开源量化框架backtrader FAQ：开发MySQL data feed

完整技术教程见这里

有很多人建立了自己本地的行情数据库，希望能够从本地数据库将数据发到backtrader，供策略使用。一个通用的方法是将数据库的行情数据读到pandas dataframe里，然后将这个数据帧的数据传给backtrader的pandas feed数据对象，这样策略就能够使用了。

但是有些同学不想通过pandas dataframe中转，而是想直接从数据库将数据喂给backtrader的数据馈送对象，这就需要针对数据库开发专门的data feed类了。

以下就是backtrader社区提供的一个从MySQL数据库读取数据的feed类MySQLData，大家可以试一试。

from __future__ import (absolute_import, division, print_function,
                        unicode_literals)
import datetime
from backtrader.feed import DataBase
from backtrader import date2num
from sqlalchemy import create_engine
class MySQLData(DataBase):
    params = (
        ('dbHost', None),
        ('dbUser', None),
        ('dbPWD', None),
        ('dbName', None),
        ('ticker', 'ISL'),
        ('fromdate', datetime.datetime.min),
        ('todate', datetime.datetime.max),
        ('name', ''),
        )
    def __init__(self):
        self.engine = create_engine('mysql://'+self.p.dbUser+':'+ self.p.dbPWD +'@'+ self.p.dbHost +'/'+ self.p.dbName +'?charset=utf8mb4', echo=False)
    def start(self):
        self.conn = self.engine.connect()
        self.stockdata = self.conn.execute('SELECT id FROM stocks WHERE ticker LIKE '' + self.p.ticker + '' LIMIT 1')
        self.stock_id = self.stockdata.fetchone()[0]
        #self.result = self.engine.execute('SELECT `date`,`open`,`high`,`low`,`close`,`volume` FROM `eoddata` WHERE `stock_id` = 10 AND `date` between ''+self.p.fromdate.strftime('%Y-%m-%d')+'' and ''+self.p.todate.strftime('%Y-%m-%d')+'' ORDER BY `date` ASC')
        self.result = self.conn.execute('SELECT `date`,`open`,`high`,`low`,`close`,`volume` FROM `eoddata` WHERE `stock_id` = ' + str(self.stock_id) + ' AND `date` between ''+self.p.fromdate.strftime('%Y-%m-%d')+'' and ''+self.p.todate.strftime('%Y-%m-%d')+'' ORDER BY `date` ASC')
    def stop(self):
        #self.conn.close()
        self.engine.dispose()
    def _load(self):
        one_row = self.result.fetchone()
        if one_row is None:
            return False
        self.lines.datetime[0] = date2num(one_row[0])
        self.lines.open[0] = float(one_row[1])
        self.lines.high[0] = float(one_row[2])
        self.lines.low[0] = float(one_row[3])
        self.lines.close[0] = float(one_row[4])
        self.lines.volume[0] = int(one_row[5])
        self.lines.openinterest[0] = -1
        return True

发布于 19 小时前