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@@ -5,14 +5,25 @@ import pymysql
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import backtrader as bt
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import backtrader.indicators as btind
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import datetime
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+import math
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import threading
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from datetime import datetime as dt
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import multiprocessing as mp
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from backtrader.feeds import PandasData
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-
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+import os
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# import multiprocessing
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import matplotlib
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+cpu_count = os.cpu_count()
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+os_name = os.name
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+if os_name == 'posix':
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+ path = '/Users/daniel/Documents/策略穷举2.csv'
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+else:
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+ path = 'D:\\BackTrader\\策略穷举0105。csv'
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+
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+
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+
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+
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class MyPandasData(PandasData):
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lines = ('change_pct', 'net_amount_main', 'net_pct_main', 'net_amount_xl', 'net_pct_xl', 'net_amount_l', 'net_pct_l'
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, 'net_amount_m', 'net_pct_m', 'net_amount_s', 'net_pct_s',)
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@@ -216,7 +227,8 @@ if __name__ == '__main__':
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for num in range(20, 180, 10):
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for Volatility in range(10, 20, 1):
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for rate in range(5, 20, 1):
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- step = 400
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+ #获得cpu数量，计算进程数
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+ step = math.ceil(len(table_list)/cpu_count/100)*100
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thread_list = []
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result = mp.Manager().list()
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result_change = mp.Manager().list()
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@@ -255,4 +267,4 @@ if __name__ == '__main__':
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print('每轮耗时：', endtime-stattime)
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edtime = dt.now()
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print('总耗时：', edtime - sttime)
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- df.to_csv('/Users/daniel/Documents/策略穷举2.csv', index=True)
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+ df.to_csv(path, index=True)
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