def load_instruments(args):
file_type = "instruments"
# create ApiFactory
factory = ApiClientFactory(api_secrets_filename=args["secrets_file"])
# get data
if args["delimiter"]:
logging.info(f"delimiter specified as {repr(args['delimiter'])}")
logging.debug("Getting data")
instruments = load_data_to_df_and_detect_delimiter(args)
# get mappings
mappings = load_json_file(args["mapping"])
if "property_columns" in mappings[file_type].keys() and not args["scope"]:
err = (
r"properties must be upserted to a specified scope, but no scope was provided. "
r"Please state what scope to upsert properties to using '-s'.")
logging.error(err)
raise ValueError(err)
validate_mapping_file_structure(mappings, instruments.columns, file_type)
if "cash_flag" in mappings.keys():
instruments, mappings = identify_cash_items(instruments, mappings,
file_type, True)
if args["dryrun"]:
logging.info(
"--dryrun specified as True, exiting before upsert call is made")
return 0
instruments_response = load_from_data_frame(
api_factory=factory,
data_frame=instruments,
scope=args["scope"],
mapping_required=mappings[file_type]["required"],
mapping_optional=mappings[file_type]["optional"]
if "optional" in mappings[file_type].keys() else {},
file_type=file_type,
identifier_mapping=mappings[file_type]["identifier_mapping"],
batch_size=args["batch_size"],
property_columns=mappings[file_type]["property_columns"]
if "property_columns" in mappings[file_type].keys() else [],
)
succ, errors, failed = cocoon_printer.format_instruments_response(
instruments_response)
logging.info(f"number of successful upserts: {len(succ)}")
logging.info(f"number of failed upserts : {len(failed)}")
logging.info(f"number of errors : {len(errors)}")
if args["display_response_head"]:
logging.info(succ.head(40))
logging.info(errors.head(40))
logging.info(failed.head(40))
return instruments_response
def load_quotes(args):
file_type = "quotes"
# create ApiFactory
factory = ApiClientFactory(api_secrets_filename=args["secrets_file"])
# get data
if args["delimiter"]:
logging.info(f"delimiter specified as {repr(args['delimiter'])}")
logging.debug("Getting data")
quotes = load_data_to_df_and_detect_delimiter(args)
# get mappings
mappings = load_json_file(args["mapping"])
# check properties exist
if "property_columns" in mappings[file_type].keys() and not args["scope"]:
err = (
r"properties must be upserted to a specified scope, but no scope was provided. "
r"Please state what scope to upsert properties to using '-s'.")
logging.error(err)
raise ValueError(err)
quotes, mappings = identify_cash_items(quotes, mappings, "quotes", True)
validate_mapping_file_structure(mappings, quotes.columns, file_type)
if "quote_scalar" in mappings[file_type].keys():
quotes, mappings = scale_quote_of_type(quotes, mappings)
if args["dryrun"]:
return quotes
quotes_response = load_from_data_frame(
api_factory=factory,
data_frame=quotes,
scope=args["scope"],
properties_scope=args.get("property_scope", args["scope"]),
identifier_mapping={},
mapping_required=mappings[file_type]["required"],
mapping_optional=mappings[file_type].get("optional", {}),
file_type=file_type,
batch_size=args["batch_size"],
property_columns=mappings[file_type].get("property_columns", []),
)
succ, errors, failed = cocoon_printer.format_quotes_response(
quotes_response)
logging.info(f"number of successful upserts: {len(succ)}")
logging.info(f"number of failed upserts : {len(failed)}")
logging.info(f"number of errors : {len(errors)}")
if args["display_response_head"]:
logging.info(succ.head(40))
logging.info(errors.head(40))
logging.info(failed.head(40))
return quotes_response
def test_get_instruments_data(self, _, args_list):
data = load_data_to_df_and_detect_delimiter(args_list)
if args_list["num_header"] == 0:
self.assertEqual(data[data.columns[0]][0], "Amazon_Nasdaq_AMZN")
else:
self.assertEqual(data[data.columns[0]][0], "BP_LondonStockEx_BP")
if args_list["num_footer"] == 0:
self.assertEqual(
data.tail(1).values[0][0], "Whitebread_LondonStockEx_WTB")
else:
self.assertEqual(
data.tail(1).values[0][0], "USTreasury_6.875_2025")
print("")
def load_transactions(args):
file_type = "transactions"
factory = ApiClientFactory(api_secrets_filename=args["secrets_file"])
if args["delimiter"]:
logging.info(f"delimiter specified as {repr(args['delimiter'])}")
logging.debug("Getting data")
transactions = load_data_to_df_and_detect_delimiter(args)
mappings = load_json_file(args["mapping"])
if "cash_flag" in mappings.keys():
identify_cash_items(transactions, mappings, file_type)
validate_mapping_file_structure(mappings, transactions.columns, file_type)
if args["dryrun"]:
logging.info("--dryrun specified as True, exiting before upsert call is made")
return 0
transactions_response = load_from_data_frame(
api_factory=factory,
data_frame=transactions,
scope=args["scope"],
identifier_mapping=mappings[file_type]["identifier_mapping"],
mapping_required=mappings[file_type]["required"],
mapping_optional=mappings[file_type]["optional"]
if "optional" in mappings[file_type].keys()
else {},
file_type=file_type,
batch_size=args["batch_size"],
property_columns=mappings[file_type]["property_columns"]
if "property_columns" in mappings[file_type].keys()
else [],
)
# print_response(transactions_response, file_type)
succ, errors = cocoon_printer.format_transactions_response(transactions_response)
logging.info(f"number of successful upserts: {len(succ)}")
logging.info(f"number of errors : {len(errors)}")
if args["display_response_head"]:
logging.info(succ.head(40))
logging.info(errors.head(40))
return transactions_response
def load_holdings(args):
file_type = "holdings"
factory = ApiClientFactory(api_secrets_filename=args["secrets_file"])
if args["delimiter"]:
logging.info(f"delimiter specified as {repr(args['delimiter'])}")
logging.debug("Getting data")
holdings = load_data_to_df_and_detect_delimiter(args)
mappings = load_json_file(args["mapping"])
if "cash_flag" in mappings.keys():
holdings, mappings = identify_cash_items(holdings, mappings, file_type)
validate_mapping_file_structure(mappings, holdings.columns, file_type)
if args["dryrun"]:
logging.info(
"--dryrun specified as True, exiting before upsert call is made")
return 0
holdings_response = load_from_data_frame(
api_factory=factory,
data_frame=holdings,
scope=args["scope"],
properties_scope=args.get("property_scope", args["scope"]),
identifier_mapping=mappings[file_type]["identifier_mapping"],
mapping_required=mappings[file_type]["required"],
mapping_optional=mappings[file_type].get("optional", {}),
file_type=file_type,
batch_size=args["batch_size"],
property_columns=mappings[file_type].get("property_columns", []),
sub_holding_keys=mappings[file_type].get("sub_holding_keys", []),
)
succ, errors = cocoon_printer.format_holdings_response(holdings_response)
logging.info(f"number of successful upserts: {len(succ)}")
logging.info(f"number of errors : {len(errors)}")
if args["display_response_head"]:
logging.info(succ.head(40))
logging.info(errors.head(40))
return holdings_response
