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Natural Language Processing client library for Python

Project description

FactSet

Natural Language Processing client library for Python

PyPi Apache-2 license

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: 1.0.0
  • Package version: 0.21.1
  • Build package: org.openapitools.codegen.languages.PythonClientCodegen

Requirements

  • Python >= 3.7

Installation

Poetry

poetry add fds.sdk.utils fds.sdk.NaturalLanguageProcessing

pip

pip install fds.sdk.utils fds.sdk.NaturalLanguageProcessing

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.NaturalLanguageProcessing
from fds.sdk.NaturalLanguageProcessing.api import 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
# 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 = themes_api.ThemesApi(api_client)
    theme_parameters_root = ThemeParametersRoot(
        data=ThemeParameters(
            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={},
    ) # ThemeParametersRoot | 

    try:
        # POST request to extract themes from text
        api_response = api_instance.cognitive_nlp_v1_themes_post(theme_parameters_root)
        pprint(api_response)
    except fds.sdk.NaturalLanguageProcessing.ApiException as e:
        print("Exception when calling ThemesApi->cognitive_nlp_v1_themes_post: %s\n" % e)

    # Get response, http status code and response headers
    # try:
    #     # POST request to extract themes from text
    #     api_response, http_status_code, response_headers = api_instance.cognitive_nlp_v1_themes_post_with_http_info(theme_parameters_root)
    #     pprint(api_response)
    #     pprint(http_status_code)
    #     pprint(response_headers)
    # except fds.sdk.NaturalLanguageProcessing.ApiException as e:
    #     print("Exception when calling ThemesApi->cognitive_nlp_v1_themes_post: %s\n" % e)

    # Get response asynchronous
    # try:
    #     # POST request to extract themes from text
    #     async_result = api_instance.cognitive_nlp_v1_themes_post_async(theme_parameters_root)
    #     api_response = async_result.get()
    #     pprint(api_response)
    # except fds.sdk.NaturalLanguageProcessing.ApiException as e:
    #     print("Exception when calling ThemesApi->cognitive_nlp_v1_themes_post: %s\n" % e)

    # Get response, http status code and response headers asynchronous
    # try:
    #     # POST request to extract themes from text
    #     async_result = api_instance.cognitive_nlp_v1_themes_post_with_http_info_async(theme_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 ThemesApi->cognitive_nlp_v1_themes_post: %s\n" % e)

Documentation for API Endpoints

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

Class Method HTTP request Description
ThemesApi cognitive_nlp_v1_themes_post POST /cognitive/nlp/v1/themes POST request to extract themes from text

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.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 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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