fds.sdk.FactSetGeoRev 1.0.13

FactSet GeoRev client library for Python

FactSet GeoRev client library for Python

FactSet Revere Geographic Revenue ("GeoRev") Exposure data provides a highly structured and normalized display of companies' revenues by geography. Using a four level taxonomy structure, understand the companies' Super-Region-->Region-->Area-->Country revenue breakdowns. Quickly understand a company's revenue exposure in countries impacted by geopolitical, macroeconomic, and market risk. Understand the geographic footprint of a company based on sources of revenue versus country of domicile, and analyze global revenue exposures at the company, index, or portfolio level.

Geographic revenue has historically been difficult to analyze due to companies' non-standard and incomplete reporting. Investors relying solely on this as-reported data are limited in their ability to compare, aggregate or screen exposures across a universe or portfolio of companies. To achieve normalization, FactSet GeoRev captures data through a proprietary four-level geographic classification structure. An estimation algorithm based on GDP weighting and accounting logic is then applied to solve for any non-explicit disclosures. The result is a consistent, accurate, and flexible dataset that can take a company's revenues and break them down into any geographic country or region categories.

As markets become more integrated and companies expand operations beyond their domestic markets, GeoRev provides a new and valuable country factor to help investors discover alpha, model risk exposure, optimize portfolio weighting, and improve fund administration and reporting.

Data Frequency - Annual; Update Frequency - Daily. 49,000+ Publically Listed Companies. All Russell 3000 and MSCI ACWI Index Consituents. U.S. Data is available from 2003, with Non-US data from 2007. For more details, visit OA 17555

Rate limit is set to 10 requests per second.

This Python package is automatically generated by the OpenAPI Generator project:

• API version: 1.0.1
• SDK version: 1.0.13
• Build package: org.openapitools.codegen.languages.PythonClientCodegen

Requirements

• Python >= 3.7

Installation

Poetry

poetry add fds.sdk.utils fds.sdk.FactSetGeoRev==1.0.13

pip

pip install fds.sdk.utils fds.sdk.FactSetGeoRev==1.0.13

Usage

1. Generate authentication credentials.
2. Setup Python environment.

   1. Install and activate python 3.7+. If you're using pyenv:

      pyenv install 3.9.7
      pyenv shell 3.9.7
      

   2. (optional) Install poetry.

3. Install dependencies.
4. Run the following:

[!IMPORTANT] The parameter variables defined below are just examples and may potentially contain non valid values. Please replace them with valid values.

Example Code

from fds.sdk.utils.authentication import ConfidentialClient

import fds.sdk.FactSetGeoRev
from fds.sdk.FactSetGeoRev.api import countries_api
from fds.sdk.FactSetGeoRev.models import *
from dateutil.parser import parse as dateutil_parser
from pprint import pprint

# See configuration.py for a list of all supported configuration parameters.

# Examples for each supported authentication method are below,
# choose one that satisfies your use case.

# (Preferred) OAuth 2.0: FactSetOAuth2
# See https://github.com/FactSet/enterprise-sdk#oauth-20
# for information on how to create the app-config.json file
#
# The confidential client instance should be reused in production environments.
# See https://github.com/FactSet/enterprise-sdk-utils-python#authentication
# for more information on using the ConfidentialClient class
configuration = fds.sdk.FactSetGeoRev.Configuration(
    fds_oauth_client=ConfidentialClient('/path/to/app-config.json')
)

# Basic authentication: FactSetApiKey
# See https://github.com/FactSet/enterprise-sdk#api-key
# for information how to create an API key
# configuration = fds.sdk.FactSetGeoRev.Configuration(
#     username='USERNAME-SERIAL',
#     password='API-KEY'
# )

