support update data to mysql
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@ -53,7 +53,7 @@ MONITOR_CONFIG = {
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"symbols": ["XCH-USDT", "BTC-USDT", "ETH-USDT", "SOL-USDT", "DOGE-USDT",
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"XCH-USDT-SWAP", "BTC-USDT-SWAP", "ETH-USDT-SWAP", "SOL-USDT-SWAP", "DOGE-USDT-SWAP"],
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"intervals": ["5m", "15m", "1H", "4H", "1D"],
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"initial_date": "2025-07-01 00:00:00"
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"initial_date": "2025-05-01 00:00:00"
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},
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"price_monitor":{
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"symbols": ["XCH-USDT"],
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@ -4,7 +4,7 @@ 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
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logging.basicConfig(level=logging.INFO, format='%(asctime)s %(levelname)s: %(message)s')
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class DataMonitor:
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@ -29,9 +29,10 @@ class DataMonitor:
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:param end_time: 结束时间（毫秒级timestamp），默认当前时间
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:return: pd.DataFrame
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"""
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from core.utils import datetime_to_timestamp
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if symbol is None:
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symbol = "XCH-USDT"
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if bar is None:
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bar = "5m"
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if end_time is None:
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end_time = int(time.time() * 1000) # 当前时间（毫秒）
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# 处理start参数
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@ -59,12 +60,10 @@ class DataMonitor:
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while start_time < end_time:
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try:
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# after，真实逻辑是获得指定时间之前的数据 ！！！
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response = self.market_api.get_history_candlesticks(
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instId=symbol,
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after=end_time, # 获取指定时间之前的数据,
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bar=bar,
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limit=str(limit)
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)
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response = self.get_data_from_api(symbol, end_time, bar, limit)
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if response is None:
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logging.warning(f"请求失败，请稍后再试")
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break
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if response["code"] != "0" or not response["data"]:
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logging.warning(f"请求失败或无数据: {response.get('msg', 'No message')}")
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break
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@ -82,10 +81,10 @@ class DataMonitor:
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break
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from_time_str = pd.to_datetime(from_time, unit='ms', utc=True).tz_convert('Asia/Shanghai')
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to_time_str = pd.to_datetime(to_time, unit='ms', utc=True).tz_convert('Asia/Shanghai')
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logging.info(f"已获取 {len(candles)} 条数据，从: {from_time_str} 到: {to_time_str}")
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logging.info(f"已获取{symbol}, 周期：{bar} {len(candles)} 条数据，从: {from_time_str} 到: {to_time_str}")
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if from_time < start_time:
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start_time_str = pd.to_datetime(start_time, unit='ms', utc=True).tz_convert('Asia/Shanghai')
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logging.warning(f"本轮获取数据最早时间 {from_time_str} 早于 此次数据获取起始时间 {start_time_str}， 停止获取数据")
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logging.warning(f"本轮获取{symbol}, {bar} 数据最早时间 {from_time_str} 早于 此次数据获取起始时间 {start_time_str}， 停止获取数据")
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# candels中仅保留start_time之后的数据
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candles = [candle for candle in candles if int(candle[0]) >= start_time]
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all_data.extend(candles)
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@ -94,7 +93,7 @@ class DataMonitor:
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# 更新 end_time 为本次请求中最早的时间戳
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end_time = from_time - 1 # 减 1 毫秒以避免重复
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all_data.extend(candles)
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time.sleep(0.2)
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time.sleep(0.5)
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except Exception as e:
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logging.error(f"请求出错: {e}")
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break
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@ -116,7 +115,39 @@ class DataMonitor:
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df.sort_values('timestamp', inplace=True)
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df.reset_index(drop=True, inplace=True)
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logging.info(f"总计获取 {len(df)} 条 K 线数据（仅confirm=1）")
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# 获取df中date_time的最早时间与最新时间
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earliest_time = df['date_time'].min()
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latest_time = df['date_time'].max()
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logging.info(f"本轮更新{symbol}, {bar} 数据最早时间: {earliest_time}， 最新时间: {latest_time}")
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return df
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else:
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logging.warning("未获取到数据")
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logging.warning(f"未获取到{symbol}, {bar} 最新数据，请稍后再试")
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return None
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def get_data_from_api(self, symbol, end_time, bar, limit):
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response = None
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count = 0
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while True:
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try:
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response = self.market_api.get_history_candlesticks(
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instId=symbol,
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after=end_time, # 获取指定时间之前的数据,
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bar=bar,
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limit=str(limit)
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)
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if response:
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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(10)
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return response
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def get_data_from_db(self, symbol, bar, db_url):
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sql = """
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SELECT * FROM crypto_market_data
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WHERE symbol = :symbol AND bar = :bar
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ORDER BY timestamp DESC
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LIMIT 1"""
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@ -1,8 +1,9 @@
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import pandas as pd
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from sqlalchemy import create_engine, exc, text
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import logging
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from core.utils import transform_data_type
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def save_market_data_to_mysql(df: pd.DataFrame, db_url: str):
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def insert_market_data_to_mysql(df: pd.DataFrame, db_url: str):
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"""
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将K线行情数据保存到MySQL的crypto_market_data表
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:param df: K线数据DataFrame
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@ -54,3 +55,51 @@ def save_market_data_to_mysql(df: pd.DataFrame, db_url: str):
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logging.info("数据已成功写入数据库。")
