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FactSet

FactSet Macroeconomics client library for Python

API Version PyPi Apache-2 license

The FactSet Macroeconomics API provides access to economic calendar events and historical time series data for global economic indicators. Use the reference endpoints to discover available indicators, regions, and FDS codes before querying event or series data.

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

  • API version: 1.0.0
  • SDK version: 0.1.0
  • Build package: org.openapitools.codegen.languages.PythonClientCodegen

For more information, please visit https://developer.factset.com/contact

Requirements

  • Python >= 3.7

Installation

Poetry

poetry add fds.sdk.utils fds.sdk.FactSetMacroeconomics==0.1.0

pip

pip install fds.sdk.utils fds.sdk.FactSetMacroeconomics==0.1.0

Usage

  1. Generate authentication credentials.
  2. Setup Python environment.
    1. Install and activate python 3.10+. If you're using pyenv:

      pyenv install 3.10.0
      pyenv shell 3.10.0
      
    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.FactSetMacroeconomics
from fds.sdk.FactSetMacroeconomics.api import as_reported_economics_api
from fds.sdk.FactSetMacroeconomics.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.FactSetMacroeconomics.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.FactSetMacroeconomics.Configuration(
#     username='USERNAME-SERIAL',
#     password='API-KEY'
# )

# Enter a context with an instance of the API client
with fds.sdk.FactSetMacroeconomics.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = as_reported_economics_api.AsReportedEconomicsApi(api_client)
    series_id = "FRBRIFSPPCD90@US" # str | The Series ID identifying the economic series to retrieve. Use the `/meta/series` endpoint to get a list of available series IDs. 
    start_date = dateutil_parser('Thu Jan 01 00:00:00 UTC 2026').date() # date | Start date for the query range.  - **Default:** If both `startDate` and `endDate` are omitted, the API defaults to the most recent available calendar day  (optional)
    end_date = dateutil_parser('Wed Jul 01 00:00:00 UTC 2026').date() # date | End date for the query range.  - **Default:** If both `startDate` and `endDate` are omitted, the API defaults to the most recent available calendar day  (optional)
    country_code = "US" # str | ISO country code for filtering events by country. Use the `/meta/events?type=countries` endpoint to retrieve available country codes.  (optional)
    frequency = "D" # str | Controls the output frequency of the data returned. The supported frequencies are:  - **D**: Daily. - **W**: Weekly. - **M**: Monthly. - **Q**: Quarterly. - **Y**: Yearly.  When `frequency` is not specified: If multiple frequencies are available for the seriesId, data is returned at the highest frequency (e.g., monthly over quarterly). If only one frequency is available, data is returned at that frequency.  (optional)
    pagination_limit = 25 # int | Maximum number of results to return per page. If not specified, the default page size is applied.  (optional) if omitted the server will use the default value of 25
    pagination_offset = 0 # int | Number of results to skip before returning the first result. Used for pagination in combination with `_paginationLimit`.  (optional) if omitted the server will use the default value of 0

    try:
        # Retrieve as-reported economic time series data
        # example passing only required values which don't have defaults set
        # and optional values
        api_response = api_instance.get_as_reported_economics(series_id, start_date=start_date, end_date=end_date, country_code=country_code, frequency=frequency, pagination_limit=pagination_limit, pagination_offset=pagination_offset)

        pprint(api_response)
    except fds.sdk.FactSetMacroeconomics.ApiException as e:
        print("Exception when calling AsReportedEconomicsApi->get_as_reported_economics: %s\n" % e)

    # # Get response, http status code and response headers
    # try:
    #     # Retrieve as-reported economic time series data
    #     api_response, http_status_code, response_headers = api_instance.get_as_reported_economics_with_http_info(series_id, start_date=start_date, end_date=end_date, country_code=country_code, frequency=frequency, pagination_limit=pagination_limit, pagination_offset=pagination_offset)


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

    # # Get response asynchronous
    # try:
    #     # Retrieve as-reported economic time series data
    #     async_result = api_instance.get_as_reported_economics_async(series_id, start_date=start_date, end_date=end_date, country_code=country_code, frequency=frequency, pagination_limit=pagination_limit, pagination_offset=pagination_offset)
    #     api_response = async_result.get()


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

    # # Get response, http status code and response headers asynchronous
    # try:
    #     # Retrieve as-reported economic time series data
    #     async_result = api_instance.get_as_reported_economics_with_http_info_async(series_id, start_date=start_date, end_date=end_date, country_code=country_code, frequency=frequency, pagination_limit=pagination_limit, pagination_offset=pagination_offset)
    #     api_response, http_status_code, response_headers = async_result.get()


    #     pprint(api_response)
    #     pprint(http_status_code)
    #     pprint(response_headers)
    # except fds.sdk.FactSetMacroeconomics.ApiException as e:
    #     print("Exception when calling AsReportedEconomicsApi->get_as_reported_economics: %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.FactSetMacroeconomics

logging.basicConfig(level=logging.DEBUG)

configuration = fds.sdk.FactSetMacroeconomics.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.FactSetMacroeconomics

configuration = fds.sdk.FactSetMacroeconomics.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.FactSetMacroeconomics

configuration = fds.sdk.FactSetMacroeconomics.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.FactSetMacroeconomics

configuration = fds.sdk.FactSetMacroeconomics.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/economics/v1

Class Method HTTP request Description
AsReportedEconomicsApi get_as_reported_economics GET /as-reported-economics Retrieve as-reported economic time series data
EconomicEventsCalendarApi get_economic_events GET /economic-events Retrieve economic calendar events
EconomicEventsCalendarApi get_economic_events_count GET /event-count Retrieve economic events count
ReferenceDataApi get_economic_event_reference_data GET /meta/events Retrieve reference data for events
ReferenceDataApi get_fds_code_mapping GET /meta/series Retrieve reference data for series

Documentation For Models

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.FactSetMacroeconomics.apis and fds.sdk.FactSetMacroeconomics.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.FactSetMacroeconomics.api.default_api import DefaultApi
  • from fds.sdk.FactSetMacroeconomics.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.FactSetMacroeconomics
from fds.sdk.FactSetMacroeconomics.apis import *
from fds.sdk.FactSetMacroeconomics.models import *

Contributing

Please refer to the contributing guide.

Copyright

Copyright 2026 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.

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