fds.sdk.NaturalLanguageProcessing 0.24.0

Natural Language Processing client library for Python

Natural Language Processing client library for Python

APIs that leverage Natural Language Processing to help extract meaningful data from unstructured text

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

• API version: 1.4.0
• SDK version: 0.24.0
• 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.NaturalLanguageProcessing==0.24.0

pip

pip install fds.sdk.utils fds.sdk.NaturalLanguageProcessing==0.24.0

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.NaturalLanguageProcessing
from fds.sdk.NaturalLanguageProcessing.api import ai_themes_api
from fds.sdk.NaturalLanguageProcessing.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.NaturalLanguageProcessing.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.NaturalLanguageProcessing.Configuration(
#     username='USERNAME-SERIAL',
#     password='API-KEY'
# )

# Enter a context with an instance of the API client
with fds.sdk.NaturalLanguageProcessing.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = ai_themes_api.AIThemesApi(api_client)
    themes_parameters_root = ThemesParametersRoot(
        data=ThemesParameters(
            include_sentiments=False,
            text="Studio Entertainment: At Studio Entertainment, operating income decreased in the quarter due to lower theatrical distribution and home entertainment results. Worldwide theatrical results continued to be adversely impacted by COVID-19, as theaters were closed in many key markets both domestically and internationally. With no significant worldwide theatrical releases in the quarter, we faced a difficult comparison against the strong performance of The Lion King and Toy Story 4 in the prior-year quarter. Operating Results: On our last earnings call, we said that we expected Q4 operating results of our DTC businesses to improve by approximately $100mm relative to the prior-year quarter. Our results came in better than that guidance, with operating income at our DTC businesses improving by approximately $300mm vs. the prior year due to better-than-expected performance across all three of our streaming services. I will note that we do not plan to further update any of our subscriber numbers until our Investor Day on December 10 At our International Channels, lower results were due to lower affiliate and advertising revenues, partially offset by a decrease in cost.",
        ),
        meta={},
    ) # ThemesParametersRoot | 

    try:
        # Endpoint to begin theme extraction job
        # example passing only required values which don't have defaults set
        api_response = api_instance.themes_extract_themes(themes_parameters_root)

        pprint(api_response)
    except fds.sdk.NaturalLanguageProcessing.ApiException as e:
        print("Exception when calling AIThemesApi->themes_extract_themes: %s\n" % e)

    # # Get response, http status code and response headers
    # try:
    #     # Endpoint to begin theme extraction job
    #     api_response, http_status_code, response_headers = api_instance.themes_extract_themes_with_http_info(themes_parameters_root)


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

    # # Get response asynchronous
    # try:
    #     # Endpoint to begin theme extraction job
    #     async_result = api_instance.themes_extract_themes_async(themes_parameters_root)
    #     api_response = async_result.get()


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

    # # Get response, http status code and response headers asynchronous
    # try:
    #     # Endpoint to begin theme extraction job
    #     async_result = api_instance.themes_extract_themes_with_http_info_async(themes_parameters_root)
    #     api_response, http_status_code, response_headers = async_result.get()


    #     pprint(api_response)
    #     pprint(http_status_code)
    #     pprint(response_headers)
    # except fds.sdk.NaturalLanguageProcessing.ApiException as e:
    #     print("Exception when calling AIThemesApi->themes_extract_themes: %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.NaturalLanguageProcessing

logging.basicConfig(level=logging.DEBUG)

configuration = fds.sdk.NaturalLanguageProcessing.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.NaturalLanguageProcessing

configuration = fds.sdk.NaturalLanguageProcessing.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.NaturalLanguageProcessing

configuration = fds.sdk.NaturalLanguageProcessing.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.NaturalLanguageProcessing

configuration = fds.sdk.NaturalLanguageProcessing.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/cognitive/nlp/v1

Class	Method	HTTP request	Description
AIThemesApi	themes_extract_themes	POST /themes	Endpoint to begin theme extraction job
AIThemesApi	themes_get_status	GET /themes/{id}/status	Endpoint to get the completion status of a themes job
AIThemesApi	themes_get_themes	GET /themes/{id}	Endpoint to get a theme (and sentiments if requested) job result
NamedEntityRecognitionApi	ner_entities	POST /ner/entities	Endpoint to detect entities from text

Documentation For Models

• ErrorSource
• HTTPError
• HTTPErrorRoot
• NEREntity
• NEREntityList
• NERInputDataSchema
• NERInputSchema
• NEROrganization
• NERResponseSchema
• Task
• TaskRoot
• ThemeSentiment
• ThemeSentimentsRoot
• ThemesParameters
• ThemesParametersRoot

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