121 lines
4.6 KiB
Python
121 lines
4.6 KiB
Python
import time
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from datetime import datetime, timedelta
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import logging
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from typing import Optional
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import pandas as pd
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import okx.MarketData as Market
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from core.utils import datetime_to_timestamp, timestamp_to_datetime
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from core.db_trade_data import DBTradeData
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logging.basicConfig(level=logging.INFO, format='%(asctime)s %(levelname)s: %(message)s')
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class TradeData:
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def __init__(self,
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api_key: str,
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secret_key: str,
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passphrase: str,
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sandbox: bool = True,
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db_url: str = None):
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flag = "1" if sandbox else "0" # 0:实盘环境 1:沙盒环境
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self.market_api = Market.MarketAPI(
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api_key=api_key, api_secret_key=secret_key, passphrase=passphrase,
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flag=flag
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)
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self.db_url = db_url
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self.db_trade_data = DBTradeData(self.db_url)
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def get_history_trades(self, symbol: str, start_ts: int, end_ts: int, limit: int = 100):
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"""
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获取历史交易数据
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:param symbol: 交易对
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:param start_ts: 起始时间（毫秒级timestamp）
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:param end_ts: 结束时间（毫秒级timestamp）
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:param limit: 每次请求数量
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:return: pd.DataFrame
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symbol-USDT）。
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tradeId：交易ID。
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px：交易价格（如USDT）。
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sz：交易数量（如BTC数量）。
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side：交易方向（buy表示买入，sell表示卖出）
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ts：交易时间戳（成交时间，Unix时间戳的毫秒数格式， 如1597026383085）。
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"""
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try:
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all_trades = []
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after = end_ts # 从较晚时间开始（OKX的after表示更早的数据）
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while True:
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count = 0
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while True:
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try:
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result = self.market_api.get_history_trades(
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instId=symbol, # 交易对，如BTC-USDT
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type=2,
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limit=str(limit), # 每次最大返回100条
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after=str(after) # 获取更早的数据
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)
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if result:
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break
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except Exception as e:
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logging.error(f"请求出错: {e}")
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count += 1
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if count > 3:
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break
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time.sleep(3)
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if result["code"] != "0":
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print(f"Error: {result['msg']}")
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break
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trades = result["data"]
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if not trades:
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break
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from_time = int(trades[-1]["ts"])
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to_time = int(trades[0]["ts"])
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from_date_time = timestamp_to_datetime(from_time)
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to_date_time = timestamp_to_datetime(to_time)
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logging.info(f"获得交易数据，最早时间: {from_date_time}， 最近时间: {to_date_time}")
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df = pd.DataFrame(trades)
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# 过滤时间范围
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df["ts"] = df["ts"].astype(int)
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df = df[(df["ts"] >= start_ts) & (df["ts"] <= end_ts)]
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# set sz, px 为float
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df["sz"] = df["sz"].astype(float)
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df["px"] = df["px"].astype(float)
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# 将instId重命名为symbol
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df.rename(columns={"instId": "symbol"}, inplace=True)
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df["date_time"] = df["ts"].apply(lambda x: timestamp_to_datetime(x))
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df["tradeId"] = df["tradeId"].astype(str)
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df["create_time"] = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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df = df[["symbol", "ts", "date_time", "tradeId", "side", "sz", "px", "create_time"]]
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self.db_trade_data.insert_data_to_mysql(df)
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all_trades.append(df)
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# 检查最近时间戳是否超出范围
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if from_time <= start_ts:
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break
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after = from_time - 1 # 更新after，继续获取更早的数据
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time.sleep(0.5)
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if len(all_trades) > 0:
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# 转换为DataFrame
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final_df = pd.concat(all_trades)
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if final_df.empty:
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print("No trades found in the specified time range.")
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return None
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else:
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return final_df
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else:
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return None
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except Exception as e:
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logging.error(f"获取历史交易数据失败: {e}")
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return None
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