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updae for datetime

This commit is contained in:
blade 2025-09-16 14:31:15 +08:00
parent e29b1cef51
commit 1963d2720b
22 changed files with 226 additions and 62 deletions
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17
auto_schedule.py
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@ -1,20 +1,27 @@
import schedule
import time
import datetime
from core.utils import get_current_date_time
import core.logger as logging
import subprocess
import os
import sys
logger = logging.logger
# 定义要执行的任务
def run_script():
start_time = time.time()
logger.info(f"Executing script at: {datetime.datetime.now()}")
logger.info(f"Executing script at: {get_current_date_time()}")
output_file = r'./output/auto_schedule.txt'
with open(output_file, 'a') as f:
f.write(f"Task ran at {datetime.datetime.now()}\n")
python_path = r"D:\miniconda3\envs\okx\python.exe"
script_path = r"D:\python_projects\crypto_quant\monitor_schedule.py"
f.write(f"Task ran at {get_current_date_time()}\n")
current_dir = os.getcwd()
python_path = sys.executable
if current_dir.endswith('crypto_quant'):
script_path = r'./monitor_schedule.py'
elif current_dir.endswith(r'python_projects'):
script_path = f'{current_dir}/crypto_quant/monitor_schedule.py'
else:
script_path = f'{current_dir}/monitor_schedule.py'
subprocess.run([python_path, script_path])
end_time = time.time()
logger.info(f"Script execution time: {end_time - start_time} seconds")

17
auto_update_market_data.py
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@ -1,20 +1,27 @@
import schedule
import time
import datetime
from core.utils import get_current_date_time
import core.logger as logging
import subprocess
import os
import sys
logger = logging.logger
# 定义要执行的任务
def run_script():
start_time = time.time()
logger.info(f"Executing script at: {datetime.datetime.now()}")
logger.info(f"Executing script at: {get_current_date_time()}")
output_file = r'./output/auto_schedule.txt'
with open(output_file, 'a') as f:
f.write(f"Task ran at {datetime.datetime.now()}\n")
python_path = r"D:\miniconda3\envs\okx\python.exe"
script_path = r"D:\python_projects\crypto_quant\huge_volume_main.py"
f.write(f"Task ran at {get_current_date_time()}\n")
python_path = sys.executable
current_dir = os.getcwd()
if current_dir.endswith('crypto_quant'):
script_path = r'./huge_volume_main.py'
elif current_dir.endswith(r'python_projects'):
script_path = f'{current_dir}/crypto_quant/huge_volume_main.py'
else:
script_path = f'{current_dir}/huge_volume_main.py'
subprocess.run([python_path, script_path])
end_time = time.time()
logger.info(f"Script execution time: {end_time - start_time} seconds")

5
config.py
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@ -12,6 +12,11 @@ SECRET_KEY = "F7AD69272FBF7C44E69CC110D2EDDB7A"
PASSPHRASE = "Bengbu!2001"
SANDBOX = False
# API_KEY = "12d911b6-f28a-4595-b177-70cb8fbdc369"
# SECRET_KEY = "C32DF88A975EE08631D0BE6B6B5A33E7"
# PASSPHRASE = "Bengbu@2001"
# SANDBOX = False
# 模拟盘API密钥配置
# API_KEY = "f309e789-3497-4ed3-896f-d18bdc4d9817"
# SECRET_KEY = "9152809391B110E2E647FDE12A37E96D"

5
core/biz/huge_volume_chart.py
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@ -7,7 +7,8 @@ from openpyxl import Workbook
from openpyxl.drawing.image import Image
from PIL import Image as PILImage
import core.logger as logging
from datetime import datetime
from datetime import datetime, timezone, timedelta
from core.utils import get_current_date_time
import pandas as pd
import os
import re
@ -403,7 +404,7 @@ class HugeVolumeChart:
}
"""
logger.info(f"输出Excel文件，包含所有{chart_type}图表")
file_name = f"huge_volume_{chart_type}_{datetime.now().strftime('%Y%m%d%H%M%S')}.xlsx"
file_name = f"huge_volume_{chart_type}_{get_current_date_time()}.xlsx"
file_path = os.path.join(self.output_folder, file_name)
# Create Excel file and worksheet

