import pandas as pd

from zipline.data.bundles import register
from zipline.data.bundles.csvdir import csvdir_equities
import datetime as dt
import pytz

stock_home = '/root/stock_home'

daily_csv = pd.read_csv("{}/daily/TQQQ.csv".format(stock_home))
daily_end_date = daily_csv.iloc[0]['timestamp']
daily_start_date = daily_csv.iloc[-1]['timestamp']
daily_start_session = pd.Timestamp(daily_start_date, tz='utc')
daily_end_session = pd.Timestamp(daily_end_date, tz='utc')


#print('{}: {}'.format(minute_start_session, minute_end_session)) 

register(
    'avcsv',
    csvdir_equities(
        ['daily'],
        stock_home,
    ),
    calendar_name='NYSE', # US equities
    start_session=daily_start_session,
    end_session=daily_end_session
)

register(
    'avcsv_minute',
    csvdir_equities(
        ['minute'],
        stock_home,
    ),
    #minutes_per_day=720,
    #calendar_name='24/7', # i
    calendar_name='NYSE', # US equities
    start_session= pd.Timestamp('2019-01-14', tz='utc'), #US/Eastern'),
    end_session=pd.Timestamp('2020-12-30', tz='utc') #US/Eastern')
)

register(
    'avcsv_all',
    csvdir_equities(
        ['daily','minute'],
        stock_home,
    ),
    calendar_name='NYSE', # US equities
    start_session= pd.Timestamp('2019-01-14', tz='utc'), #US/Eastern'),
    end_session=pd.Timestamp('2021-01-08', tz='utc') #US/Eastern')
)