# Enter a context with an instance of the API client
with fds.sdk.FactSetGeoRev.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = countries_api.CountriesApi(api_client)
    ids = ["AAPL-USA"] # [str] | Security or Entity identifiers. FactSet Identifiers, tickers, CUSIP and SEDOL are accepted input. <p>***ids limit** =  300 per request*</p> *<p>Make note, GET Method URL request lines are also limited to a total length of 8192 bytes (8KB). In cases where the service allows for thousands of ids, which may lead to exceeding this request line limit of 8KB, its advised for any requests with large request lines to be requested through the respective \"POST\" method.</p>* 
    country_ids = ["US","CN"] # [str] | The Country ISO2 Codes representing the Country requested. By default, the service will request *ALL* Countries. To limit the Countries returned in the response, provide a comma-separated list of the ISO2 Country Codes. Visit [OA 8754](https://my.apps.factset.com/oa/pages/8754) for a full list of ISO2 codes.  (optional) if omitted the server will use the default value of ["ALL"]
    start_date = "2018-12-31" # str | The start date requested for a given date range in **YYYY-MM-DD** format. Data is available on a Fiscal Annual periodicity and updated Daily. If left blank, the API will default to latest available fiscal period. Future dates (T+1) are not accepted in this endpoint.  (optional)
    end_date = "2019-12-31" # str | The end date requested for a given date range in **YYYY-MM-DD** format. Data is available on a Fiscal Annual periodicity and updated daily. If left blank, the API will default to latest available fiscal period. Future dates (T+1) are not accepted in this endpoint.  (optional)
    frequency = "FY" # str | Controls the display frequency of the data returned.   * **D** = Daily   * **W** = Weekly, based on the last day of the week of the start date.   * **M** = Monthly, based on the last trading day of the month.   * **AM** = Monthly, based on the start date (e.g., if the start date is June 16, data is displayed for June 16, May 16, April 16 etc.).   * **CQ** = Quarterly based on the last trading day of the calendar quarter (March, June, September, or December).   * **FQ** = Fiscal Quarter of the company.   * **AY** = Actual Annual, based on the start date.   * **CY** = Calendar Annual, based on the last trading day of the calendar year.   * **FY** = Fiscal Annual, based on the last trading day of the company's fiscal year.     (optional) if omitted the server will use the default value of "FY"
    currency = "USD" # str | Currency code for adjusting the data. For a list of currency ISO codes, visit [Online Assistant Page #1470](https://oa.apps.factset.com/pages/1470). (optional)

    try:
        # Gets the revenue details for the requested Countries.
        # example passing only required values which don't have defaults set
        # and optional values
        api_response = api_instance.get_countries(ids, country_ids=country_ids, start_date=start_date, end_date=end_date, frequency=frequency, currency=currency)

        pprint(api_response)
    except fds.sdk.FactSetGeoRev.ApiException as e:
        print("Exception when calling CountriesApi->get_countries: %s\n" % e)

    # # Get response, http status code and response headers
    # try:
    #     # Gets the revenue details for the requested Countries.
    #     api_response, http_status_code, response_headers = api_instance.get_countries_with_http_info(ids, country_ids=country_ids, start_date=start_date, end_date=end_date, frequency=frequency, currency=currency)


    #     pprint(api_response)
    #     pprint(http_status_code)
    #     pprint(response_headers)
    # except fds.sdk.FactSetGeoRev.ApiException as e:
    #     print("Exception when calling CountriesApi->get_countries: %s\n" % e)

    # # Get response asynchronous
    # try:
    #     # Gets the revenue details for the requested Countries.
    #     async_result = api_instance.get_countries_async(ids, country_ids=country_ids, start_date=start_date, end_date=end_date, frequency=frequency, currency=currency)
    #     api_response = async_result.get()


    #     pprint(api_response)
    # except fds.sdk.FactSetGeoRev.ApiException as e:
    #     print("Exception when calling CountriesApi->get_countries: %s\n" % e)

    # # Get response, http status code and response headers asynchronous
    # try:
    #     # Gets the revenue details for the requested Countries.
    #     async_result = api_instance.get_countries_with_http_info_async(ids, country_ids=country_ids, start_date=start_date, end_date=end_date, frequency=frequency, currency=currency)
    #     api_response, http_status_code, response_headers = async_result.get()


    #     pprint(api_response)
    #     pprint(http_status_code)
    #     pprint(response_headers)
    # except fds.sdk.FactSetGeoRev.ApiException as e:
    #     print("Exception when calling CountriesApi->get_countries: %s\n" % e)

Using Pandas

To convert an API response to a Pandas DataFrame, it is necessary to transform it first to a dictionary.

import pandas as pd

response_dict = api_response.to_dict()['data']

simple_json_response = pd.DataFrame(response_dict)
nested_json_response = pd.json_normalize(response_dict)

Debugging

The SDK uses the standard library logging module.

