def _get_esg_breakdown(self,
card: ESGCard,
measure: ESGMeasure,
pricing_date: dt.date = None) -> pd.DataFrame:
sector_data = GsEsgApi.get_esg(entity_id=self.id,
pricing_date=pricing_date,
cards=[card],
measures=[measure]).get(card.value)[0].get('results')
df = pd.DataFrame(sector_data)
return df.set_index('name')
def _get_esg_ranked_card(self,
card: ESGCard,
measure: ESGMeasure,
pricing_date: dt.date = None) -> pd.DataFrame:
data = GsEsgApi.get_esg(entity_id=self.id,
pricing_date=pricing_date,
cards=[card],
measures=[measure]).get(card.value)[0].get('results')
df = pd.DataFrame(data)
return df.set_index('assetId')
def get_esg_quintiles(self,
measure: ESGMeasure,
pricing_date: dt.date = None) -> pd.DataFrame:
"""
Get breakdown of entity by weight in each percentile quintile for requested ESG measure
:param measure: ESG Measure
:param pricing_date: optional pricing date; defaults to last previous business day
:return: a Pandas DataFrame with results
"""
quintile_data = GsEsgApi.get_esg(entity_id=self.id,
pricing_date=pricing_date,
cards=[ESGCard.QUINTILES],
measures=[measure]).get('quintiles')[0].get('results')
df = pd.DataFrame(quintile_data)
df = df.filter(items=['description', 'gross', 'long', 'short'])
return df.set_index('description')
def get_all_esg_data(self,
measures: List[ESGMeasure] = None,
cards: List[ESGCard] = None,
pricing_date: dt.date = None,
benchmark_id: str = None) -> Dict:
"""
Get all ESG Data
:param measures: list of ESG Measures to include in results
:param cards: list of ESG Cards to include in results
:param pricing_date: optional pricing date; defaults to last previous business day
:param benchmark_id: optional benchmark asset ID to include in results
:return: a dictionary of results
"""
return GsEsgApi.get_esg(entity_id=self.id,
pricing_date=pricing_date,
cards=cards if cards else [c for c in ESGCard],
measures=measures if measures else [m for m in ESGMeasure],
benchmark_id=benchmark_id)
def get_esg_summary(self, pricing_date: dt.date = None) -> pd.DataFrame:
summary_data = GsEsgApi.get_esg(entity_id=self.id,
pricing_date=pricing_date,
cards=[ESGCard.SUMMARY]).get('summary')
return pd.DataFrame(summary_data)
def test_get_risk_models(mocker):
mock_response = {
'pricingDate': '2021-04-08',
'summary': {
'gross': {
'gPercentile': 97.57,
'gRegionalPercentile': 88.94,
'esPercentile': 89.52,
'esDisclosurePercentage': 83.33,
'esMomentumPercentile': 28.15
},
'long': {
'gPercentile': 97.57,
'gRegionalPercentile': 88.94,
'esPercentile': 89.52,
'esDisclosurePercentage': 83.33,
'esMomentumPercentile': 28.15},
'short': {
'gPercentile': None,
'gRegionalPercentile': None,
'esPercentile': None,
'esDisclosurePercentage': None,
'esMomentumPercentile': None
},
'benchmark': {
'gPercentile': 76.30923829640506,
'gRegionalPercentile': 54.3718544735162,
'esPercentile': 51.677217204614415,
'esDisclosurePercentage': 54.89969169789053,
'esMomentumPercentile': 48.186284955203256
}
},
'bottomTenRanked': [
{
'measure': 'gPercentile',
'results': [
{
'assetId': 'MA4B66MW5E27UAHKG34',
'name': 'The Goldman Sachs Group, Inc.',
'value': 97.57
}
]
}, {
'measure': 'esDisclosurePercentage',
'results': [
{
'assetId': 'MA4B66MW5E27UAHKG34',
'name': 'The Goldman Sachs Group, Inc.',
'value': 83.33
}
]
}
],
'noESGData': {
'gross': {
'weight': 0.0,
'assets': []
},
'long': {
'weight': 0.0,
'assets': []
},
'short': {
'weight': 0.0,
'assets': []
},
'benchmark': {
'weight': 2.5402270308391683,
'assets': [
{
'assetId': 'MA4B66MW5E27UALNB96',
'name': 'News Corp - Class B',
'weight': 0.026140889953506573
}, {
'assetId': 'MA4B66MW5E27UANLXX3',
'name': 'Under Armour Inc-Class C',
'weight': 0.02019587639265163
}, {
'assetId': 'MA4B66MW5E27UAGYZ49',
'name': 'Alphabet Inc-CL C',
'weight': 2.4141476728491242
}, {
'assetId': 'MA4B66MW5E27UAE4MGB',
'name': 'Discovery Inc-C',
'weight': 0.03970496421509619
}, {
'assetId': 'MA4B66MW5E27UAGEHL4',
'name': 'Fox Corp - Class A',
'weight': 0.040037627428790246
}
]
}
}
}
# mock GsSession
mocker.patch.object(
GsSession.__class__,
'default_value',
return_value=GsSession.get(
Environment.QA,
'client_id',
'secret'))
mocker.patch.object(GsSession.current, '_get', return_value=mock_response)
# run test
response = GsEsgApi.get_esg(entity_id='MPM9Y3434RDFVKA3',
benchmark_id='MA4B66MW5E27U8P32SB',
pricing_date=dt.date(2021, 4, 8),
measures=[Measure.G_PERCENTILE, Measure.ES_DISCLOSURE_PERCENTAGE],
cards=[Card.SUMMARY, Card.BOTTOM_TEN_RANKED])
GsSession.current._get.assert_called_with(
'/esg/MPM9Y3434RDFVKA3?&date=2021-04-08&benchmark=MA4B66MW5E27U8P32SB&measure=gPercentile&'
'measure=esDisclosurePercentage&card=summary&card=bottomTenRanked')
assert response == mock_response
