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FactSet Concordance client library for Python

Project description

FactSet

FactSet Concordance client library for Python

PyPi Apache-2 license

The FactSet Concordance API enables Application Developers and Data Scientists to programmatically discover the FactSet Identifier for a specific Entity or Person based on attributes, such as name, URL, and location.FactSet Identifiers are mapped to industry-standard identifiers, as well as to a comprehensive set of reference data and unique content, to enhance the ability to quickly connect content sets.

Using the submitted attributes, the FactSet Concordance API leverages FactSet’s extensive Entity Master, People, and Symbology databases to return potential candidate matches and a proposed match. The result is a concorded FactSet Identifier that can then be used as input throughout FactSet's expanding catalog of Content using our Content APIs or Standard DataFeeds.

There are two types of workflows supported in the API:

Entity & People Match: The first workflow follows traditional API conventions in that a request is accepted and a response is returned synchronously enabling the concordance of up to 25 names in a single request. The response returns a list of 20 candidates as well as a proposed match.

Entity & People Match - Bulk: The second workflow allows you to input a large list of names within a .CSV file in a single request With this workflow, a task is created for uploading a set of queries. Once the task has completed, the client retrieves the concordance results through the /entity-decisions or /people-decisions endpoint. Note that in the Bulk workflow, only the matches for the records are returned. Candidates are not included.

Once the service has provided a list of concorded FactSet Identifiers, you can then use our Entity Mappings and People Mappings endpoints to further review the universe of mapped identifiers or modify existing records.

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

  • API version: 2.6.0
  • Package version: 0.23.0
  • Build package: org.openapitools.codegen.languages.PythonClientCodegen

Requirements

  • Python >= 3.7

Installation

Poetry

poetry add fds.sdk.utils fds.sdk.FactSetConcordance

pip

pip install fds.sdk.utils fds.sdk.FactSetConcordance

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:
from fds.sdk.utils.authentication import ConfidentialClient

import fds.sdk.FactSetConcordance
from fds.sdk.FactSetConcordance.api import entity_mappings_api
from fds.sdk.FactSetConcordance.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
# See https://github.com/FactSet/enterprise-sdk-utils-python#authentication
# for more information on using the ConfidentialClient class
configuration = fds.sdk.FactSetConcordance.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.FactSetConcordance.Configuration(
#     username='USERNAME-SERIAL',
#     password='API-KEY'
# )

# Enter a context with an instance of the API client
with fds.sdk.FactSetConcordance.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = entity_mappings_api.EntityMappingsApi(api_client)
    entity_mapping_delete_request = EntityMappingDeleteRequest(
        universe_id=1,
        client_id=["abc-123","dfg-456"],
    ) # EntityMappingDeleteRequest | A request to delete entity mappings specified by the client

    try:
        # Deletes mapping specified by the client.
        api_response = api_instance.get_entity_mapping_delete_for_list(entity_mapping_delete_request)
        pprint(api_response)
    except fds.sdk.FactSetConcordance.ApiException as e:
        print("Exception when calling EntityMappingsApi->get_entity_mapping_delete_for_list: %s\n" % e)

    # Get response, http status code and response headers
    # try:
    #     # Deletes mapping specified by the client.
    #     api_response, http_status_code, response_headers = api_instance.get_entity_mapping_delete_for_list_with_http_info(entity_mapping_delete_request)
    #     pprint(api_response)
    #     pprint(http_status_code)
    #     pprint(response_headers)
    # except fds.sdk.FactSetConcordance.ApiException as e:
    #     print("Exception when calling EntityMappingsApi->get_entity_mapping_delete_for_list: %s\n" % e)

    # Get response asynchronous
    # try:
    #     # Deletes mapping specified by the client.
    #     async_result = api_instance.get_entity_mapping_delete_for_list_async(entity_mapping_delete_request)
    #     api_response = async_result.get()
    #     pprint(api_response)
    # except fds.sdk.FactSetConcordance.ApiException as e:
    #     print("Exception when calling EntityMappingsApi->get_entity_mapping_delete_for_list: %s\n" % e)

