FMZ는 파이썬 로컬 백테스트 엔진을 출시했습니다.

FMZ는 파이썬 로컬 백테스트 엔진을 출시했습니다.

FMZ 백테스트 엔진 파이썬 패키지 파이썬2와 파이썬3를 지원합니다. 윈도우, 리눅스, 맥 OS 시스템을 지원합니다.

설치

다음 명령어를 명령 줄에 입력합니다:

pip install https://github.com/fmzquant/backtest_python/archive/master.zip

• 참고: Mac OS 시스템에서 엔진을 설치할 때, 보안 제한이 있는 경우, pip 앞에 sudo을 추가해야 하며, 전체 설치 명령어가 실행되기 전에 시스템 비밀번호가 요청됩니다.

단순 한 예

'''backtest
start: 2018-02-19 00:00:00
end: 2018-03-22 12:00:00
period: 15m
exchanges: [{"eid":"OKEX","currency":"LTC_BTC","balance":3,"stocks":0}]
'''
from fmz import *
task = VCtx(__doc__) # initialize backtest engine from __doc__
print exchange.GetAccount()
print exchange.GetTicker()
print task.Join() # print backtest result

컨피그 문자열은 스트래티지 편집 페이지에서 백테스트 구성을 저장하여 자동으로 생성할 수 있습니다.

문서

API 문서: (특히 데모에서 GetAccount 같은 문서를 호출 함수)

• https://www.fmz.com/api

파이썬 코드의 간단한 언급:

'''backtest
start: 2018-02-19 00:00:00
end: 2018-03-22 12:00:00
period: 15m
exchanges: [{"eid":"OKEX","currency":"LTC_BTC","balance":3,"stocks":0}]
'''
from fmz import *           # Call the FMZ Quant library 
task = VCtx(__doc__)        # Initialize the backtest engine from __doc__ by calling VCtx
print exchange.GetAccount() # Test GetAccount function, and print the account information of the backtested platform 
print exchange.GetTicker()  # Test GetTicker function, and print the market quote information of backtest system 
print task.Join()           # Call the initialized task object, and print the backtest result    

• __doc__

  With two underscores, "__doc__" is used to access the first unassigned string in modules like class declaration or function declaration; the string can be enclosed by """ ""","" "" or ' ', which is to pass the backtest configuration information of '''backtest ... ''' in the code into the VCtx class constructor to construct objects.
  

• 백테스트 코드를 수정해서 로그와 GetTicker를 구체적으로 호출하는 방법을 알아보겠습니다.

  # coding=UTF-8
  
  '''backtest
  start: 2018-02-19 00:00:00
  end: 2018-03-22 12:00:00
  period: 15m
  exchanges: [{"eid":"OKEX","currency":"LTC_BTC","balance":3,"stocks":0}]
  '''
  
  from fmz import *                                               # Call the FMZ Quant library
  task = VCtx(__doc__) # initialize backtest engine from __doc__  # Call VCtx function according to the initialization of __doc__
  print exchange.GetAccount()                                     # Test GetAccount and print the account information of the tested platform by the backtest system
  Log("\n call Log")
  Log("Call exchange.GetTicker() : ", exchange.GetTicker())
  print task.Join()                                                # Call the initialized task object, and print the backtest result 
  

  • 인쇄 교환.GetAccount():

  {'Balance': 3.0, 'Stocks': 0.0, 'FrozenBalance': 0.0, 'FrozenStocks': 0.0}
  

  • 로그 (("\n 호출 로그") 、 로그 ((("콜 교환.GetTicker() : ", 교환.GetTicker())

  인쇄된 데이터는 인쇄 작업의 구조에 있습니다.