86
core/biz/market_data.py
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@ -1,12 +1,17 @@
import time
from datetime import datetime, timedelta
from datetime import datetime, timedelta, timezone
from core.utils import get_current_date_time
from typing import Optional
import pandas as pd
import requests
import json
import okx.MarketData as Market
import okx.TradingData as TradingData
from core.utils import transform_date_time_to_timestamp, timestamp_to_datetime
from core.biz.market_data_from_itick import MarketDataFromItick
import core.logger as logging
import sys
logger = logging.logger
@ -23,9 +28,18 @@ class MarketData:
self.passphrase = passphrase
self.market_api = Market.MarketAPI(
api_key=api_key, api_secret_key=secret_key, passphrase=passphrase,
flag=self.flag
flag=self.flag,
)
self.is_us_stock = is_us_stock
# 当前操作系统是windows还是linux
self.is_windows = sys.platform == "win32"
if not self.is_us_stock:
# 如果当前操作系统是windows，则is_binance为False，否则为True
# 因为LINUX服务器，目前访问不了欧易的API
if self.is_windows:
self.is_binance = False
else:
self.is_binance = True
# self.trade_api = TradingData.TradingDataAPI(
# api_key=api_key, api_secret_key=secret_key, passphrase=passphrase,
@ -48,11 +62,21 @@ class MarketData:
if end_time is None:
logger.error(f"end_time参数解析失败: {end_time}")
return None
response = self.get_realtime_candlesticks_from_api(symbol, bar, end_time, limit)
if self.is_binance:
if symbol == "XCH-USDT":
return None
response = self.get_realtime_candlesticks_from_binance(symbol, bar, end_time, limit)
else:
response = self.get_realtime_candlesticks_from_api(symbol, bar, end_time, limit)
if response:
candles = response["data"]
from_time = int(candles[-1][0])
to_time = int(candles[0][0])
if self.is_binance:
from_time = int(candles[0][0])
to_time = int(candles[-1][0])
else:
from_time = int(candles[-1][0])
to_time = int(candles[0][0])
from_time_str = pd.to_datetime(from_time, unit='ms', utc=True).tz_convert('Asia/Shanghai')
to_time_str = pd.to_datetime(to_time, unit='ms', utc=True).tz_convert('Asia/Shanghai')
logger.info(f"已获取{symbol}, 周期：{bar} {len(candles)} 条数据，从: {from_time_str} 到: {to_time_str}")
@ -68,7 +92,7 @@ class MarketData:
candles_pd['symbol'] = symbol
# 添加bar列，内容为bar
candles_pd['bar'] = bar
candles_pd['create_time'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
candles_pd['create_time'] = get_current_date_time()
candles_pd = candles_pd[['symbol', 'bar', 'timestamp', 'date_time', 'open', 'high', 'low', 'close', 'volume', 'volCcy', 'volCCyQuote', 'create_time']]
candles_pd.sort_values('timestamp', inplace=True)
candles_pd.reset_index(drop=True, inplace=True)
@ -197,7 +221,7 @@ class MarketData:
df['symbol'] = symbol
# 添加bar列，内容为bar
df['bar'] = bar
df['create_time'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
df['create_time'] = get_current_date_time()
if self.is_us_stock:
# 如果是美股数据，则仅保留date_time_us字中，在开盘时间内的数据，即开盘时间为美国时间9:30到16:00
@ -280,6 +304,54 @@ class MarketData:
time.sleep(10)
return response
def get_realtime_candlesticks_from_binance(self, symbol, bar, end_time, limit):
# API 端点：币安现货 K 线数据
base_url = "https://api.binance.com"
endpoint = "/api/v3/klines"
params = {
"symbol": symbol.replace("-", ""),
"interval": bar,
"limit": limit
}
response = None
count = 0
data = None
while True:
try:
# 发送 GET 请求
response = requests.get(base_url + endpoint, params=params)
if response.status_code == 200:
data = response.json()
break
except Exception as e:
logger.error(f"请求出错: {e}")
count += 1
if count > 3:
break
time.sleep(10)
if data:
# 每条数据格式：[开盘时间, 开盘价, 最高价, 最低价, 收盘价, 成交量, 收盘时间, 报价成交量, 成交笔数, 主动买入成交量, 主动买入报价成交量, 忽略]
columns = ["timestamp", "open", "high", "low", "close", "volume", "volCcy", "volCCyQuote", "confirm"]
data_list = []
# [开盘时间, 开盘价, 最高价, 最低价, 收盘价, 成交量, 报价成交量, 是否收盘]
for record in data:
record = [
int(record[6]),
float(record[1]),
float(record[2]),
float(record[3]),
float(record[4]),
float(record[5]),
float(record[7]),
float(record[7]),
"1"
]
data_list.append(record)
return {"data": data_list}
else:
logger.warning(f"未获取到{symbol}, {bar} 最新数据，请稍后再试")
return None
def get_realtime_candlesticks_from_api(self, symbol, bar, end_time, limit):
response = None
count = 0

