backtrader
comes with a set of Data Feed parsers (at the time of writing all CSV Based) to let you load data from different sources.
backtrader附带了一组数据源解析器(在编写所有基于CSV的代码时),允许您从不同的源加载数据
-
Yahoo (online or already saved to a file)
-
VisualChart (see www.visualchart.com
-
Backtrader CSV (own cooked format for testing)
-
Generic CSV support
From the Quickstart guide it should be clear that you add data feeds to a Cerebro
instance. The data feeds will later be available to the different strategies in:
从快速入门指南中可以清楚地看到,您可以向一个大脑实例添加数据源。数据源稍后将提供给不同的策略:
-
An array self.datas (insertion order)
- 一个数组self.datas(插入顺序)
-
Alias to the array objects:
- 数组对象的别名
-
-
self.data and self.data0 point to the first element
- self.data和self.data0指向了第一个元素
-
self.dataX points to elements with index X in the array
- self.dataX指向了array的第X索引的元素
-
A quick reminder as to how the insertion works:
关于插入如何工作的快速提示:
import backtrader as bt import backtrader.feeds as btfeeds data = btfeeds.YahooFinanceCSVData(dataname='wheremydatacsvis.csv') cerebro = bt.Cerebro() cerebro.adddata(data) # a 'name' parameter can be passed for plotting purposes
Data Feeds Common parameters
This data feed can download data directly from Yahoo and feed into the system.
这个数据源可以直接从Yahoo下载数据并输入到系统中
Parameters:
-
dataname
(default: None) MUST BE PROVIDED(必须提供)The meaning varies with the data feed type (file location, ticker, …)
-
其含义随数据馈送类型(文件位置、ticker等)而变化
-
name
(default: ‘’)Meant for decorative purposes in plotting. If not specified it may be derived from
dataname
(example: last part of a file path) - 在绘图的时候用于装饰用。如果没有指定,它可能来至与dataname(例如:文件路径的最后一部分)
-
fromdate
(default: mindate)Python datetime object indicating that any datetime prior to this should be ignored
- Python日期时间对象,该对象指示在此之前的任何日期时间都应被忽略
-
todate
(default: maxdate)Python datetime object indicating that any datetime posterior to this should be ignored
- Python日期时间对象,该对象指示在此之后的任何日期时间都应被忽略
-
timeframe
(default: TimeFrame.Days) - 时间框架
-
Potential values:
Ticks
,Seconds
,Minutes
,Days
,Weeks
,Months
andYears
-
compression
(default: 1) - 压缩
-
Number of actual bars per bar. Informative. Only effective in Data Resampling/Replaying.
- 每个bar的实际数量,仅对数据重采样/重放有效。
-
sessionstart
(default: None)Indication of session starting time for the data. May be used by classes for purposes like resampling
- 指示数据的会话开始时间。可能被类用于重采样等目的
-
sessionend
(default: None)Indication of session ending time for the data. May be used by classes for purposes like resampling
- 指示数据的会话结束时间。可能被类用于重采样等目的
CSV Data Feeds Common parameters
Parameters (additional to the common ones):
额外的参数
-
headers
(default: True)Indicates if the passed data has an initial headers row
- 指示传递的数据是否具有初始标题行
-
separator
(default: “,”)Separator to take into account to tokenize each of the CSV rows
- 分隔符,用于标记每个CSV行
GenericCSVData
一般CSVData
This class exposes a generic interface allowing parsing mostly every CSV file format out there.
Parses a CSV file according to the order and field presence defined by the parameters
Specific parameters (or specific meaning):
这个类公开了一个通用接口,允许解析大部分CSV文件格式。
解析CSV文件根据参数的顺序以及字段的定义
-
dataname
The filename to parse or a file-like object
- 分析文件名或者文件对象
-
datetime
(default: 0) column containing the date (or datetime) field - 列包含date或datetime的字段
-
time
(default: -1) column containing the time field if separate from the datetime field (-1 indicates it’s not present) -
时间(默认值:-1)如果与日期时间字段分开,则包含时间字段的列(-1表示不存在)
-
open
(default: 1) ,high
(default: 2),low
(default: 3),close
(default: 4),volume
(default: 5),openinterest
(default: 6)Index of the columns containing the corresponding fields
- 列的索引包含不同的领域
-
If a negative value is passed (example: -1) it indicates the field is not present in the CSV data
- 如果传递负值(例如:-1),则表示CSV数据中不存在该字段
-
nullvalue
(default: float(‘NaN’))Value that will be used if a value which should be there is missing (the CSV field is empty)
- 如果缺少应存在的值(CSV字段为空)时将使用的值
-
dtformat
(default: %Y-%m-%d %H:%M:%S)用于分析datetime CSV字段的格式
-
tmformat
(default: %H:%M:%S)Format used to parse the time CSV field if “present” (the default for the “time” CSV field is not to be present)
- 用于分析“present”时的timeCSV字段的格式(“time”CSV字段的默认值不存在)
An example usage covering the following requirements:
包含以下要求的示例用法:
-
Limit input to year 2000
- 输入限制在2000年以后
-
HLOC order rather than OHLC
- 输入数据为hight,low,open,close
-
Missing values to be replaced with zero (0.0)
- 缺省的值为0.0
-
Daily bars are provided and datetime is just the day with format YYYY-MM-DD
- 时间格式化为YYYY-MM-DD
-
No
openinterest
column is present - 当前没有
openinterest
的列
import datetime import backtrader as bt import backtrader.feeds as btfeeds ... ... data = btfeeds.GenericCSVData( dataname='mydata.csv', fromdate=datetime.datetime(2000, 1, 1), todate=datetime.datetime(2000, 12, 31), nullvalue=0.0, dtformat=('%Y-%m-%d'), datetime=0, high=1, low=2, open=3, close=4, volume=5, openinterest=-1 ) ...
Slightly modified requirements:
略微改进的要求
-
Limit input to year 2000
-
HLOC order rather than OHLC
-
Missing values to be replaced with zero (0.0)
-
Intraday bars are provided, with separate date and time columns
- 提供日内的bars,分成日期与时间两个柱
-
- Date has format YYYY-MM-DD
- Time has format HH.MM.SS (instead of the usual HH:MM:SS)
-
No
openinterest
column is present
import datetime import backtrader as bt import backtrader.feeds as btfeed ... ... data = btfeeds.GenericCSVData( dataname='mydata.csv', fromdate=datetime.datetime(2000, 1, 1), todate=datetime.datetime(2000, 12, 31), nullvalue=0.0, dtformat=('%Y-%m-%d'), tmformat=('%H.%M.%S'), datetime=0, time=1, high=2, low=3, open=4, close=5, volume=6, openinterest=-1 )
This can also be made permanent with subclassing:
import datetime import backtrader.feeds as btfeed class MyHLOC(btfreeds.GenericCSVData): params = ( ('fromdate', datetime.datetime(2000, 1, 1)), ('todate', datetime.datetime(2000, 12, 31)), ('nullvalue', 0.0), ('dtformat', ('%Y-%m-%d')), ('tmformat', ('%H.%M.%S')), ('datetime', 0), ('time', 1), ('high', 2), ('low', 3), ('open', 4), ('close', 5), ('volume', 6), ('openinterest', -1) )
This new class can be reused now by just providing the dataname
:
这个新的类可以让我们只提供dataname
就可以重用
data = btfeeds.MyHLOC(dataname='mydata.csv')