[轉貼] Backtrader量化平台教程（一）:backtrader的整体框架
Backtrader量化平台教程（一）:backtrader的整体框架
這一篇寫的很好
重點是範例檔會動，之前我抓過好幾個程式都不能用，東缺西缺的。
程式碼如下
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import datetime# For datetime objects
import os.path# To manage paths
import sys# To find out the script name (in argv)
import pandas as pd
#from WindPy import w
# Import the backtrader platform
import backtrader as bt
# Create a Stratey
class TestStrategy(bt.Strategy):
def log(self, txt, dt=None):
''' Logging function fot this strategy'''
dt = dt or self.datas.datetime.date(0)
print('%s, %s' % (dt.isoformat(), txt))
def __init__(self):
# Keep a reference to the "close" line in the data dataseries
self.dataclose = self.datas.close
# To keep track of pending orders
self.order = None
def notify(self, order):
if order.status in :
# Buy/Sell order submitted/accepted to/by broker - Nothing to do
return
# Check if an order has been completed
# Attention: broker could reject order if not enougth cash
if order.status in :
if order.isbuy():
self.log('BUY EXECUTED, %.2f' % order.executed.price)
elif order.issell():
self.log('SELL EXECUTED, %.2f' % order.executed.price)
self.bar_executed = len(self)
# Write down: no pending order
self.order = None
def next(self):
# Simply log the closing price of the series from the reference
self.log('Close, %.2f' % self.dataclose)
# Check if an order is pending ... if yes, we cannot send a 2nd one
if self.order:
return
# Check if we are in the market
if not self.position:
# Not yet ... we MIGHT BUY if ...
if self.dataclose < self.dataclose[-1]:
# current close less than previous close
if self.dataclose[-1] < self.dataclose[-2]:
# previous close less than the previous close
# BUY, BUY, BUY!!! (with default parameters)
self.log('BUY CREATE, %.2f' % self.dataclose)
# Keep track of the created order to avoid a 2nd order
self.order = self.buy()
else:
# Already in the market ... we might sell
if len(self) >= (self.bar_executed + 5):
# SELL, SELL, SELL!!! (with all possible default parameters)
self.log('SELL CREATE, %.2f' % self.dataclose)
# Keep track of the created order to avoid a 2nd order
self.order = self.sell()
if __name__ == '__main__':
# Create a cerebro entity
cerebro = bt.Cerebro()
# Add a strategy
cerebro.addstrategy(TestStrategy)
# Create a Data Feed
# 本地数据，笔者用Wind获取的东风汽车数据以csv形式存储在本地。
# parase_dates = True是为了读取csv为dataframe的时候能够自动识别datetime格式的字符串，big作为index
# 注意，这里最后的pandas要符合backtrader的要求的格式
dataframe = pd.read_csv('dfqc.csv', index_col=0, parse_dates=True)
dataframe['openinterest'] = 0
data = bt.feeds.PandasData(dataname=dataframe,
fromdate = datetime.datetime(2015, 1, 1),
todate = datetime.datetime(2016, 12, 31)
)
# Add the Data Feed to Cerebro
cerebro.adddata(data)
# 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())
# Plot the result
cerebro.plot()
裡面的範例在下面這裡
感謝分享，把 from __future__ import (absolute_import, division, print_function, unicode_literals) 拿掉，可以在 python3 執行，測試成功 感謝分享
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