2
core/biz/market_data_from_itick.py
View File

@ -63,7 +63,7 @@ class MarketDataFromItick:
# 设置默认时间范围
if end_time is None:
end_time = int(datetime.now().strftime('%Y-%m-%d %H:%M:%S').timestamp())
end_time = int(datetime.now().timestamp())
if isinstance(end_time, str):
end_time = int(datetime.strptime(end_time, '%Y-%m-%d %H:%M:%S').timestamp())
self.end_time = end_time

3
core/biz/market_monitor.py
View File

@ -16,6 +16,7 @@ def create_metrics_report(
only_output_huge_volume: bool = False,
only_output_rise: bool = False,
now_datetime_str: str = None,
is_binance: bool = False,
):
"""
创建指标报告
@ -61,6 +62,8 @@ def create_metrics_report(
brief = f"{symbol} {bar} 量率: {volume_ratio} {change}: {pct_chg}% 异动 价: {close}"
else:
brief = f"{symbol} {bar} 量率: {volume_ratio} {change}: {pct_chg}% 价: {close}"
if is_binance:
brief += " 币安"
if huge_volume == 1:
contents.append(f"## {brief} 交易巨量报告")

5
core/biz/strategy.py
View File

@ -1,5 +1,6 @@
import time
from datetime import datetime
from datetime import datetime, timezone, timedelta
from core.utils import get_current_date_time
import core.logger as logging
from typing import Optional
import pandas as pd
@ -177,7 +178,7 @@ class QuantStrategy:
logger.info(f"开始运行{strategy}策略，间隔{interval}秒")
while True:
try:
logger.info(datetime.now().strftime('%Y-%m-%d %H:%M:%S'))
logger.info(get_current_date_time())
try:
self.quant_trader.get_account_balance()
except Exception as e:

5
core/biz/trade_data.py
View File

@ -1,5 +1,6 @@
import time
from datetime import datetime, timedelta
from datetime import datetime, timedelta, timezone
from core.utils import get_current_date_time
from typing import Optional
import pandas as pd
import okx.MarketData as Market
@ -87,7 +88,7 @@ class TradeData:
df.rename(columns={"instId": "symbol"}, inplace=True)
df["date_time"] = df["ts"].apply(lambda x: timestamp_to_datetime(x))
df["tradeId"] = df["tradeId"].astype(str)
df["create_time"] = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
df["create_time"] = get_current_date_time()
df = df[["symbol", "ts", "date_time", "tradeId", "side", "sz", "px", "create_time"]]
self.db_trade_data.insert_data_to_mysql(df)

