FactSet Search Answers client library for Python

Project description

FactSet Search Answers client library for Python

The FactSet Search Answers API provides answers to search queries, reflecting the data shown within FactSet Search Answers, and allowing you to easily add financial data to your widgets, lookups, bots, and assistants. The API understands a fixed amount of search terms and returns structured data from FactSet’s many data sources. Possible answers include Price of a Company, Top 10 Year-to-Date Gainers, Revenue per Passenger Mile, and many more.

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

API version: 1.0.0
Package version: 1.0.3
Build package: org.openapitools.codegen.languages.PythonClientCodegen

Requirements

Python >= 3.7

Installation

Poetry

poetry add fds.sdk.utils fds.sdk.FactSetSearchAnswers

pip

pip install fds.sdk.utils fds.sdk.FactSetSearchAnswers

Usage

Generate authentication credentials.
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.
Install dependencies.
Run the following:

from fds.sdk.utils.authentication import ConfidentialClient

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

# Enter a context with an instance of the API client
with fds.sdk.FactSetSearchAnswers.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = answers_api.AnswersApi(api_client)
    query = "query_example" # str | Query for desired answer (e.g., \"fds price\")
    include_thumbnail = False # bool | Includes thumbnail of Adaptive Card in response (optional) if omitted the server will use the default value of False
    disable_no_answer_responses = True # bool | Disables no-result answer responses (no-results and answer without data) (optional) if omitted the server will use the default value of True

    try:
        # Fetch FactSet answer in Adaptive Card format
        api_response = api_instance.search_for_adaptive_card_answer(query, include_thumbnail=include_thumbnail, disable_no_answer_responses=disable_no_answer_responses)
        pprint(api_response)
    except fds.sdk.FactSetSearchAnswers.ApiException as e:
        print("Exception when calling AnswersApi->search_for_adaptive_card_answer: %s\n" % e)

    # Get response, http status code and response headers
    # try:
    #     # Fetch FactSet answer in Adaptive Card format
    #     api_response, http_status_code, response_headers = api_instance.search_for_adaptive_card_answer_with_http_info(query, include_thumbnail=include_thumbnail, disable_no_answer_responses=disable_no_answer_responses)
    #     pprint(api_response)
    #     pprint(http_status_code)
    #     pprint(response_headers)
    # except fds.sdk.FactSetSearchAnswers.ApiException as e:
    #     print("Exception when calling AnswersApi->search_for_adaptive_card_answer: %s\n" % e)

    # Get response asynchronous
    # try:
    #     # Fetch FactSet answer in Adaptive Card format
    #     async_result = api_instance.search_for_adaptive_card_answer_async(query, include_thumbnail=include_thumbnail, disable_no_answer_responses=disable_no_answer_responses)
    #     api_response = async_result.get()
    #     pprint(api_response)
    # except fds.sdk.FactSetSearchAnswers.ApiException as e:
    #     print("Exception when calling AnswersApi->search_for_adaptive_card_answer: %s\n" % e)

    # Get response, http status code and response headers asynchronous
    # try:
    #     # Fetch FactSet answer in Adaptive Card format
    #     async_result = api_instance.search_for_adaptive_card_answer_with_http_info_async(query, include_thumbnail=include_thumbnail, disable_no_answer_responses=disable_no_answer_responses)
    #     api_response, http_status_code, response_headers = async_result.get()
    #     pprint(api_response)
    #     pprint(http_status_code)
    #     pprint(response_headers)
    # except fds.sdk.FactSetSearchAnswers.ApiException as e:
    #     print("Exception when calling AnswersApi->search_for_adaptive_card_answer: %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.FactSetSearchAnswers

logging.basicConfig(level=logging.DEBUG)

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

Documentation for API Endpoints

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

Class	Method	HTTP request	Description
AnswersApi	search_for_adaptive_card_answer	GET /search/answers/v1/adaptive-card	Fetch FactSet answer in Adaptive Card format
AnswersApi	search_for_data_answer	GET /search/answers/v1/data	Fetch FactSet answer in data format

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.FactSetSearchAnswers.apis and fds.sdk.FactSetSearchAnswers.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.FactSetSearchAnswers.api.default_api import DefaultApi
from fds.sdk.FactSetSearchAnswers.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.FactSetSearchAnswers
from fds.sdk.FactSetSearchAnswers.apis import *
from fds.sdk.FactSetSearchAnswers.models import *

Contributing

Please refer to the contributing guide.

Copyright

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.

Project details

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1.1.5

Nov 1, 2024

1.1.4

Jun 26, 2024

1.1.3

Jun 26, 2024

1.1.2

May 2, 2024

1.1.1

Apr 8, 2024

1.1.0

Dec 15, 2023

1.0.7

Oct 25, 2023

1.0.6

Aug 30, 2023

1.0.5

Jun 6, 2023

1.0.4

May 17, 2023

This version

1.0.3

May 12, 2023

1.0.2

May 11, 2023

1.0.1

Feb 24, 2023

1.0.0

Dec 2, 2022

0.21.4

Nov 14, 2022

0.21.3

Oct 24, 2022

0.21.2

Aug 31, 2022

0.21.0

Jul 21, 2022

0.20.0

May 24, 2022

0.9.1

Feb 14, 2022

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