如何在自定义拉链捆绑包中使用自定义日历？

Question

我在我的维亚CSV.py旨在允许接收自定义捆绑包的文件：

#
# Ingest stock csv files to create a zipline data bundle

import os

import numpy  as np
import pandas as pd
import datetime

boDebug=True # Set True to get trace messages

from zipline.utils.cli import maybe_show_progress

def viacsv(symbols,start=None,end=None):

    # strict this in memory so that we can reiterate over it.
    # (Because it could be a generator and they live only once)
    tuSymbols = tuple(symbols)

    if boDebug:
        print "entering viacsv.  tuSymbols=",tuSymbols

    # Define our custom ingest function
    def ingest(environ,
               asset_db_writer,
               minute_bar_writer,  # unused
               daily_bar_writer,
               adjustment_writer,
               calendar,
               cache,
               show_progress,
               output_dir,
               # pass these as defaults to make them 'nonlocal' in py2
               start=start,
               end=end):

        if boDebug:
            print "entering ingest and creating blank dfMetadata"

        dfMetadata = pd.DataFrame(np.empty(len(tuSymbols), dtype=[
            ('start_date', 'datetime64[ns]'),
            ('end_date', 'datetime64[ns]'),
            ('auto_close_date', 'datetime64[ns]'),
            ('symbol', 'object'),
        ]))

        if boDebug:
            print "dfMetadata",type(dfMetadata)
            print dfMetadata.describe
            print

        # We need to feed something that is iterable - like a list or a generator -
        # that is a tuple with an integer for sid and a DataFrame for the data to
        # daily_bar_writer

        liData=[]
        iSid=0
        for S in tuSymbols:
            IFIL="~/notebooks/csv/"+S+".csv"
            if boDebug:
               print "S=",S,"IFIL=",IFIL
            dfData=pd.read_csv(IFIL,index_col='Date',parse_dates=True).sort_index()
            if boDebug:
               print "read_csv dfData",type(dfData),"length",len(dfData)
               print
            dfData.rename(
                columns={
                    'Open': 'open',
                    'High': 'high',
                    'Low': 'low',
                    'Close': 'close',
                    'Volume': 'volume',
                    'Adj Close': 'price',
                },
                inplace=True,
            )
            dfData['volume']=dfData['volume']/1000
            liData.append((iSid,dfData))

            # the start date is the date of the first trade and
            start_date = dfData.index[0]
            if boDebug:
                print "start_date",type(start_date),start_date

            # the end date is the date of the last trade
            end_date = dfData.index[-1]
            if boDebug:
                print "end_date",type(end_date),end_date

            # The auto_close date is the day after the last trade.
            ac_date = end_date + pd.Timedelta(days=1)
            if boDebug:
                print "ac_date",type(ac_date),ac_date

            # Update our meta data
            dfMetadata.iloc[iSid] = start_date, end_date, ac_date, S

            iSid += 1

        if boDebug:
            print "liData",type(liData),"length",len(liData)
            print liData
            print
            print "Now calling daily_bar_writer"

        daily_bar_writer.write(liData, show_progress=False)

        # Hardcode the exchange to "YAHOO" for all assets and (elsewhere)
        # register "YAHOO" to resolve to the NYSE calendar, because these are
        # all equities and thus can use the NYSE calendar.
        dfMetadata['exchange'] = "YAHOO"

        if boDebug:
            print "returned from daily_bar_writer"
            print "calling asset_db_writer"
            print "dfMetadata",type(dfMetadata)
            print dfMetadata
            print

        # Not sure why symbol_map is needed
        symbol_map = pd.Series(dfMetadata.symbol.index, dfMetadata.symbol)
        if boDebug:
            print "symbol_map",type(symbol_map)
            print symbol_map
            print

        asset_db_writer.write(equities=dfMetadata)

        if boDebug:
            print "returned from asset_db_writer"
            print "calling adjustment_writer"

        adjustment_writer.write()

        if boDebug:
            print "returned from adjustment_writer"
            print "now leaving ingest function"

    if boDebug:
       print "about to return ingest function"
    return ingest

我的问题是，我输入的数据不是美国数据，而是澳大利亚股票数据。因此，它遵守澳大利亚的假日，而不是美国的假日。似乎不知何故，下面的代码默认使用美国的交易日历，并告诉我，我不能传递数据，美国市场将关闭，反之亦然。如何调整上面的代码以接受自定义日历？为了接收捆绑包，我在终端上运行以下命令：

^{pr2}$

有什么想法？在

Answer 1

您需要在zipline/utils/calendars中定义您自己的日历：只需创建一个现有文件的副本（例如，exchange\u calendar）_纽约证券交易所）并编辑所需的假日。假设你把这个文件叫做“我的”_日历.py和班级的《我的日历》。在

请注意，您还需要采取其他2（或3）个步骤：

1）在zipline/util/calendars/calendar中注册日历_实用工具.py：您可以添加一个条目到\u default_calendar_factories，如果需要别名，还可以添加一个别名。例如，映射我自己的_日历.py使用别名“我的日历”来“拥有”：

_default_calendar_factories = {
    'NYSE': NYSEExchangeCalendar,
    'CME': CMEExchangeCalendar,
    ...
    'OWN': MyOwnCalendar
}

_default_calendar_aliases = {
    'NASDAQ': 'NYSE',
    ...
    'MY_CALENDAR': 'OWN'
 }

2）您需要编辑.zipline/扩展名.py（您将在主目录中找到.zipline-要在Windows下查看您的主页，请打开dos shell并键入echo%USERPROFILE%

^{pr2}$

通过这些步骤，您应该可以简单地输入zipline incentate-b my\u market来摄取您的捆绑包。在

3）我个人遇到的问题是，我需要对交易日历进行更多的控制，因为超级类交易日历假设周六/周日为非交易日，但并非每个市场/资产类别都如此。错误的日历定义将导致摄取时出现异常。 例如，为了让一个7/7、24/24交易的市场有日历，我对日历进行了如下黑客攻击：

from datetime import time
from pytz import timezone
from pandas import date_range
from .trading_calendar import TradingCalendar, HolidayCalendar

from zipline.utils.memoize import lazyval

from pandas.tseries.offsets import CustomBusinessDay

class MyOwnCalendar(TradingCalendar):
    """
    Round the clock calendar: 7/7, 24/24
    """

    @property
    def name(self):
        return "OWN"

    @property
    def tz(self):
        return timezone("Europe/London")

    @property
    def open_time(self):
        return time(0)

    @property
    def close_time(self):
        return time(23, 59)

    @property
    def regular_holidays(self):
        return []

    @property
    def special_opens(self):
        return []

    def sessions_in_range(self, start_session, last_session):
        return date_range(start_session, last_session)

    @lazyval
    def day(self):
        return CustomBusinessDay(holidays=self.adhoc_holidays,
        calendar=self.regular_holidays,weekmask="Mon Tue Wed Thu Fri Sat Sun")