5
core/db/db_manager.py
View File

@ -1,6 +1,7 @@
import pandas as pd
from sqlalchemy import create_engine, exc, text
import re, datetime
import re
from core.utils import get_current_date_time
import core.logger as logging
from core.utils import transform_data_type
@ -12,7 +13,7 @@ class DBData:
):
self.table_name = table_name
self.temp_table_name = (
f"temp_{table_name}_{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}"
f"temp_{table_name}_{get_current_date_time()}"
)
self.columns = columns
if self.columns is None:

8
core/logger.py
View File

@ -12,11 +12,11 @@ class Logger:
# log文件存储路径
current_dir = os.getcwd()
if current_dir.endswith('crypto_quant'):
output_folder = r'./output/log/'
elif current_dir.startswith(r'/root/'):
output_folder = r'/root/crypto_quant/output/log/'
output_folder = f'{current_dir}/output/log/'
elif current_dir.endswith(r'python_projects'):
output_folder = f'{current_dir}/crypto_quant/output/log/'
else:
output_folder = r'./output/log/'
output_folder = f'{current_dir}/output/log/'
os.makedirs(output_folder, exist_ok=True)
# add self._log_filename to be adata_yyyyMMddHHmm.log
self._log_filename = os.path.join(output_folder, 'crypto_monitor_{}.log'.format(time.strftime("%Y%m%d%H%M%S", time.localtime())))

5
core/statistics/price_volume_stats.py
View File

@ -4,7 +4,8 @@ import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from datetime import datetime
from datetime import datetime, timezone, timedelta
from core.utils import get_current_date_time
import re
from openpyxl import Workbook
from openpyxl.drawing.image import Image
@ -41,7 +42,7 @@ class PriceVolumeStats:
self.initial_date = OKX_MONITOR_CONFIG.get("volume_monitor", {}).get(
"initial_date", "2025-05-15 00:00:00"
)
self.end_date = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
self.end_date = get_current_date_time()
self.window_size = 100
self.stats_output_dir = "./output/statistics/excel/"
os.makedirs(self.stats_output_dir, exist_ok=True)

7
core/trade/ma_break_statistics.py
View File

@ -4,7 +4,8 @@ import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from datetime import datetime, timedelta
from datetime import datetime, timedelta, timezone
from core.utils import get_current_date_time
import re
import json
from openpyxl import Workbook
@ -81,7 +82,7 @@ class MaBreakStatistics:
self.db_market_data = DBMarketData(self.db_url)
if len(self.initial_date) > 10:
self.initial_date = self.initial_date[:10]
self.end_date = datetime.now().strftime("%Y-%m-%d")
self.end_date = get_current_date_time()
self.trade_strategy_config = self.get_trade_strategy_config()
self.main_strategy = self.trade_strategy_config.get("均线系统策略", None)
@ -233,7 +234,7 @@ class MaBreakStatistics:
)
latest_market_date_time = ma_break_market_data["end_date_time"].max()
if latest_market_date_time is None:
latest_market_date_time = datetime.now().strftime("%Y%m%d")
latest_market_date_time = get_current_date_time()
latest_market_date_time = re.sub(
r"[\:\-\s]", "", str(latest_market_date_time)
)

7
core/utils.py
View File

@ -74,3 +74,10 @@ def transform_date_time_to_timestamp(date_time: int | str):
except Exception as e:
logger.error(f"start参数解析失败: {e}")
return None
def get_current_date_time() -> str:
"""
获取当前日期时间
"""
return datetime.now(timezone(timedelta(hours=8))).strftime("%Y-%m-%d %H:%M:%S")

