def test_get_coverage_api(mocker):
test_coverage_data = {'results': [{'gsid': 'gsid1'}]}
mocker.patch.object(ContextMeta, 'current', return_value=GsSession(Environment.QA))
mocker.patch.object(ContextMeta.current, '_get', return_value=test_coverage_data)
data = GsDataApi.get_coverage('MA_RANK')
assert [{'gsid': 'gsid1'}] == data
def test_get_coverage_api(mocker):
test_coverage_data_1 = {'results': [{'gsid': 'gsid1'}], 'scrollId': 'fake-scroll-id-1', 'totalResults': 1}
test_coverage_data_2 = {'results': [], 'scrollId': 'fake-scroll-id-2', 'totalResults': 1}
mocker.patch.object(ContextMeta, 'current', return_value=GsSession(Environment.QA))
mock = mocker.patch.object(ContextMeta.current, '_get')
mock.side_effect = [test_coverage_data_1, test_coverage_data_2]
data = GsDataApi.get_coverage('MA_RANK')
assert [{'gsid': 'gsid1'}] == data
def __get_dataset_trial_appendage(self):
availability_response = [model_dataset for model_dataset in
GsSession.current._get(f'/data/measures/{self.risk_model_id}/availability?entityType'
f'=RISK_MODEL').get('data')
if model_dataset.get('type') == 'Factor Return']
availability_response = sorted(availability_response, key=lambda k: k['rank'], reverse=True)
for availability in availability_response:
dataset_id = availability.get('datasetId')
models_covered = GsDataApi.get_coverage(dataset_id, limit=1000)
for model in models_covered:
if model.get('riskModel') == self.risk_model_id:
return dataset_id.replace('RISK_MODEL_FACTOR', '')
def get_flagships_constituents(
fields: [str] = [],
basket_type: List[BasketType] = BasketType.to_list(),
asset_class: List[AssetClass] = [AssetClass.Equity],
region: List[Region] = None,
styles: List[Union[CustomBasketStyles, ResearchBasketStyles]] = None,
start: dt.date = None,
end: dt.date = None,
) -> pd.DataFrame:
"""
Retrieve flagship baskets constituents
:param fields: Fields to retrieve in addition to mqid, name, ticker, region, basket type, \
styles, live date, and asset class
:param basket_type: Basket type(s)
:param asset_class: Asset class (defaults to Equity)
:param region: Basket region(s)
:param styles: Basket style(s)
:param start: Start date for which to retrieve constituents (defaults to previous business day)
:param end: End date for which to retrieve constituents (defaults to previous business day)
:return: flagship baskets constituents
**Usage**
Retrieve flagship baskets constituents
**Examples**
Retrieve a list of flagship baskets constituents
>>> from gs_quant.markets.indices_utils import *
>>>
>>> get_flagships_constituents()
**See also**
:func:`get_flagships_with_assets` :func:`get_flagships_performance` :func:`get_flagship_baskets`
"""
start = start or prev_business_date()
end = end or prev_business_date()
fields = list(
set(fields).union(
set([
'id', 'name', 'ticker', 'region', 'type', 'styles', 'liveDate',
'assetClass'
])))
query = dict(fields=fields,
type=basket_type,
asset_class=asset_class,
is_pair_basket=[False],
flagship=[True])
if region is not None:
query.update(region=region)
if styles is not None:
query.update(styles=styles)
basket_data = GsAssetApi.get_many_assets_data_scroll(**query,
limit=2000,
scroll='1m')
basket_map = {get(basket, 'id'): basket for basket in basket_data}
coverage = GsDataApi.get_coverage(
dataset_id=IndicesDatasets.GSCB_FLAGSHIP.value,
fields=['type', 'bbid'],
include_history=True)
cbs, rbs = [], []
for b in coverage:
_id = get(b, 'assetId')
_type = get(b, 'type')
if _id in list(basket_map.keys()):
start_date = dt.datetime.strptime(b['historyStartDate'],
'%Y-%m-%d').date()
start_date = start_date if start < start_date else start
if _type == BasketType.CUSTOM_BASKET.value:
data = GsDataApi.query_data(
query=DataQuery(where=dict(assetId=_id),
startDate=start_date,
endDate=end),
dataset_id=IndicesDatasets.GSBASKETCONSTITUENTS.value)
basket_map[_id].update(constituents=data)
cbs.append(basket_map[_id])
elif _type == BasketType.RESEARCH_BASKET.value:
data = GsDataApi.query_data(
query=DataQuery(where=dict(assetId=_id),
startDate=start_date,
endDate=end),
dataset_id=IndicesDatasets.GIRBASKETCONSTITUENTS.value)
basket_map[_id].update(constituents=data)
rbs.append(basket_map[_id])
return pd.DataFrame(cbs + rbs)
def get_flagships_performance(
fields: [str] = [],
basket_type: List[BasketType] = BasketType.to_list(),
asset_class: List[AssetClass] = [AssetClass.Equity],
region: List[Region] = None,
styles: List[Union[CustomBasketStyles, ResearchBasketStyles]] = None,
start: dt.date = None,
end: dt.date = None,
) -> pd.DataFrame:
"""
Retrieve performance data for flagship baskets
:param fields: Fields to retrieve in addition to bbid, mqid, name, region, basket type, \
styles, live date, and asset class
:param basket_type: Basket type(s)
:param asset_class: Asset class (defaults to Equity)
:param region: Basket region(s)
:param styles: Basket style(s)
:param start: Date for which to retrieve pricing (defaults to previous business day)
:param end: Date for which to retrieve pricing (defaults to previous business day)
:return: pricing data for flagship baskets
**Usage**
Retrieve performance data for flagship baskets
**Examples**
Retrieve performance data for flagship Asia custom baskets
>>> from gs_quant.markets.indices_utils import *
>>>
>>> get_flagships_performance(basket_type=[BasketType.CUSTOM_BASKET], region=[Region.ASIA])
**See also**
:func:`get_flagships_with_assets` :func:`get_flagship_baskets` :func:`get_flagships_constituents`
"""
start = start or prev_business_date()
end = end or prev_business_date()
fields = list(
set(fields).union(
set([
'name', 'region', 'type', 'flagship', 'isPairBasket', 'styles',
'liveDate', 'assetClass'
])))
coverage = GsDataApi.get_coverage(
dataset_id=IndicesDatasets.GSCB_FLAGSHIP.value, fields=fields)
basket_regions = [] if region is None else [r.value for r in region]
basket_styles = [] if styles is None else [s.value for s in styles]
basket_types = [b_type.value for b_type in basket_type]
baskets_map = {}
for basket in coverage:
if get(basket, 'flagship') is False or get(basket, 'isPairBasket') is True or \
region is not None and get(basket, 'region') not in basket_regions or \
get(basket, 'type') not in basket_types or \
get(basket, 'assetClass') not in [a.value for a in asset_class] or \
styles is not None and not any(s in get(basket, 'styles', []) for s in basket_styles):
continue
baskets_map[get(basket, 'assetId')] = basket
response = GsDataApi.query_data(
query=DataQuery(where=dict(assetId=list(baskets_map.keys())),
startDate=start,
endDate=end),
dataset_id=IndicesDatasets.GSCB_FLAGSHIP.value)
performance = []
for basket in response:
basket_data = baskets_map[get(basket, 'assetId')]
basket_data.update(closePrice=get(basket, 'closePrice'))
basket_data.update(date=get(basket, 'date'))
performance.append(basket_data)
return pd.DataFrame(performance)