
|
||||
if g.endswith('H'):
|
||||
return int(g[:-1]) * 3600
|
||||
if g.endswith('D'):
|
||||
return int(g[:-1]) * 86400 if g[:-1].isdigit() else 86400
|
||||
if g.endswith('M') and len(g) > 1 and g[0].isdigit():
|
||||
# 例如 M1, M5 (分钟)
|
||||
return int(g[1:]) * 60 if g[0] == 'M' else 30
|
||||
# 默认按小时处理
|
||||
return 3600
|
||||
|
||||
step_seconds = granularity_seconds(granularity) * MAX_CANDLES
|
||||
|
||||
all_data = []
|
||||
current_start = pd.to_datetime(start)
|
||||
end_ts = pd.to_datetime(end)
|
||||
|
||||
while current_start < end_ts:
|
||||
current_end = current_start + pd.Timedelta(seconds=step_seconds)
|
||||
if current_end > end_ts:
|
||||
current_end = end_ts
|
||||
|
||||
params = {
|
||||
"from": current_start.strftime("%Y-%m-%dT%H:%M:%S.000000Z"),
|
||||
"to": current_end.strftime("%Y-%m-%dT%H:%M:%S.000000Z"),
|
||||
"granularity": granularity,
|
||||
"price": price
|
||||
}
|
||||
|
||||
request = instruments.InstrumentsCandles(
|
||||
instrument=self.instrument,
|
||||
params=params
|
||||
)
|
||||
|
||||
try:
|
||||
response = self.client.request(request)
|
||||
candles = response.get("candles", [])
|
||||
|
||||
for candle in candles:
|
||||
if candle.get("complete"):
|
||||
all_data.append({
|
||||
"datetime": pd.to_datetime(candle["time"]),
|
||||
"open": float(candle["mid"]["o"]),
|
||||
"high": float(candle["mid"]["h"]),
|
||||
"low": float(candle["mid"]["l"]),
|
||||
"close": float(candle["mid"]["c"]),
|
||||
"volume": int(candle.get("volume", 0))
|
||||
})
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"获取历史数据失败: {str(e)}")
|
||||
raise
|
||||
|
||||
# 推进起点
|
||||
current_start = current_end
|
||||
|
||||
if not all_data:
|
||||
return pd.DataFrame()
|
||||
|
||||
df = pd.DataFrame(all_data)
|
||||
df.drop_duplicates(subset=["datetime"], inplace=True)
|
||||
df.sort_values(by="datetime", inplace=True)
|
||||
df.set_index("datetime", inplace=True)
|
||||
return df
|
||||
|
||||
async def get_latest_data(self) -> Dict[str, Any]:
|
||||
"""获取最新数据"""
|
||||
return self._latest_data if self._latest_data else {}
|
||||
|
||||
async def subscribe(self, callback) -> None:
|
||||
"""订阅实时数据"""
|
||||
self._callback = callback
|
||||
self._loop = asyncio.get_running_loop()
|
||||
if not self._thread or not self._thread.is_alive():
|
||||
self._start_stream()
|
||||
|
||||
async def unsubscribe(self) -> None:
|
||||
"""取消订阅"""
|
||||
self._stop.set()
|
||||
if self._thread:
|
||||
self._thread.join(timeout=2.0)
|
||||
self._loop = None
|
||||
logger.info("[OANDA] Pricing stream stopped.")
|
||||
|
||||
def _start_stream(self) -> None:
|
||||
"""启动价格流"""
|
||||
if self._thread and self._thread.is_alive():
|
||||
return
|
||||
self._stop.clear()
|
||||
self._thread = threading.Thread(target=self._run_stream, daemon=True)
|
||||
self._thread.start()
|
||||
logger.info(
|
||||
f"[OANDA] Pricing stream started for {self.instrument} (account={self.account_id})"
|
||||
)
|
||||
|
||||
def _run_stream(self) -> None:
|
||||
"""运行价格流"""
|
||||
if OandaPricingStream is None:
|
||||
raise RuntimeError(
|
||||
"oandapyV20.endpoints.pricing.PricingStream is unavailable. "
|
||||
"Ensure oandapyV20 is installed."
|
||||
)
|
||||
params = {"instruments": self.instrument}
|
||||
while not self._stop.is_set():
|
||||
request = OandaPricingStream(
|
||||
accountID=self.account_id,
|
||||
params=params
|
||||
)
|
||||
try:
|
||||
for msg in self.client.request(request):
|
||||
if self._stop.is_set():
|
||||
break
|
||||
self._handle_msg(msg)
|
||||
except Exception as exc:
|
||||
if self._stop.is_set():
|
||||
break
|
||||
logger.warning(
|
||||
f"[OANDA] Pricing stream error: {exc}. "
|
||||
f"Reconnecting in {self.reconnect_wait}s"
|
||||
)
|
||||
time.sleep(self.reconnect_wait)
|
||||
|
||||
def _handle_msg(self, msg: dict) -> None:
|
||||
"""处理价格消息"""
|
||||
msg_type = msg.get("type")
|
||||
if msg_type == "HEARTBEAT":
|
||||
if self.log_heartbeat:
|
||||
logger.debug(f"[OANDA] Heartbeat {msg.get('time')}")
|
||||
return
|
||||
|
||||
if msg_type != "PRICE":
|
||||
logger.debug(f"[OANDA] Skip message type={msg_type}")
|
||||
return
|
||||
|
||||
try:
|
||||
bids = msg.get("bids")
|
||||
asks = msg.get("asks")
|
||||
if not bids or not asks:
|
||||
return
|
||||
|
||||
bid = float(bids[0]["price"])
|
||||
ask = float(asks[0]["price"])
|
||||
timestamp = pd.to_datetime(msg["time"]).to_pydatetime()
|
||||
|
||||
self._latest_data = {
|
||||
"bid": bid,
|
||||
"ask": ask,
|
||||
"timestamp": timestamp,
|
||||
"mid": (bid + ask) / 2
|
||||
}
|
||||
|
||||
if self._callback and self._loop:
|
||||
event = MarketDataEvent(
|
||||
instrument=self.instrument,
|
||||
timestamp=timestamp,
|
||||
data=self._latest_data
|
||||
)
|
||||
try:
|
||||
coro = self._callback(event)
|
||||
if asyncio.iscoroutine(coro):
|
||||
asyncio.run_coroutine_threadsafe(coro, self._loop)
|
||||
else:
|
||||
self._loop.call_soon_threadsafe(self._callback, event)
|
||||
except RuntimeError as exc:
|
||||
logger.warning(f"[OANDA] Failed to dispatch callback: {exc}")
|
||||
elif self._callback and not self._loop:
|
||||
logger.warning("[OANDA] Callback set but event loop missing; dropping tick")
|
||||
|
||||
except Exception as exc:
|
||||
logger.warning(f"[OANDA] Malformed price message: {msg} ({exc})")
|
||||
Reference in New Issue
Block a user