22
huge_volume_main.py
View File

@ -4,7 +4,7 @@ from core.db.db_market_data import DBMarketData
from core.db.db_huge_volume_data import DBHugeVolumeData
from core.db.db_binance_data import DBBinanceData
from core.db.db_binance_huge_volume_data import DBBinanceHugeVolumeData
from core.utils import timestamp_to_datetime, transform_date_time_to_timestamp
from core.utils import timestamp_to_datetime, transform_date_time_to_timestamp, get_current_date_time
from market_data_main import MarketDataMain
from core.wechat import Wechat
import core.logger as logging
@ -15,7 +15,7 @@ from config import (
WINDOW_SIZE,
BINANCE_MONITOR_CONFIG,
)
from datetime import datetime, timedelta
from datetime import datetime, timedelta, timezone
import pandas as pd
import os
import re
@ -108,7 +108,7 @@ class HugeVolumeMain:
)
if end is None:
end = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
end = get_current_date_time()
logger.info(
f"开始处理巨量交易数据: {symbol} {bar} 窗口大小: {window_size} 从 {start} 到 {end}"
)
@ -344,7 +344,7 @@ class HugeVolumeMain:
is_update=True,
)
logger.info(
f"更新巨量交易数据: {symbol} {bar} 窗口大小: {window_size} 从 {earliest_date_time} 到 {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}"
f"更新巨量交易数据: {symbol} {bar} 窗口大小: {window_size} 从 {earliest_date_time} 到 {get_current_date_time()}"
)
if data is not None and len(data) > 0:
logger.info(f"此次更新巨量交易数据: {len(data)}条")
@ -352,7 +352,7 @@ class HugeVolumeMain:
logger.info(f"此次更新巨量交易数据为空")
except Exception as e:
logger.error(
f"更新巨量交易数据失败: {symbol} {bar} 窗口大小: {window_size} 到 {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}: {e}"
f"更新巨量交易数据失败: {symbol} {bar} 窗口大小: {window_size} 到 {get_current_date_time()}: {e}"
)
def get_seconds_by_bar(self, bar: str):
@ -413,7 +413,7 @@ class HugeVolumeMain:
"initial_date", "2025-05-01 00:00:00"
)
if end is None:
end = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
end = get_current_date_time()
periods_text = ", ".join([str(period) for period in periods])
logger.info(
f"开始计算巨量出现后，之后{periods_text}个周期，上涨或下跌的比例: {symbol} {bar} 窗口大小: {window_size} 从 {start} 到 {end}"
@ -473,7 +473,7 @@ class HugeVolumeMain:
"initial_date", "2025-05-01 00:00:00"
)
if end is None:
end = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
end = get_current_date_time()
start_timestamp = transform_date_time_to_timestamp(start)
end_timestamp = transform_date_time_to_timestamp(end)
@ -582,7 +582,7 @@ class HugeVolumeMain:
"initial_date", "2025-05-01 00:00:00"
)
if end is None:
end = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
end = get_current_date_time()
huge_volume_data_list = []
result_data_list = []
window_size_list = WINDOW_SIZE.get("window_sizes", None)
@ -606,7 +606,7 @@ class HugeVolumeMain:
if output_excel:
total_huge_volume_data = total_huge_volume_data.reset_index(drop=True)
total_result_data = total_result_data.reset_index(drop=True)
current_date = datetime.now().strftime("%Y%m%d%H%M%S")
current_date = get_current_date_time()
file_name = f"next_periods_rise_or_fall_{current_date}.xlsx"
try:
with pd.ExcelWriter(
@ -687,10 +687,10 @@ def test_import_binance_data_by_csv():
def test_send_huge_volume_data_to_wechat():
huge_volume_main = HugeVolumeMain(threshold=2.0)
# 获得昨天日期
yesterday = (datetime.now() - timedelta(days=1)).strftime("%Y-%m-%d")
yesterday = (datetime.now(timezone(timedelta(hours=8))) - timedelta(days=1)).strftime("%Y-%m-%d")
logger.info(f"昨天日期: {yesterday}")
# 获得今天日期
today = datetime.now().strftime("%Y-%m-%d")
today = datetime.now(timezone(timedelta(hours=8))).strftime("%Y-%m-%d")
logger.info(f"今天日期: {today}")
huge_volume_main.send_huge_volume_data_to_wechat(start=yesterday, end=today)

5
market_data_from_itick_main.py
View File

@ -2,8 +2,7 @@ import requests
import core.logger as logging
from datetime import datetime, timedelta
from futu import KLType
from core.utils import get_current_date_time
logger = logging.logger
@ -41,7 +40,7 @@ def main():
logger.info(f"成功下载 {len(processed_data)} 条数据")
# 保存数据
filename = f"{symbol}_{interval}_{datetime.now().strftime('%Y%m%d_%H%M%S')}.csv"
filename = f"{symbol}_{interval}_{get_current_date_time()}.csv"
market_data_from_futu.save_to_csv(filename)
# 显示数据统计

