def get_adj_dates(self, start, end, assets, data_frequency):
"""
Contains a date range to the trading availability of the specified
markets.
Parameters
----------
start: pd.Timestamp
end: pd.Timestamp
assets: list[TradingPair]
data_frequency: str
Returns
-------
pd.Timestamp, pd.Timestamp
"""
earliest_trade = None
last_entry = None
for asset in assets:
if earliest_trade is None or earliest_trade > asset.start_date:
if asset.start_date >= self.calendar.first_session:
earliest_trade = asset.start_date
else:
earliest_trade = self.calendar.first_session
end_asset = asset.end_minute if data_frequency == 'minute' else \
asset.end_daily
if end_asset is not None:
if last_entry is None or end_asset > last_entry:
last_entry = end_asset
else:
end = None
last_entry = None
if start is None or \
(earliest_trade is not None and earliest_trade > start):
start = earliest_trade
if end is None or (last_entry is not None and end > last_entry):
end = last_entry.replace(minute=59, hour=23) \
if data_frequency == 'minute' else last_entry
if end is None or start is None or start > end:
raise NoDataAvailableOnExchange(
exchange=[asset.exchange for asset in assets],
symbol=[asset.symbol for asset in assets],
data_frequency=data_frequency,
)
return start, end
def get_adj_dates(start, end, assets, data_frequency):
"""
Contains a date range to the trading availability of the specified pairs.
:param start:
:param end:
:param assets:
:param data_frequency:
:return:
"""
earliest_trade = None
last_entry = None
for asset in assets:
if earliest_trade is None or earliest_trade > asset.start_date:
earliest_trade = asset.start_date
end_asset = asset.end_minute if data_frequency == 'minute' else \
asset.end_daily
if end_asset is not None and \
(last_entry is None or end_asset > last_entry):
last_entry = end_asset
if start is None or earliest_trade > start:
start = earliest_trade
if end is None or (last_entry is not None and end > last_entry):
end = last_entry
if end is None or start >= end:
raise NoDataAvailableOnExchange(
exchange=asset.exchange.title(),
symbol=[asset.symbol.encode('utf-8')],
data_frequency=data_frequency,
)
return start, end
def get_asset(self,
symbol,
data_frequency=None,
is_exchange_symbol=False,
is_local=None):
"""
The market for the specified symbol.
Parameters
----------
symbol: str
The Catalyst or exchange symbol.
data_frequency: str
Check for asset corresponding to the specified data_frequency.
The same asset might exist in the Catalyst repository or
locally (following a CSV ingestion). Filtering by
data_frequency picks the right asset.
is_exchange_symbol: bool
Whether the symbol uses the Catalyst or exchange convention.
is_local: bool
For the local or Catalyst asset.
Returns
-------
TradingPair
The asset object.
"""
asset = None
# TODO: temp mapping, fix to use a single symbol convention
og_symbol = symbol
symbol = self.get_symbol(symbol) if not is_exchange_symbol else symbol
log.debug('searching assets for: {} {}'.format(self.name, symbol))
# TODO: simplify and loose the loop
for a in self.assets:
if asset is not None:
break
if is_local is not None:
data_source = 'local' if is_local else 'catalyst'
applies = (a.data_source == data_source)
elif data_frequency is not None:
applies = (
(data_frequency == 'minute' and a.end_minute is not None)
or (data_frequency == 'daily' and a.end_daily is not None))
else:
applies = True
# The symbol provided may use the Catalyst or the exchange
# convention
key = a.exchange_symbol if \
is_exchange_symbol else self.get_symbol(a)
if not asset and key.lower() == symbol.lower():
if applies:
asset = a
else:
raise NoDataAvailableOnExchange(
symbol=key,
exchange=self.name,
data_frequency=data_frequency,
)
if asset is None:
supported_symbols = sorted([a.symbol for a in self.assets])
raise SymbolNotFoundOnExchange(symbol=og_symbol,
exchange=self.name.title(),
supported_symbols=supported_symbols)
log.debug('found asset: {}'.format(asset))
return asset
