Onepy

Install

pip install pandas
pip install TA-Lib
pip install plotly
pip install funcy
pip install arrow
pip install pymongo
pip install OnePy_trader
pip install --upgrade OnePy_trader

Getting started

import OnePy as op
class MyStrategy(op.StrategyBase):
 def __init__(self, marketevent):
 super(MyStrategy, self).__init__(marketevent)
 def prenext(self):
 """以下条件均可用于next中进行策略逻辑判断"""
 # print(self.position[-1])
 # print(self.margin[-1])
 # print(self.avg_price[-1])
 # print(self.unrealizedPL[-1])
 # print(self.realizedPL[-1])
 # print(self.commission[-1])
 # print(self.cash[-1])
 # print(self.balance[-1])
 pass
 def next(self):
 """这里写主要的策略思路"""
 if self.i.SMA(period=30, index=-1) > self.i.SMA(period=50, index=-1):
 if self.unrealizedPL[-1] <= 0:
 self.buy(0.1, takeprofit=self.pips(200), # 设置止盈为200个pips,不可为负
 stoploss=self.pct(1), # 设置止损为成交价的1%,不可为负
 trailingstop=self.pips(60)) # 设置追踪止损,盈利时触发
 else:
 self.sell(0.05, price=self.pips(50), # 设置挂单,默认为第二天open价格加50点,也可为负数
 takeprofit=self.pips(200),
 stoploss=self.pips(200),
 trailingstop=self.pips(60))
 if self.unrealizedPL[-2] > self.unrealizedPL[-1] and self.unrealizedPL[-2] > 100:
 self.exitall() # 设置浮亏浮盈大于100元且出现下降时清仓
go = op.OnePiece()
Forex = op.ForexCSVFeed(datapath='../data/EUR_USD30m.csv', instrument='EUR_USD',
 fromdate='2012-04-01', todate='2012-05-01')
# 注意若要用MongoDB_Backtest_Feed,先运行tests里面的csv_to_MongoDB.py,推荐用MongoDB
# Forex = op.MongoDB_Backtest_Feed(database='EUR_USD', collection='M30', instrument='EUR_USD',
#                 fromdate='2012-04-01', todate='2012-05-01')
data_list = [Forex]
portfolio = op.Portfolio
strategy = MyStrategy
go.set_backtest(data_list, [strategy], portfolio, 'Forex')
go.set_commission(commission=10, margin=325, mult=100000)
go.set_cash(100000) # 设置初始资金
# go.set_pricetype(‘close’) # 设置成交价格为close,若不设置,默认为open
# go.set_notify() # 打印交易日志
go.sunny() # 开始启动策略
print(go.get_tlog('EUR_USD')) # 打印交易日志
go.get_analysis('EUR_USD')
go.plot(instrument='EUR_USD', notebook=False)

+------------------------+
| Final_Value | 92619.2 |
| Total_return | -7.381% |
| Max_Drawdown | 9.261% |
| Duration | 989.0 |
| Sharpe_Ratio | -0.474 |
+------------------------+
+------------------------------------------------------------------+
| start | 2012年04月01日 22:00:00 |
| end | 2012年04月30日 23:30:00 |
| beginning_balance | 100000 |
| ending_balance | 92619.2 |
| unrealized_profit | -10032.85 |
| total_net_profit | 2652.05 |
| gross_profit | 2774.75 |
| gross_loss | -7.7 |
| profit_factor | 360.357 |
| return_on_initial_capital | 2.652 |
| annual_return_rate | -61.848 |
| trading_period | 0 years 0 months 29 days |
| pct_time_in_market | 469.595 |
| total_num_trades | 69 |
| num_winning_trades | 64 |
| num_losing_trades | 5 |
| num_even_trades | 0 |
| pct_profitable_trades | 92.754 |
| avg_profit_per_trade | 38.436 |
| avg_profit_per_winning_trade | 43.355 |
| avg_loss_per_losing_trade | -1.54 |
| ratio_avg_profit_win_loss | 28.153 |
| largest_profit_winning_trade | 80.5 |
| largest_loss_losing_trade | -2.5 |
| num_winning_points | 0.119 |
| num_losing_points | -0.326 |
| total_net_points | -0.207 |
| avg_points | -0.003 |
| largest_points_winning_trade | 0.007 |
| largest_points_losing_trade | -0.016 |
| avg_pct_gain_per_trade | -0.227 |
| largest_pct_winning_trade | 0.533 |
| largest_pct_losing_trade | -1.219 |
| max_consecutive_winning_trades | 54 |
| max_consecutive_losing_trades | 2 |
| avg_bars_winning_trades | 70.672 |
| avg_bars_losing_trades | 46.8 |
| max_closed_out_drawdown | -9.259 |
| max_closed_out_drawdown_start_date | 2012年04月02日 09:00:00 |
| max_closed_out_drawdown_end_date | 2012年04月19日 13:00:00 |
| max_closed_out_drawdown_recovery_date | Not Recovered Yet |
| drawdown_recovery | -0.047 |
| drawdown_annualized_return | 0.15 |
| max_intra_day_drawdown | -9.544 |
| avg_yearly_closed_out_drawdown | -4.166 |
| max_yearly_closed_out_drawdown | -6.346 |
| avg_monthly_closed_out_drawdown | -0.814 |
| max_monthly_closed_out_drawdown | -3.743 |
| avg_weekly_closed_out_drawdown | -0.273 |
| max_weekly_closed_out_drawdown | -2.997 |
| avg_yearly_closed_out_runup | 2.997 |
| max_yearly_closed_out_runup | 5.455 |
| avg_monthly_closed_out_runup | 0.673 |
| max_monthly_closed_out_runup | 4.458 |
| avg_weekly_closed_out_runup | 0.239 |
| max_weekly_closed_out_runup | 2.79 |
| pct_profitable_years | 28.816 |
| best_year | 2.843 |
| worst_year | -6.277 |
| avg_year | -1.436 |
| annual_std | 2.093 |
| pct_profitable_months | 42.54 |
| best_month | 4.458 |
| worst_month | -3.727 |
| avg_month | -0.147 |
| monthly_std | 1.17 |
| pct_profitable_weeks | 40.814 |
| best_week | 2.79 |
| worst_week | -2.997 |
| avg_week | -0.037 |
| weekly_std | 0.535 |
| sharpe_ratio | -0.474 |
| sortino_ratio | -0.466 |
+------------------------------------------------------------------+

Main Features

OnePy 综合方面:

Tools 工具方面:

Feed 数据方面:

Strategy 策略方面:

Portfolio 风控方面:

Broker 执行方面:

Fill 日志方面:

Stats 分析方面:

Alternatives

后记

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