    # Get response, http status code and response headers asynchronous
    # try:
    #     # Deletes mapping specified by the client.
    #     async_result = api_instance.get_entity_mapping_delete_for_list_with_http_info_async(entity_mapping_delete_request)
    #     api_response, http_status_code, response_headers = async_result.get()
    #     pprint(api_response)
    #     pprint(http_status_code)
    #     pprint(response_headers)
    # except fds.sdk.FactSetConcordance.ApiException as e:
    #     print("Exception when calling EntityMappingsApi->get_entity_mapping_delete_for_list: %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.FactSetConcordance

logging.basicConfig(level=logging.DEBUG)

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

Documentation for API Endpoints

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

Class Method HTTP request Description
EntityMappingsApi get_entity_mapping_delete_for_list POST /factset-concordance/v2/entity-mapping-delete Deletes mapping specified by the client.
EntityMappingsApi get_entity_mapping_for_list POST /factset-concordance/v2/entity-mapping Saves a single-mapping specified by the client.
EntityMappingsApi get_entity_universe GET /factset-concordance/v2/entity-universe Retrieve all saved mappings within a requested universe
EntityMappingsApi get_entity_universe_for_list POST /factset-concordance/v2/entity-universe Retrieve all saved mappings within a requested universe or large list of client ids
EntityMatchApi get_entity_match GET /factset-concordance/v2/entity-match Get Entity Candidates and Matches for a single name and attributes.
EntityMatchApi get_entity_match_for_list POST /factset-concordance/v2/entity-match Get a list of Entity Candidates and Matches for a requested list of up to 25 names and attributes.
EntityMatchBulkApi get_entity_decisions GET /factset-concordance/v2/entity-decisions Get the decisions of matches for the requested taskId.
EntityMatchBulkApi get_entity_task_for_list POST /factset-concordance/v2/entity-task Input a file with names and attributes, creating a taskId.
EntityMatchBulkApi get_entity_task_status GET /factset-concordance/v2/entity-task-status Gets the status of the requested taskId or all tasks for a User
PeopleMappingApi get_people_mapping_delete_for_list POST /factset-concordance/v2/people-mapping-delete Deletes mapping specified by the client.
PeopleMappingApi get_people_mapping_for_list POST /factset-concordance/v2/people-mapping Saves a single-mapping specified by the client.
PeopleMappingApi get_people_universe GET /factset-concordance/v2/people-universe Retrieve all saved mappings within a requested universe
PeopleMappingApi get_people_universe_for_list POST /factset-concordance/v2/people-universe Retrieve all saved mappings within a requested universe or large list of client ids
PeopleMatchApi get_people_match GET /factset-concordance/v2/people-match Find potential people matches given a person's name.People matches can be retrieved using person's name and other attributes like firstname, middlename and lastname.
PeopleMatchApi get_people_match_for_list POST /factset-concordance/v2/people-match Find potential people matches given a person's name.
PeopleMatchBulkApi get_people_decisions GET /factset-concordance/v2/people-decisions Get the decisions of matches for the requested taskId.
PeopleMatchBulkApi get_people_task_for_list POST /factset-concordance/v2/people-task Create a People Concordance Task.
PeopleMatchBulkApi get_people_task_status GET /factset-concordance/v2/people-task-status Get the Status of the People Tasks.
SnowflakeApi get_snowflake_entity_match_for_list POST /factset-concordance/v2/snowflake-entity-match Perform an entity search and return a snowflake-friendly response. Up to 25 Names per request.
SnowflakeApi snowflake_entity_mapping_post POST /factset-concordance/v2/snowflake-entity-mapping Save entity mappings to a universe
UniversesApi get_entity_universe_statistics GET /factset-concordance/v2/entity-universe-statistics Get statistics on a given universe
UniversesApi get_universe_for_list POST /factset-concordance/v2/universe Create a new universe
UniversesApi get_universe_statistics GET /factset-concordance/v2/universe-statistics Get statistics on a given universe
UniversesApi get_universes GET /factset-concordance/v2/universes Fetch metadata for universes
UniversesApi get_update_universe_for_list POST /factset-concordance/v2/update-universe Update metadata for an existing universe

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

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