def test_get_props(self):
result = get_props.main(
parse=lambda: get_props.parse(
args=["--secrets", f"{self.secrets_file}"]),
display_df=self.display_df,
)
self.validate_results_df(result)
def process_args(api, args):
MAX_PROPS = 50
def success(result):
idents = [f"identifiers.KEY:{v}" for v in args.identifiers]
columns = ["lusid_instrument_id", "name"]
columns.extend(idents)
if args.properties:
columns.extend(["P:" + v for v in args.properties])
df = lpt.to_df(result.content.values.values(), columns)
return df.rename(columns=dict(zip(idents, args.identifiers)))
if args.from_file:
df = pd.read_csv(
args.from_file[0])[args.from_file[1:]].drop_duplicates()
args.instrument.extend(df[args.from_file[1]].values)
def step3(result, props_remaining, final_dataframe):
df = success(result)
if final_dataframe is None:
final_dataframe = df
else:
props = [c for c in df.columns.values if c.startswith("P:")]
final_dataframe = final_dataframe.merge(
df[["lusid_instrument_id"] + props],
how="left",
on="lusid_instrument_id",
)
if len(props_remaining) > 0:
args.properties = props_remaining[:MAX_PROPS]
remaining = props_remaining[MAX_PROPS:]
return api.call.get_instruments(
args.type,
args.instrument,
instrument_property_keys=args.properties).bind(
lambda r: step3(r, remaining, final_dataframe))
return final_dataframe
def step2(result=None):
next_step = success
if result is not None:
# Contains full set of instrument properties
l = list(
result.apply(lambda r: f"Instrument/{r['scope']}/{r['code']}",
axis=1))
args.properties = l[:MAX_PROPS] # limitation
if len(l) > MAX_PROPS:
next_step = lambda r: step3(r, l[MAX_PROPS:], None)
return api.call.get_instruments(
args.type,
args.instrument,
instrument_property_keys=args.properties).bind(next_step)
if args.identifiers is None:
args.identifiers = [args.type]
if args.properties:
if args.properties[0] == "all":
from lusidtools.lpt import qry_properties as qp
return qp.process_args(
api, qp.parse(args=["-d", "Instrument"])).bind(step2)
return step2()