Setting debug to True on an instance of the Configuration class sets the log-level of related packages to DEBUG and enables additional logging in Pythons HTTP Client.

Note: This prints out sensitive information (e.g. the full request and response). Use with care.

import logging
import fds.sdk.FactSetGeoRev

logging.basicConfig(level=logging.DEBUG)

configuration = fds.sdk.FactSetGeoRev.Configuration(...)
configuration.debug = True

Configure a Proxy

You can pass proxy settings to the Configuration class:

• proxy: The URL of the proxy to use.
• proxy_headers: a dictionary to pass additional headers to the proxy (e.g. Proxy-Authorization).

import fds.sdk.FactSetGeoRev

configuration = fds.sdk.FactSetGeoRev.Configuration(
    # ...
    proxy="http://secret:password@localhost:5050",
    proxy_headers={
        "Custom-Proxy-Header": "Custom-Proxy-Header-Value"
    }
)

Custom SSL Certificate

TLS/SSL certificate verification can be configured with the following Configuration parameters:

• ssl_ca_cert: a path to the certificate to use for verification in PEM format.
• verify_ssl: setting this to False disables the verification of certificates. Disabling the verification is not recommended, but it might be useful during local development or testing.

import fds.sdk.FactSetGeoRev

configuration = fds.sdk.FactSetGeoRev.Configuration(
    # ...
    ssl_ca_cert='/path/to/ca.pem'
)

Request Retries

In case the request retry behaviour should be customized, it is possible to pass a urllib3.Retry object to the retry property of the Configuration.

from urllib3 import Retry
import fds.sdk.FactSetGeoRev

configuration = fds.sdk.FactSetGeoRev.Configuration(
    # ...
)

configuration.retries = Retry(total=3, status_forcelist=[500, 502, 503, 504])

Documentation for API Endpoints

All URIs are relative to https://api.factset.com/content

Class	Method	HTTP request	Description
CountriesApi	get_countries	GET /factset-georev/v1/countries	Gets the revenue details for the requested Countries.
CountriesApi	get_countries_for_list	POST /factset-georev/v1/countries	Gets the revenue details for the requested Countries. Use for large lists of ids.
RegionsApi	get_regions	GET /factset-georev/v1/regions	Gets the revenue details for the requested Regions
RegionsApi	get_regions_for_list	POST /factset-georev/v1/regions	Gets the revenue details for the requested Regions. Use for large lists of company ids.

Documentation For Models

• Country
• CountryIds
• CountryRequest
• CountryResponse
• ErrorResponse
• ErrorResponseSubErrors
• Frequency
• Ids
• Region
• RegionIds
• RegionRequest
• RegionResponse

Documentation For Authorization

FactSetApiKey

• Type: HTTP basic authentication

FactSetOAuth2

• Type: OAuth
• Flow: application
• Authorization URL:
• Scopes: N/A

Notes for Large OpenAPI documents

If the OpenAPI document is large, imports in fds.sdk.FactSetGeoRev.apis and fds.sdk.FactSetGeoRev.models may fail with a RecursionError indicating the maximum recursion limit has been exceeded. In that case, there are a couple of solutions:

Solution 1: Use specific imports for apis and models like:

• from fds.sdk.FactSetGeoRev.api.default_api import DefaultApi
• from fds.sdk.FactSetGeoRev.model.pet import Pet

Solution 2: Before importing the package, adjust the maximum recursion limit as shown below:

import sys
sys.setrecursionlimit(1500)
import fds.sdk.FactSetGeoRev
from fds.sdk.FactSetGeoRev.apis import *
from fds.sdk.FactSetGeoRev.models import *

Contributing

Please refer to the contributing guide.

Copyright

Copyright 2022 FactSet Research Systems Inc

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.