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except Exception as e:
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logging.error(f'数据库连接或写入失败: {e}')
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def query_latest_data(symbol: str, bar: str, db_url: str):
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"""
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查询最新数据
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:param symbol: 交易对
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:param bar: K线周期
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:param db_url: 数据库连接URL
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"""
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sql = """
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SELECT * FROM crypto_market_data
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WHERE symbol = :symbol AND bar = :bar
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ORDER BY timestamp DESC
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LIMIT 1
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"""
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condition_dict = {"symbol": symbol, "bar": bar}
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return query(sql, condition_dict, db_url, return_multi=False)
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def query(sql: str, condition_dict: dict, db_url: str, return_multi: bool = True):
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"""
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查询数据
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:param sql: 查询SQL
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:param db_url: 数据库连接URL
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"""
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try:
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engine = create_engine(db_url)
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with engine.connect() as conn:
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result = conn.execute(text(sql), condition_dict)
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if return_multi:
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result = result.fetchall()
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if result:
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result_list = [transform_data_type(dict(row._mapping)) for row in result]
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return result_list
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else:
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return None
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else:
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result = result.fetchone()
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if result:
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result_dict = transform_data_type(dict(result._mapping))
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return result_dict
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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'查询数据出错: {e}')
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return None
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@ -1,4 +1,5 @@
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from datetime import datetime, timezone, timedelta
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from decimal import Decimal
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def datetime_to_timestamp(date_str: str) -> int:
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"""
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@ -18,3 +19,12 @@ def timestamp_to_datetime(timestamp: int) -> str:
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"""
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dt = datetime.fromtimestamp(timestamp / 1000, timezone(timedelta(hours=8)))
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return dt.strftime('%Y-%m-%d %H:%M:%S')
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def transform_data_type(data: dict):
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"""
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遍历字典，将所有Decimal类型的值转换为float类型
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"""
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for key, value in data.items():
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if isinstance(value, Decimal):
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data[key] = float(value)
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return data
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@ -1,7 +1,7 @@
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import logging
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from time import sleep
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from core.data_monitor import DataMonitor
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from core.db_manager import save_market_data_to_mysql
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from core.db_manager import insert_market_data_to_mysql, query_latest_data
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from config import API_KEY, SECRET_KEY, PASSPHRASE, SANDBOX, \
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MONITOR_CONFIG, MYSQL_CONFIG
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@ -29,16 +29,54 @@ class MonitorMain:
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self.db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}"
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def initial_data(self):
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"""
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初始化数据
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"""
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for symbol in self.symbols:
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for interval in self.intervals:
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latest_data = query_latest_data(symbol, interval, self.db_url)
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if latest_data:
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logging.info(f"已初始化{symbol}, {interval} 最新数据，请使用update_data()更新数据")
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continue
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self.fetch_save_data(symbol, interval, self.initial_date)
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def fetch_save_data(self, symbol: str, interval: str, start: str):
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"""
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获取保存数据
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"""
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data = self.data_monitor.get_historical_kline_data(symbol=symbol,
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start=self.initial_date,
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start=start,
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bar=interval)
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save_market_data_to_mysql(data, self.db_url)
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if data is not None and len(data) > 0:
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insert_market_data_to_mysql(data, self.db_url)
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def update_data(self):
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"""
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更新数据
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1. 获取最新数据
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2. 获取最新数据的时间戳
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3. 根据最新数据的时间戳，获取最新数据
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4. 将最新数据保存到数据库
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"""
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for symbol in self.symbols:
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for interval in self.intervals:
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latest_data = query_latest_data(symbol, interval, self.db_url)
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if not latest_data:
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self.fetch_save_data(symbol, interval, self.initial_date)
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continue
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else:
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latest_timestamp = latest_data.get("timestamp")
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if latest_timestamp:
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latest_timestamp = int(latest_timestamp)
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else:
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logging.warning(f"获取{symbol}, {interval} 最新数据失败")
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continue
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self.fetch_save_data(symbol, interval, latest_timestamp + 1)
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if __name__ == "__main__":
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monitor_main = MonitorMain()
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# monitor_main.update_data()
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monitor_main.initial_data()
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