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four ways to load data and it's different time
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if your data is large,pandasDirectData maybe more suit for you.from __future__ import (absolute_import, division, print_function, unicode_literals) import time import datetime # For datetime objects import os.path # To manage paths import sys # To find out the script name (in argv[0]) import pickle import inspect import pandas as pd # Import the backtrader platform import backtrader as bt from backtrader.comminfo import ComminfoFuturesPercent,ComminfoFuturesFixed from backtrader.metabase import findbases,MetaBase # Create a Stratey class YunStrategy(bt.Strategy): author = "yunjinqi" params = (("look_back_days",60),("hold_days",30),) def log(self, txt, dt=None): ''' Logging function for this strategy''' dt = dt or self.datas[0].datetime.date(0) print('%s, %s' % (dt.isoformat(), txt)) def __init__(self): # Keep a reference to the "close" line in the data[0] dataseries self.bar_num =0 self.ma = bt.indicators.SMA(period = self.p.look_back_days) def next(self): self.bar_num+=1 if self.bar_num % self.p.look_back_days == 0: # self.log("开仓日,当前收盘价为：{}".format(self.datas[0].close[0])) # self.log("当前数据的长度为:{}".format(len(self.datas[0]))) # self.log("data._name is {}".format(self.datas[0]._name)) # self.log("DataSeries : getwriterinfo :{}".format(self.datas[0].getwriterinfo())) # self.log("DataSeries : getwriterheaders :{}".format(self.datas[0].getwriterheaders())) # self.log("DataSeries : getwritervalues :{}".format(self.datas[0].getwritervalues())) # self.log("findbases :self.datas[0].__class__:{},something:{} ".format(self.datas[0].__class__, # inspect.getmembers(self.datas[0].__class__, inspect.isclass))) # self.log("lines:{} ".format(self.datas[0].lines.__dir__)) # self.log("strategy:{}".format(inspect.getmembers(self.__class__, inspect.isclass))) # self.log("strategy PriceClose:{}".format(self.PriceClose)) # self.log("strategy PriceLow:{}".format(self.PriceLow)) pass if self.bar_num % self.p.hold_days == 0: # self.log("平仓日,当前收盘价为：{}".format(self.datas[0].close[0])) pass def run_CSVData(): begin_time=time.time() # Create a cerebro entity cerebro = bt.Cerebro() # Add a strategy cerebro.addstrategy(YunStrategy) # Datas are in a subfolder of the samples. Need to find where the script is # because it could have been called from anywhere datapath = 'E:/orcl-1995-2014.txt' # Create a Data Feed data = bt.feeds.YahooFinanceCSVData( dataname=datapath, # Do not pass values before this date fromdate=datetime.datetime(1995, 1, 1), # Do not pass values before this date todate=datetime.datetime(2014, 12, 31), # Do not pass values after this date reverse=False) # Add the Data Feed to Cerebro cerebro.adddata(data) comm=ComminfoFuturesPercent(commission=0.0002,margin=0.1, mult=10) cerebro.broker.addcommissioninfo(comm) # Set our desired cash start cerebro.broker.setcash(100000.0) # Print out the starting conditions # print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue()) # Run over everything cerebro.run() # Print out the final result # print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue()) end_time=time.time() # print(f"run1 total_use time is {end_time-begin_time}") return end_time-begin_time def run_PandasData(): begin_time=time.time() # Create a cerebro entity cerebro = bt.Cerebro() # Add a strategy cerebro.addstrategy(YunStrategy) # Datas are in a subfolder of the samples. Need to find where the script is # because it could have been called from anywhere df=pd.read_csv('E:/orcl-1995-2014.txt') df.index=pd.to_datetime(df['Date']) data = bt.feeds.PandasData(dataname=df) # Add the Data Feed to Cerebro cerebro.adddata(data) comm=ComminfoFuturesPercent(commission=0.0002,margin=0.1, mult=10) cerebro.broker.addcommissioninfo(comm) # Set our desired cash start cerebro.broker.setcash(100000.0) # Print out the starting conditions # print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue()) # Run over everything cerebro.run() # Print out the final result # print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue()) end_time=time.time() # print(f"PandasData total_use time is {end_time-begin_time}") return end_time-begin_time def run_PandasDirectData(): begin_time=time.time() # Create a cerebro entity cerebro = bt.Cerebro() # Add a strategy cerebro.addstrategy(YunStrategy) # Datas are in a subfolder of the samples. Need to find where the script is # because it could have been called from anywhere df=pd.read_csv('E:/orcl-1995-2014.txt') df.columns=['datetime','open','high','low','close','openinterest','volume'] df=df[['datetime','open','high','low','close','volume','openinterest']] df.index=pd.to_datetime(df['datetime']) del df['datetime'] # df=df.astype('float') data = bt.feeds.PandasDirectData(dataname=df) # Add the Data Feed to Cerebro cerebro.adddata(data) comm=ComminfoFuturesPercent(commission=0.0002,margin=0.1, mult=10) cerebro.broker.addcommissioninfo(comm) # Set our desired cash start cerebro.broker.setcash(100000.0) # Print out the starting conditions # print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue()) # Run over everything cerebro.run() # Print out the final result # print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue()) end_time=time.time() # print(f"PandasDirectData total_use time is {end_time-begin_time}") return end_time-begin_time def run_pickle(): begin_time=time.time() # Create a cerebro entity cerebro = bt.Cerebro() # Add a strategy cerebro.addstrategy(YunStrategy) # Datas are in a subfolder of the samples. Need to find where the script is # because it could have been called from anywhere with open("E:/test_backtrader_load_data.pkl",'rb') as f: df=pickle.load(f) # df=df.astype('float') data = bt.feeds.PandasDirectData(dataname=df) # Add the Data Feed to Cerebro cerebro.adddata(data) comm=ComminfoFuturesPercent(commission=0.0002,margin=0.1, mult=10) cerebro.broker.addcommissioninfo(comm) # Set our desired cash start cerebro.broker.setcash(100000.0) # Print out the starting conditions # print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue()) # Run over everything cerebro.run() # Print out the final result # print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue()) end_time=time.time() # print(f"PandasDirectData total_use time is {end_time-begin_time}") return end_time-begin_time if __name__ == '__main__': csvdata_list=[] PandasData_list=[] PandasDirectData_list=[] pickle_list=[] for i in range(100): csvdata_list.append(run_CSVData()) PandasData_list.append(run_PandasData()) PandasDirectData_list.append(run_PandasDirectData()) pickle_list.append(run_pickle())import matplotlib.pyplot as plt plt.plot(range(100),csvdata_list,color='green',label='csv load data') plt.plot(range(100),PandasData_list,color='blue',label='PandasData load data') plt.plot(range(100),PandasDirectData_list,color='red',label='PandasDirectData load data') plt.plot(range(100),pickle_list,color='black',label='pickle df and load data') plt.legend(loc='best') # 控制图片显示的位置 plt.title("backtrader load data time") plt.xlabel("different trial") plt.ylabel("seconds") plt.show()
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Wow, thanks for doing the hard work!