  {
      "Chart": {
   	   "Cfg": "",
   	   "Datas": []
      },
      "Elapsed": 42000000,
      "Finished": true,
      "Indicators": {},
      "LoadBytes": 441845,
      "LoadElapsed": 24000000,
      "LogsCount": 2,
      "Profit": 0.0,
      "ProfitLogs": [],
      "Progress": 100.0,
      "RuntimeLogs": [                                                  # Here call the printed data  
   	   [1, 1518969600200, 5, "", 0, 0.0, 0.0, "\n call Log", "", ""],
   	   [2, 1518969600400, 5, "", 0, 0.0, 0.0, "Call exchange.GetTicker() :  {'Sell': 0.02113476, 'Volume': 519.6953, 'Buy': 0.02113474, 'Last': 0.02113475, 'High': 0.02113476, 'Time': 1518969600000L, 'Low': 0.02113474}", "", ""]
      ],
      "Snapshort": [{
   	   "Balance": 3.0,
   	   "BaseCurrency": "LTC",
   	   "Commission": 0.0,
   	   "FrozenBalance": 0.0,
   	   "FrozenStocks": 0.0,
   	   "Id": "OKEX",
   	   "QuoteCurrency": "BTC",
   	   "Stocks": 0.0,
   	   "Symbols": {
   		   "LTC_BTC_OKEX": {
   			   "Last": 0.01893785
   		   }
   	   },
   	   "TradeStatus": {}
      }],
      "Status": "",
      "Task": {
   	   "Args": null,
   	   "Exchanges": [{
   		   "Balance": 3,
   		   "BaseCurrency": "LTC",
   		   "BasePeriod": 300000,
   		   "BasePrecision": 4,
   		   "DepthDeep": 5,
   		   "FaultTolerant": 0,
   		   "FeeDenominator": 5,
   		   "FeeMaker": 75,
   		   "FeeMin": 0,
   		   "FeeTaker": 80,
   		   "Id": "OKEX",
   		   "Label": "OKEX",
   		   "PriceTick": 1e-08,
   		   "QuoteCurrency": "BTC",
   		   "QuotePrecision": 8,
   		   "SlipPoint": 0,
   		   "Stocks": 0
   	   }],
   	   "Options": {
   		   "DataServer": "q.botvs.net",
   		   "MaxChartLogs": 800,
   		   "MaxProfitLogs": 800,
   		   "MaxRuntimeLogs": 800,
   		   "NetDelay": 200,
   		   "Period": 900000,
   		   "RetFlags": 189,
   		   "SnapshortPeriod": 300000,
   		   "TimeBegin": 1518969600,
   		   "TimeEnd": 1521691200,
   		   "UpdatePeriod": 5000
   	   }
      },
      "TaskStatus": 1,
      "Time": 1521691200000
  }
  

• 로컬 백테스트 엔진에서 백테스트 전략을 어떻게 사용할 수 있을까요?

# !/usr/local/bin/python
# -*- coding: UTF-8 -*-
'''backtest
start: 2018-02-19 00:00:00
end: 2018-03-22 12:00:00
period: 15m
exchanges: [{"eid":"Bitfinex","currency":"BTC_USD","balance":10000,"stocks":3}]
'''
import sys
sys.path.append("/usr/local/lib/python2.7/site-packages")    # Add a path during the backtest, and you can delete it if not needed 

from fmz import *
import math
import talib

task = VCtx(__doc__) # initialize backtest engine from __doc__

# ------------------------------ Strategy Section Starts --------------------------
print exchange.GetAccount()     # Call some interfaces, and print their return values 
print exchange.GetTicker()

def adjustFloat(v):             # Custom functions in the strategy 
    v = math.floor(v * 1000)
    return v / 1000

def onTick(e):
    Log("onTick")
    # ....

#
# ...
# 
# Here the codes including the implementation of custom functions are omitted 

def main():
    InitAccount = GetAccount()
    
    while True:
        onTick(exchange)
        Sleep(1000)
# ------------------------------ Strategy Section Ends --------------------------

try:
    main()                     # Raise EOFError() when the backtest ends, to stop the backtest loop. Therefore, the error needs to be processed by calling task.Join() when the error is detected, and print the backtest result 
except:
    print task.Join()          # print the backtest result