def handle_result(result: Optional[Union[DataFrameWithInfo, ErrorValue, PricingFuture]]) -> \
[OverlayMarket, dict]:
if isinstance(result, ErrorValue):
return result
properties = MarketDataCoordinate.properties()
is_historical = result.index.name == 'date'
location = PricingContext.current.market_data_location
def extract_market_data(this_result: DataFrameWithInfo):
market_data = {}
for _, row in this_result.iterrows():
coordinate_values = {p: row.get(p) for p in properties}
mkt_point = coordinate_values.get('mkt_point')
if mkt_point is not None:
coordinate_values['mkt_point'] = tuple(coordinate_values['mkt_point'].split(';'))
# return 'redacted' as coordinate value if its a redacted coordinate
market_data[MarketDataCoordinate.from_dict(coordinate_values)] = row['value'] if \
row['permissions'] == 'Granted' else 'redacted'
return market_data
if is_historical:
return {date: OverlayMarket(
base_market=CloseMarket(date=date, location=location),
market_data=extract_market_data(result.loc[date]))
for date in set(result.index)}
else:
return OverlayMarket(base_market=result.risk_key.market,
market_data=extract_market_data(result))
def handle_result(result: Optional[Union[DataFrameWithInfo, ErrorValue, PricingFuture]]) ->\
[OverlayMarket, dict]:
properties = MarketDataCoordinate.properties()
is_historical = isinstance(PricingContext.current,
HistoricalPricingContext)
location = PricingContext.current.market_data_location
def extract_market_data(this_result: DataFrameWithInfo):
market_data = {}
for _, row in result.iterrows():
coordinate_values = {p: row.get(p) for p in properties}
if 'mkt_point' in coordinate_values:
coordinate_values['mkt_point'] = tuple(
coordinate_values['mkt_point'].split(';'))
market_data[MarketDataCoordinate.from_dict(
coordinate_values)] = row['value']
return market_data
if is_historical:
return {
date: OverlayMarket(
base_market=CloseMarket(date=date, location=location),
market_data=extract_market_data(result.loc[date]))
for date in set(result.index)
}
else:
return OverlayMarket(base_market=result.risk_key.market,
market_data=extract_market_data(result))