FMZ telah melancarkan Python Local Backtest Engine

FMZ telah melancarkan Python Local Backtest Engine

FMZ backtest enjin Python pakej menyokong Python2 dan Python3; menyokong sistem Windows, Linux, Mac OS.

Pemasangan

Masukkan arahan berikut dalam baris arahan:

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

• Nota: Apabila memasang enjin dalam sistem Mac OS, jika terdapat sekatan keselamatan, anda perlu menambah sudo di hadapan pip, dan kata laluan sistem akan diminta sebelum seluruh perintah pemasangan dijalankan.

Contoh Sederhana

'''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

Senar konfigurasi boleh dihasilkan secara automatik dengan menyimpan konfigurasi backtest di halaman Strategi Edit.

Dokumen

Dokumentasi API: (iaitu dokumentasi memanggil fungsi seperti GetAccount dalam demo)

• https://www.fmz.com/api

Catatan Mudah Kod Python:

'''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.
  

• Ubah kod backtest, untuk melihat bagaimana untuk memanggil Log dan GetTicker secara khusus.

  # 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 
  

  • cetak pertukaran.GetAccount():

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

  • Log (("\n call Log") 、 Log ((("Call exchange.GetTicker() ": ", pertukaran.GetTicker())

  Data yang dicetak adalah dalam struktur tugas cetak.Join():

  {
      "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
  }
  

• Bagaimana untuk menggunakan strategi untuk backtest dalam enjin backtest tempatan?

# !/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