FactSet Concordance client library for Python
Project description
FactSet Concordance client library for Python
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: 0.23.3
- 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
- Generate authentication credentials.
- Setup Python environment.
-
Install and activate python 3.7+. If you're using pyenv:
pyenv install 3.9.7 pyenv shell 3.9.7
-
(optional) Install poetry.
-
- Install dependencies.
- 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)
# NOTE: The parameter variable defined below is just an example and may potentially contain non valid values. So please replace this with valid values.
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
- CreateUniverseRequest
- EntityDecisionsResponse
- EntityMapping
- EntityMappingDeleteRequest
- EntityMappingDeleteResponse
- EntityMappingRequest
- EntityMappingResponse
- EntityMatch
- EntityMatchRequest
- EntityMatchRequestInput
- EntityMatchesResponse
- EntityResponse
- EntityTaskResponse
- EntityTaskStatus
- EntityTaskStatusResponse
- EntityUniverseRequest
- EntityUniverseResponse
- EntityUniverseStatisticsResponse
- ErrorResponse
- ErrorResponseSubErrors
- MapStatus
- PeopleDecisions
- PeopleDecisionsResponse
- PeopleMapping
- PeopleMappingDeleteResponse
- PeopleMappingRequest
- PeopleMappingResponse
- PeopleMatch
- PeopleMatchRequest
- PeopleMatchRequestInput
- PeopleMatchesResponse
- PeopleTask
- PeopleTaskResponse
- PeopleTaskStatus
- PeopleTaskStatusResponse
- PeopleUniverseRequest
- PeopleUniverseResponse
- SnowflakeEntityMappingRequest
- SnowflakeEntityMappingResponse
- SnowflakeEntityMatchRequest
- SnowflakeEntityMatchResponse
- Universe
- UniverseMeta
- UniverseMetaResponse
- UniverseStatistics
- UniverseStatisticsResponse
- UniversesResponse
- UpdateUniverseRequest
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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