Package: fds.sdk.AITextSummarization
AI Text Summarization client library for PythonAI Text SummarizationThis Python package is automatically generated by theOpenAPI Generatorproject:API version: 1.0.0Package version: 0.21.8Build package: org.openapitools.codegen.languages.PythonClientCodegenRequirementsPython >= 3.7InstallationPoetrypoetryaddfds.sdk.utilsfds.sdk.AITextSummarization==0.21.8pippipinstallfds.sdk.utilsfds.sdk.AITextSummarization==0.21.8UsageGenerate authentication credentials.Setup Python environment.Install and activate python 3.7+. If you're usingpyenv:pyenvinstall3.9.7
pyenvshell3.9.7(optional)Install poetry.Install dependencies.Run the following:fromfds.sdk.utils.authenticationimportConfidentialClientimportfds.sdk.AITextSummarizationfromfds.sdk.AITextSummarization.apiimportdefault_apifromfds.sdk.AITextSummarization.modelsimport*fromdateutil.parserimportparseasdateutil_parserfrompprintimportpprint# 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 classconfiguration=fds.sdk.AITextSummarization.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.AITextSummarization.Configuration(#     username='USERNAME-SERIAL',#     password='API-KEY'# )# Enter a context with an instance of the API clientwithfds.sdk.AITextSummarization.ApiClient(configuration)asapi_client:# Create an instance of the API classapi_instance=default_api.DefaultApi(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.result_id="result_id_example"# str |try:# GET request that returns the full headline and summary results from the initial POST requests# example passing only required values which don't have defaults setapi_response=api_instance.get_result_v1_result_result_id(result_id)pprint(api_response)exceptfds.sdk.AITextSummarization.ApiExceptionase:print("Exception when calling DefaultApi->get_result_v1_result_result_id:%s\n"%e)# # Get response, http status code and response headers# try:#     # GET request that returns the full headline and summary results from the initial POST requests#     api_response, http_status_code, response_headers = api_instance.get_result_v1_result_result_id_with_http_info(result_id)#     pprint(api_response)#     pprint(http_status_code)#     pprint(response_headers)# except fds.sdk.AITextSummarization.ApiException as e:#     print("Exception when calling DefaultApi->get_result_v1_result_result_id: %s\n" % e)# # Get response asynchronous# try:#     # GET request that returns the full headline and summary results from the initial POST requests#     async_result = api_instance.get_result_v1_result_result_id_async(result_id)#     api_response = async_result.get()#     pprint(api_response)# except fds.sdk.AITextSummarization.ApiException as e:#     print("Exception when calling DefaultApi->get_result_v1_result_result_id: %s\n" % e)# # Get response, http status code and response headers asynchronous# try:#     # GET request that returns the full headline and summary results from the initial POST requests#     async_result = api_instance.get_result_v1_result_result_id_with_http_info_async(result_id)#     api_response, http_status_code, response_headers = async_result.get()#     pprint(api_response)#     pprint(http_status_code)#     pprint(response_headers)# except fds.sdk.AITextSummarization.ApiException as e:#     print("Exception when calling DefaultApi->get_result_v1_result_result_id: %s\n" % e)Using PandasTo convert an API response to a Pandas DataFrame, it is necessary to transform it first to a dictionary.importpandasaspdresponse_dict=api_response.to_dict()['data']simple_json_response=pd.DataFrame(response_dict)nested_json_response=pd.json_normalize(response_dict)DebuggingThe SDK uses the standard libraryloggingmodule.SettingdebugtoTrueon an instance of theConfigurationclass sets the log-level of related packages toDEBUGand enables additional logging in PythonsHTTP Client.Note: This prints out sensitive information (e.g. the full request and response). Use with care.importloggingimportfds.sdk.AITextSummarizationlogging.basicConfig(level=logging.DEBUG)configuration=fds.sdk.AITextSummarization.Configuration(...)configuration.debug=TrueConfigure a ProxyYou 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).importfds.sdk.AITextSummarizationconfiguration=fds.sdk.AITextSummarization.Configuration(# ...proxy="http://secret:password@localhost:5050",proxy_headers={"Custom-Proxy-Header":"Custom-Proxy-Header-Value"})Custom SSL CertificateTLS/SSL certificate verification can be configured with the following Configuration parameters:ssl_ca_cert: a path to the certificate to use for verification inPEMformat.verify_ssl: setting this toFalsedisables the verification of certificates.
Disabling the verification is not recommended, but it might be useful during
local development or testing.importfds.sdk.AITextSummarizationconfiguration=fds.sdk.AITextSummarization.Configuration(# ...ssl_ca_cert='/path/to/ca.pem')Documentation for API EndpointsAll URIs are relative tohttp://api.factset.com/cognitive/summarization/v1ClassMethodHTTP requestDescriptionDefaultApiget_result_v1_result_result_idGET/result/{result_id}GET request that returns the full headline and summary results from the initial POST requestsDefaultApipost_headline_and_summary_v1_headline_and_summaryPOST/headline-and-summaryPOST request to create a 2-3 sentence summary from input textDefaultApipost_headline_v1_headlinePOST/headlinePOST request to create a headline from input textDefaultApipost_summary_v1_summaryPOST/summaryPOST request to create a headline and summary from input textDocumentation For ModelsBadRequestResponseInternalServerErrorResponseRequestSuccessResponseDocumentation For AuthorizationFactSetApiKeyType: HTTP basic authenticationFactSetOAuth2Type: OAuthFlow: applicationAuthorization URL:Scopes: N/ANotes for Large OpenAPI documentsIf the OpenAPI document is large, imports in fds.sdk.AITextSummarization.apis and fds.sdk.AITextSummarization.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.AITextSummarization.api.default_api import DefaultApifrom fds.sdk.AITextSummarization.model.pet import PetSolution 2:
Before importing the package, adjust the maximum recursion limit as shown below:import sys
sys.setrecursionlimit(1500)
import fds.sdk.AITextSummarization
from fds.sdk.AITextSummarization.apis import *
from fds.sdk.AITextSummarization.models import *ContributingPlease refer to thecontributing guide.CopyrightCopyright 2022 FactSet Research Systems IncLicensed 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 athttp://www.apache.org/licenses/LICENSE-2.0Unless 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.