def start_shell(algorithm, algomodule):
algomodule['context'] = algorithm
algomodule['data'] = BarData(algorithm.data_portal,
algorithm.data_frequency)
algorithm.on_dt_changed(pd.Timestamp.utcnow().floor('1min'))
algomodule['data'].datetime = algorithm.datetime
InteractiveShellEmbed()('*** pylivetrader shell ***', local_ns=algomodule)
def __init__(self, algo, data_portal):
self.data_portal = data_portal
self.algo = algo
# This object is the way that user algorithms interact with OHLCV data,
# fetcher data, and some API methods like `data.can_trade`.
self.current_data = BarData(
data_portal,
self.algo.data_frequency,
)
before_trading_start_minute = \
(datetime.time(8, 45), 'America/New_York')
self.clock = RealtimeClock(
self.algo.trading_calendar,
before_trading_start_minute,
minute_emission=algo.data_frequency == 'minute',
time_skew=self.algo._backend.time_skew,
)
def test_bardata():
portal = get_fixture_data_portal()
asset0 = portal.asset_finder.retrieve_asset('asset-0')
asset1 = portal.asset_finder.retrieve_asset('asset-1')
data = BarData(portal, 'minute')
# current
last_in_fields = {
'open': 780 + 10 - 1,
'high': 780 + 15 - 1,
'low': 780 + 8 - 1,
'close': 780 + 10 - 1,
'price': 780 + 10 - 1,
'volume': 100,
}
for k, v in last_in_fields.items():
assert data.current(asset0, k) == v
o = data.current([asset0, asset1], k)
assert len(o) == 2
assert type(o) == pd.Series
o = data.current(asset0, ['open', 'close'])
assert len(o) == 2
assert type(o) == pd.Series
o = data.current([asset0, asset1], ['open', 'close'])
assert set(list(o.columns)) == set(['open', 'close'])
assert set(list(o.index)) == set([asset0, asset1])
# history
day_values = {
'open': 2 + 10 - 1,
'high': 2 + 15 - 1,
'low': 2 + 8 - 1,
'close': 2 + 10 - 1,
'price': 2 + 10 - 1,
'volume': 100,
}
for k, v in last_in_fields.items():
assert data.history(asset0, k, 1, 'minute').iloc[0] == v
assert data.history(asset0, k, 1, 'day').iloc[0] == day_values[k]
o = data.history([asset0, asset1], 'open', 1, 'minute')
assert type(o) == pd.DataFrame
assert len(o.index) == 1
assert len(o.columns) == 2
o = data.history([asset0, asset1], ['open', 'close'], 1, 'minute')
assert type(o) == pd.Panel
# can_trade
data.datetime = pd.Timestamp('2018-08-13', tz='UTC')
asset_to_check = Asset(
'asset-0',
'NYSE',
symbol='ASSET',
start_date=pd.Timestamp('2018-01-01', tz='UTC'),
end_date=pd.Timestamp('2018/08/13', tz='UTC'),
)
assert data.can_trade(asset_to_check)
assert not data.is_stale(asset_to_check)
# data.datetime = pd.Timestamp('2018-08-14', tz='UTC')
# assert not data.can_trade(asset_to_check)
# when asset is not tradable, return false
assert not data.is_stale(asset_to_check)