xingetouzi / rqalpha-mod-fxdayu-source Goto Github PK

quantaxis数据存储在本地，有分钟、日线数据等.另问一个问题，rqalpha回测时默认是尾盘撮合，在尾盘涨停买不进，跌停卖不出。想改在开盘或其他时间撮合，有什么好方法实现

Installing collected packages: pandas, rqalpha-mod-fxdayu-source
Found existing installation: pandas 0.24.2
Uninstalling pandas-0.24.2:
Successfully uninstalled pandas-0.24.2
Successfully installed pandas-0.20.0 rqalpha-mod-fxdayu-source-0.1.0
安装的时候把我pandas降级了

hi，thanks for sharing this nice project.
在使用过程中，遇到如下问题：

单独使用QuantOsSource data_source以及data_proxy的history_bar获取日或者分钟数据时，报错RuntimeError: 0,Cannot deserialize instance of java.lang.String out of START_ARRAY token
at [Source: UNKNOWN; line: -1, column: -1] (through reference chain: com.junzhiam.cloud.gateway.SessionActor$LoginReq["username"])

环境

ubuntu 16.04 python3.6

code

`import datetime
from rqalpha.data.data_proxy import DataProxy
from rqalpha_mod_fxdayu_source.data_source.quantos import QuantOsSource

rqalpha_data_path = "xxxx"
api_url = "tcp://data.quantos.org:8910"
quantos_user = "xxxx"
quantos_token = "xxxx"

data_source = QuantOsSource(rqalpha_data_path, api_url=api_url, user=quantos_user, token=quantos_token)

data_proxy = DataProxy(data_source)
end_dt = datetime.datetime(2018,7,24,10,54,00)
output = data_proxy.history_bars('000001.XSHE',bar_count = 10,frequency='5m',dt=end_dt,field=['open','close'])
`

可否查看一下原因？ thanks for your time

看程序 mongodb 的数据源接口已经完成，请问如果构建 mongodb 数据源有说明文档吗，当前开源数据很多，采用 quantos 的数据也可以，但太慢了，所以最好能本地化？

在配置回测参数时候，如果不设置benchmark，则回测正常；如果设置benchmark，则会报错，不论是按1min回测还是按1d回测

弹出There is no current event loop in thread

参考如下连接修改后能正常运行了
Link

In python3.6, unknown reason, will lead to program exit without raise Exception.
#5

According to below code, is base frequency not supported yet when use 1m or 1h?

def history_bars(self, instrument, bar_count, frequency, fields, dt,
                 skip_suspended=True, include_now=False,
                 adjust_type='pre', adjust_orig=None):
    if self.is_base_frequency(instrument, frequency):
        bar_data = self.raw_history_bars(instrument, frequency, end_dt=dt, length=bar_count)
    else:

...

def raw_history_bars(self, instrument, frequency, start_dt=None, end_dt=None, length=None):
    raise NotImplementedError