feed – 数据源基类

Feeds 是将时间序列抽象化 当这些在事件调度循环时，会推送一个新的可用数据。 When these are included in the event dispatch loop, they emit an event as new data is available. Feeds are also responsible for updating the pyalgotrade.dataseries.DataSeries associated with each piece of data that the feed provides.

当前位置是关于数据源基类的，要了解bar的数据源请查阅： barfeed – Bar数据来源 板块.

CSV 支持

CSV 支持的例子

一个带有以下格式的文件

Date,USD,GBP,EUR
2013-09-29,1333.0,831.203,986.75
2013-09-22,1349.25,842.755,997.671
2013-09-15,1318.5,831.546,993.969
2013-09-08,1387.0,886.885,1052.911
.
.
.

像这样引入并使用:

from pyalgotrade.feed import csvfeed

feed = csvfeed.Feed("Date", "%Y-%m-%d")
feed.addValuesFromCSV("quandl_gold_2.csv")
for dateTime, value in feed:
    print(dateTime, value)

输出结果如下:

1968-04-07 00:00:00 {'USD': 37.0, 'GBP': 15.3875, 'EUR': ''}
1968-04-14 00:00:00 {'USD': 38.0, 'GBP': 15.8208, 'EUR': ''}
1968-04-21 00:00:00 {'USD': 37.65, 'GBP': 15.6833, 'EUR': ''}
1968-04-28 00:00:00 {'USD': 38.65, 'GBP': 16.1271, 'EUR': ''}
1968-05-05 00:00:00 {'USD': 39.1, 'GBP': 16.3188, 'EUR': ''}
1968-05-12 00:00:00 {'USD': 39.6, 'GBP': 16.5625, 'EUR': ''}
1968-05-19 00:00:00 {'USD': 41.5, 'GBP': 17.3958, 'EUR': ''}
1968-05-26 00:00:00 {'USD': 41.75, 'GBP': 17.5104, 'EUR': ''}
1968-06-02 00:00:00 {'USD': 41.95, 'GBP': 17.6, 'EUR': ''}
1968-06-09 00:00:00 {'USD': 41.25, 'GBP': 17.3042, 'EUR': ''}
.
.
.
2013-07-28 00:00:00 {'USD': 1331.0, 'GBP': 864.23, 'EUR': 1001.505}
2013-08-04 00:00:00 {'USD': 1309.25, 'GBP': 858.637, 'EUR': 986.921}
2013-08-11 00:00:00 {'USD': 1309.0, 'GBP': 843.156, 'EUR': 979.79}
2013-08-18 00:00:00 {'USD': 1369.25, 'GBP': 875.424, 'EUR': 1024.964}
2013-08-25 00:00:00 {'USD': 1377.5, 'GBP': 885.738, 'EUR': 1030.6}
2013-09-01 00:00:00 {'USD': 1394.75, 'GBP': 901.292, 'EUR': 1055.749}
2013-09-08 00:00:00 {'USD': 1387.0, 'GBP': 886.885, 'EUR': 1052.911}
2013-09-15 00:00:00 {'USD': 1318.5, 'GBP': 831.546, 'EUR': 993.969}
2013-09-22 00:00:00 {'USD': 1349.25, 'GBP': 842.755, 'EUR': 997.671}
2013-09-29 00:00:00 {'USD': 1333.0, 'GBP': 831.203, 'EUR': 986.75}