def create_aggregation_request(analyst_scope_code, today, quotes_date):
# Create our aggregation request
inline_recipe = models.ConfigurationRecipe(
scope="User",
code='quotes_recipe',
market=models.MarketContext(
market_rules=[
models.MarketDataKeyRule(
key='Equity.LusidInstrumentId.*',
supplier='DataScope',
data_scope=analyst_scope_code,
quote_type='Price',
field='Mid',
quote_interval=quotes_date.strftime("%Y-%m-%d"))
],
suppliers=models.MarketContextSuppliers(commodity='DataScope',
credit='DataScope',
equity='DataScope',
fx='DataScope',
rates='DataScope'),
options=models.MarketOptions(
default_supplier='DataScope',
default_instrument_code_type='LusidInstrumentId',
default_scope=analyst_scope_code)),
)
aggregation_request = models.AggregationRequest(
inline_recipe=inline_recipe,
effective_at=today,
metrics=[
models.AggregateSpec(key='Instrument/default/LusidInstrumentId',
op='Value'),
models.AggregateSpec(key='Holding/default/Units', op='Sum'),
models.AggregateSpec(key='Holding/default/Cost', op='Sum'),
models.AggregateSpec(key='Holding/default/PV', op='Sum'),
models.AggregateSpec(key='Holding/default/Price', op='Sum')
],
group_by=['Instrument/default/LusidInstrumentId'])
return aggregation_request
def valuation(api_factory, marketdata_scope, portfolio_group, time):
time_parts = [time[:10], time[11:]]
if time_parts[1] == "LSE_market_close":
time_parts[1] = "16:30:00.000000+00:00"
elif time_parts[1] == "NYSE_market_close":
time_parts[1] = "21:00:00.000000+00:00"
time = "T".join(time_parts)
# Create a recipe to perform a valuation
configuration_recipe = models.ConfigurationRecipe(
scope="User",
code="quotes_recipe",
market=models.MarketContext(
market_rules=[
models.MarketDataKeyRule(
key="Equity.Figi.*",
supplier="DataScope",
data_scope=marketdata_scope,
quote_type="Price",
field="Mid",
),
models.MarketDataKeyRule(
key="Equity.Isin.*",
supplier="DataScope",
data_scope=marketdata_scope,
quote_type="Price",
field="Mid",
),
models.MarketDataKeyRule(
key="Equity.LusidInstrumentId.*",
supplier="DataScope",
data_scope=marketdata_scope,
quote_type="Price",
field="Mid",
),
models.MarketDataKeyRule(
key="Fx.CurrencyPair.*",
supplier="DataScope",
data_scope=marketdata_scope,
quote_type="Rate",
field="Mid",
),
],
suppliers=models.MarketContextSuppliers(
commodity="DataScope",
credit="DataScope",
equity="DataScope",
fx="DataScope",
rates="DataScope",
),
options=models.MarketOptions(
default_supplier="DataScope",
default_instrument_code_type="Figi",
default_scope=marketdata_scope,
),
),
)
upsert_configuration_recipe_response = api_factory.build(
lusid.api.ConfigurationRecipeApi).upsert_configuration_recipe(
upsert_recipe_request=models.UpsertRecipeRequest(
configuration_recipe=configuration_recipe))
# Create the valuation request
valuation_request = models.ValuationRequest(
recipe_id=models.ResourceId(scope="User", code="quotes_recipe"),
metrics=[
models.AggregateSpec(key="Instrument/default/LusidInstrumentId",
op="Value"),
models.AggregateSpec(key="Instrument/default/Name", op="Value"),
models.AggregateSpec(key="Holding/default/Units", op="Sum"),
models.AggregateSpec(key="Holding/default/Cost", op="Sum"),
models.AggregateSpec(key="Holding/default/PV", op="Sum"),
models.AggregateSpec(key="Holding/default/PV", op="Proportion"),
],
group_by=["Instrument/default/LusidInstrumentId"],
portfolio_entity_ids=[
models.PortfolioEntityId(
scope=portfolio_group.scope,
code=portfolio_group.code,
portfolio_entity_type="GroupPortfolio",
)
],
valuation_schedule=models.ValuationSchedule(effective_at=time),
)
# Perform a valuation
response = api_factory.build(lusid.api.AggregationApi).get_valuation(
valuation_request=valuation_request)
dataframe = prettyprint.aggregation_responses_generic_df([response])
dataframe = dataframe.append(dataframe.sum(numeric_only=True),
ignore_index=True)
return dataframe