def scalar_formatter(
result: List, pricing_key: PricingKey
) -> Optional[Union[FloatWithInfo, SeriesWithInfo]]:
if not result:
return None
result = __flatten_result(result)
if len(result) > 1 and 'date' in result[0]:
r = [
__float_with_info_from_result(
r, pricing_key.for_pricing_date(r['date'])) for r in result
]
return FloatWithInfo.compose(r, pricing_key)
else:
return __float_with_info_from_result(result[0], pricing_key)
def scalar_formatter(result: List, pricing_key: PricingKey, _instrument: InstrumentBase)\
-> Optional[Union[FloatWithInfo, SeriesWithInfo]]:
if not result:
return None
result = __flatten_result(result)
if len(result) > 1 and 'date' in result[0]:
columns = [x for x in result[0].keys() if x != 'value']
compressed_results = pd.DataFrame(result).groupby(columns).sum().reset_index().to_dict('records')
r = [__float_with_info_from_result(r, pricing_key.for_pricing_date(r['date'])) for r in compressed_results]
return FloatWithInfo.compose(
r,
pricing_key)
else:
return __float_with_info_from_result(result[0], pricing_key)