5
market_data_main.py
View File

@ -1,5 +1,6 @@
import core.logger as logging
from datetime import datetime, timedelta, timezone
from core.utils import get_current_date_time
from time import sleep
import pandas as pd
from core.biz.market_data import MarketData
@ -107,7 +108,7 @@ class MarketDataMain:
"""
获取保存数据
"""
end_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
end_time = get_current_date_time()
end_time_ts = transform_date_time_to_timestamp(end_time)
if end_time_ts is None:
logger.error(f"结束时间格式错误: {end_time}")
@ -225,7 +226,7 @@ class MarketDataMain:
data['date_time'] = dt_series.dt.strftime('%Y-%m-%d %H:%M:%S')
dt_us_series = pd.to_datetime(data['timestamp'].astype(int), unit='ms', utc=True, errors='coerce').dt.tz_convert('America/New_York')
data['date_time_us'] = dt_us_series.dt.strftime('%Y-%m-%d %H:%M:%S')
data['create_time'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
data['create_time'] = get_current_date_time()
data["date_time"] = data["date_time"].astype(str)
data["date_time_us"] = data["date_time_us"].astype(str)

20
market_monitor_main.py
View File

@ -9,8 +9,9 @@ from core.utils import timestamp_to_datetime, transform_date_time_to_timestamp
import core.logger as logging
import os
import sys
import pandas as pd
from datetime import datetime, timedelta
from datetime import datetime, timedelta, timezone
import json
import re
@ -42,6 +43,15 @@ class MarketMonitorMain:
self.db_market_monitor = DBMarketMonitor(self.db_url)
# 当前操作系统是windows还是linux
self.is_windows = sys.platform == "win32"
# 如果当前操作系统是windows，则is_binance为False，否则为True
# 因为LINUX服务器，目前访问不了欧易的API
if self.is_windows:
self.is_binance = False
else:
self.is_binance = True
def get_latest_record(self):
"""
获取最新记录
@ -71,8 +81,8 @@ class MarketMonitorMain:
监控最新市场数据
考虑到速度，暂不与数据库交互，直接从api获取数据
"""
# 获得当前时间字符串
now_datetime = datetime.now()
# 获得当前时间字符串，转为北京时间
now_datetime = datetime.now(timezone(timedelta(hours=8)))
now_datetime_str = now_datetime.strftime("%Y-%m-%d %H:%M:%S")
end_time = transform_date_time_to_timestamp(now_datetime_str)
real_time_data = self.market_data_main.market_data.get_realtime_kline_data(
@ -174,6 +184,7 @@ class MarketMonitorMain:
only_output_huge_volume,
only_output_rise,
now_datetime_str,
self.is_binance,
)
text_length = len(report.encode("utf-8"))
@ -268,6 +279,9 @@ class MarketMonitorMain:
only_output_rise: bool = True,
):
for symbol in self.market_data_main.symbols:
if self.is_binance and symbol == "XCH-USDT":
logger.info(f"币安交易所无: {symbol}")
continue
for bar in self.market_data_main.bars:
logger.info(
f"开始监控: {symbol} {bar} 窗口大小: {self.window_size} 行情数据"

