def __create_query(cls,
fields: Union[List, Tuple] = None,
as_of: dt.datetime = None,
limit: int = None,
scroll: str = None,
scroll_id: str = None,
order_by: List[str] = None,
**kwargs) -> EntityQuery:
keys = set(kwargs.keys())
valid = keys.intersection(
i for i in dir(FieldFilterMap)
if isinstance(getattr(FieldFilterMap, i), property))
invalid = keys.difference(valid)
if invalid:
bad_args = ['{}={}'.format(k, kwargs[k]) for k in invalid]
raise KeyError('Invalid asset query argument(s): {}'.format(
', '.join(bad_args)))
return EntityQuery(where=FieldFilterMap(**kwargs),
fields=fields,
asOfTime=as_of or dt.datetime.utcnow(),
limit=limit,
scroll=scroll,
scroll_id=scroll_id,
order_by=order_by)
def test_get_many_assets(mocker, monkeypatch):
marquee_id_1 = 'MQA1234567890'
marquee_id_2 = 'MQA4567890123'
query = {'id': [marquee_id_1, marquee_id_2]}
as_of = dt.datetime.utcnow()
inputs = EntityQuery(where=FieldFilterMap(**query),
fields=None,
asOfTime=as_of,
limit=100)
mock_response = {
'results': (GsAsset.from_dict({
'id': marquee_id_1,
'assetClass': 'Equity',
'type': 'Single Stock',
'name': 'Test 1'
}),
GsAsset.from_dict({
'id': marquee_id_2,
'assetClass': 'Equity',
'type': 'Single Stock',
'name': 'Test 2'
}))
}
expected_response = (GsAsset(id=marquee_id_1,
assetClass='Equity',
type='Single Stock',
name='Test 1'),
GsAsset(id=marquee_id_2,
assetClass='Equity',
type='Single Stock',
name='Test 2'))
# mock GsSession
mocker.patch.object(GsSession.__class__,
'default_value',
return_value=GsSession.get(Environment.QA, 'client_id',
'secret'))
mocker.patch.object(GsSession.current, '_post', return_value=mock_response)
# run test
monkeypatch.delenv(ENABLE_ASSET_CACHING, raising=False)
response = GsAssetApi.get_many_assets(id=[marquee_id_1, marquee_id_2],
as_of=as_of)
GsSession.current._post.assert_called_with('/assets/query',
cls=GsAsset,
payload=inputs)
assert response == expected_response
monkeypatch.setenv(ENABLE_ASSET_CACHING, 1) # run 2x with cache on
response = GsAssetApi.get_many_assets(id=[marquee_id_1, marquee_id_2],
as_of=as_of)
assert response == expected_response
response = GsAssetApi.get_many_assets(id=[marquee_id_1, marquee_id_2],
as_of=as_of)
assert response == expected_response
def test_auto_scroll_on_pages(mocker):
response = {
"requestId": "049de678-1480000",
"totalPages": 5,
"data": [{
"date": "2012-01-25",
"assetId": "MADXKSGX6921CFNF",
"value": 1
}]
}
mocker.patch.object(ContextMeta,
'current',
return_value=GsSession(Environment.QA))
mocker.patch.object(ContextMeta.current, '_post', return_value=response)
query = DataQuery(start_date=dt.date(2017, 1, 15),
end_date=dt.date(2017, 1, 18),
where=FieldFilterMap(currency="GBP"))
response = GsDataApi.get_results("test", response, query)
assert len(response) == 5
def get_many_coordinates(
cls,
mkt_type: str = None,
mkt_asset: str = None,
mkt_class: str = None,
mkt_point: Tuple[str, ...] = (),
*,
limit: int = 100,
return_type: type = str,
) -> Union[Tuple[str, ...], Tuple[MarketDataCoordinate, ...]]:
where = FieldFilterMap(
mkt_type=mkt_type.upper() if mkt_type is not None else None,
mkt_asset=mkt_asset.upper() if mkt_asset is not None else None,
mkt_class=mkt_class.upper() if mkt_class is not None else None,
)
for index, point in enumerate(mkt_point):
setattr(where, 'mkt_point' + str(index + 1), point.upper())
query = EntityQuery(where=where, limit=limit)
results = GsSession.current._post('/data/mdapi/query',
query)['results']
if return_type is str:
return tuple(coordinate['name'] for coordinate in results)
elif return_type is MarketDataCoordinate:
return tuple(
MarketDataCoordinate(
mkt_type=coordinate['dimensions']['mktType'],
mkt_asset=coordinate['dimensions']['mktAsset'],
mkt_class=coordinate['dimensions']['mktClass'],
mkt_point=tuple(coordinate['dimensions']
['mktPoint'].values()),
mkt_quoting_style=coordinate['dimensions']
['mktQuotingStyle']) for coordinate in results)
else:
raise NotImplementedError('Unsupported return type')