Instruments Master

Instruments master

This section demonstrates how instruments can be loaded into LUSID from a source file. This file could be a securities master, or any other file containing instrument data such as a transactions file.

The table below shows an extract from a typical instruments file.

inst_name	FIGI_id	Ticker	Market Sector	Currency	Security type
Apple	BBG0013T5HY0	APPLE	M-Mkt	USD	Common Stock
MICROSOFT CORP	BBG007F5XJZ0	MSFTCHF	Corp	USD	Common Stock
UBER Tech	BBG00NW4HSM1	UBER	Equity	USD	Common Stock
USD		USD		USD	Cash
JPY		JPY		JPY	Currency

In order to load the instrument data, each field on the request must be mapped to its appropriate column in the source data. For example, the Figi identifier in this file is labeled as "FIGI_id" and must be mapped to the "Figi" parameter in our request. The required fields can be found in the API documentation for Upsert Instruments.

In this example the source file also contains some cash items which have a security type of "Cash" or "Currency". The utility function identify_cash_items() is used here to identify cash by searching for specific values in a field, then assigning them a __currency_identifier_for_LUSID inherited from the source currency column. The configuration for this is provided in the cash_flag mapping, for more information on the behaviour, see documentation for identify_cash_items().

mapping ={
    "instrument": {
        "identifier_mapping": {
            "Figi": "FIGI_id",
            "Ticker": "Ticker"
        }
        "required": {
            "name": {
                "column": "inst_name",
                "default": "Name Not Found"
            }
        },
        "properties": ["market Sector"]
    }
    "cash_flag": {
        "cash_identifiers": {
            "Security type": ["Cash", "Currency"]
        }
        "implicit": "currency"
    }
}

from lusid.utilities import ApiClientFactory
import lusid_sample_data as sd
from lusidtools.cocoon import cocoon_printer as cp
import pandas as pd
import os
# get client
Api_factory =  ApiClientFactory(api_secrets_filename="c:full/path/to/secrets.json")

# load data
df = pd.load_excel("/path/to/data.XLSX")

# Specify scope
scope = "test_scope_1"

# Identify cash items 
instruments, mapping = identify_cash_items(df.copy(),
                                           mappings,
                                           "instruments")

result = lusidtools.cocoon.load_from_data_frame(
    api_factory=api_factory,
    scope=scope,
    data_frame=instruments,
    mapping_required=mapping["instruments"]["required"],
    mapping_optional={},
    file_type="instruments",
    identifier_mapping=mapping["instruments"]["identifier_mapping"],
    property_columns=mapping["instruments"]["properties"],
    properties_scope=scope
)