7
orb_trade_main.py
View File

@ -1,7 +1,8 @@
from core.trade.orb_trade import ORBStrategy
from config import US_STOCK_MONITOR_CONFIG, OKX_MONITOR_CONFIG, BINANCE_MONITOR_CONFIG
import core.logger as logging
from datetime import datetime
from datetime import datetime, timezone, timedelta
from core.utils import get_current_date_time
from openpyxl import Workbook
from openpyxl.drawing.image import Image
import openpyxl
@ -27,7 +28,7 @@ def main():
start_date = start_date[:10]
else:
start_date = "2024-01-01"
end_date = datetime.now().strftime("%Y-%m-%d")
end_date = get_current_date_time()
# 原值 盈利目标倍数（默认10倍$R，即10R）
profit_target_multiple = 10
@ -120,7 +121,7 @@ def main():
statitics_dict = statistics_summary(total_trades_summary_df)
output_excel_folder = r"./output/trade_sandbox/orb_strategy/excel/summary/"
os.makedirs(output_excel_folder, exist_ok=True)
now_str = datetime.now().strftime("%Y%m%d%H%M%S")
now_str = get_current_date_time()
excel_file_name = f"orb_strategy_summary_{now_str}.xlsx"
output_file_path = os.path.join(output_excel_folder, excel_file_name)
with pd.ExcelWriter(output_file_path) as writer:

2
requirements.txt
View File

@ -10,3 +10,5 @@ schedule >= 1.2.2
xlsxwriter >= 3.2.5
openpyxl >= 3.1.5
cryptography >= 3.4.8
mplfinance
schedule

39
test_binance.py Normal file
View File

@ -0,0 +1,39 @@
import requests
import json
from datetime import datetime
# API 端点：币安现货 K 线数据
base_url = "https://api.binance.com"
endpoint = "/api/v3/klines"
# 参数设置
symbol = "ETHUSDT" # 交易对：ETH-USDT
interval = "5m" # 时间间隔：5 分钟
limit = 100 # 获取最近 100 条 K 线（可根据需要调整，最大 1000）
params = {
"symbol": symbol,
"interval": interval,
"limit": limit
}
# 发送 GET 请求
response = requests.get(base_url + endpoint, params=params)
# 检查响应状态
if response.status_code == 200:
data = response.json()
# 输出最近 5 条 K 线数据作为示例（每条数据格式：[开盘时间, 开盘价, 最高价, 最低价, 收盘价, 成交量, 收盘时间, 报价成交量, 成交笔数, 主动买入成交量, 主动买入报价成交量, 忽略]）
print("最近 5 条 5 分钟 K 线数据 (ETH-USDT):")
print(json.dumps(data[-5:], indent=4, ensure_ascii=False))
# 可选：转换为更易读的格式
print("\n转换为易读格式（时间为 UTC）：")
for kline in data[-5:]:
open_time = datetime.fromtimestamp(kline[0] / 1000).strftime('%Y-%m-%d %H:%M:%S')
close_time = datetime.fromtimestamp(kline[6] / 1000).strftime('%Y-%m-%d %H:%M:%S')
print(f"时间: {open_time} - {close_time}, "
f"开: {kline[1]}, 高: {kline[2]}, 低: {kline[3]}, 收: {kline[4]}, 量: {kline[5]}")
else:
print(f"请求失败，状态码: {response.status_code}, 错误信息: {response.text}")

7
trade_sandbox_main.py
View File

@ -5,7 +5,8 @@ import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from matplotlib.ticker import PercentFormatter
from datetime import datetime
from datetime import datetime, timezone, timedelta
from core.utils import get_current_date_time
import re
from openpyxl import Workbook
from openpyxl.drawing.image import Image
@ -68,7 +69,7 @@ class MeanReversionSandboxMain:
stat_data = self.statistic_data(total_data)
excel_save_path = os.path.join(self.save_path, solution, "excel")
os.makedirs(excel_save_path, exist_ok=True)
date_time_str = datetime.now().strftime("%Y%m%d%H%M%S")
date_time_str = get_current_date_time()
excel_file_path = os.path.join(
excel_save_path, f"{solution}_{date_time_str}.xlsx"
)
@ -301,7 +302,7 @@ class MeanReversionSandboxMain:
if __name__ == "__main__":
start_date = "2025-05-15 00:00:00"
end_date = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
end_date = get_current_date_time()
solution_list = ["solution_3"]
mean_reversion_sandbox_main = MeanReversionSandboxMain(
start_date=start_date, end_date=end_date, window_size=100, only_5m=True, solution_list=solution_list