fds.sdk.QuantitativeResearchEnvironment 0.21.2

Quantitative Research Environment client library for Python

Quantitative Research Environment client library for Python

TBD

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

• API version: 0.0.0
• Package version: 0.21.2
• Build package: org.openapitools.codegen.languages.PythonClientCodegen

Requirements

• Python >= 3.7

Installation

Poetry

poetry add fds.sdk.utils fds.sdk.QuantitativeResearchEnvironment

pip

pip install fds.sdk.utils fds.sdk.QuantitativeResearchEnvironment

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

# Enter a context with an instance of the API client
with fds.sdk.QuantitativeResearchEnvironment.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = calculations_api.CalculationsApi(api_client)
    id = "id_example" # str | From url, provided by location header or response body in the calculation start endpoint

    try:
        # Get calculation status by id
        api_response = api_instance.analytics_quant_qre_v1_calculations_id_get(id)
        pprint(api_response)
    except fds.sdk.QuantitativeResearchEnvironment.ApiException as e:
        print("Exception when calling CalculationsApi->analytics_quant_qre_v1_calculations_id_get: %s\n" % e)

    # Get response, http status code and response headers
    # try:
    #     # Get calculation status by id
    #     api_response, http_status_code, response_headers = api_instance.analytics_quant_qre_v1_calculations_id_get_with_http_info(id)
    #     pprint(api_response)
    #     pprint(http_status_code)
    #     pprint(response_headers)
    # except fds.sdk.QuantitativeResearchEnvironment.ApiException as e:
    #     print("Exception when calling CalculationsApi->analytics_quant_qre_v1_calculations_id_get: %s\n" % e)

    # Get response asynchronous
    # try:
    #     # Get calculation status by id
    #     async_result = api_instance.analytics_quant_qre_v1_calculations_id_get_async(id)
    #     api_response = async_result.get()
    #     pprint(api_response)
    # except fds.sdk.QuantitativeResearchEnvironment.ApiException as e:
    #     print("Exception when calling CalculationsApi->analytics_quant_qre_v1_calculations_id_get: %s\n" % e)

    # Get response, http status code and response headers asynchronous
    # try:
    #     # Get calculation status by id
    #     async_result = api_instance.analytics_quant_qre_v1_calculations_id_get_with_http_info_async(id)
    #     api_response, http_status_code, response_headers = async_result.get()
    #     pprint(api_response)
    #     pprint(http_status_code)
    #     pprint(response_headers)
    # except fds.sdk.QuantitativeResearchEnvironment.ApiException as e:
    #     print("Exception when calling CalculationsApi->analytics_quant_qre_v1_calculations_id_get: %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.QuantitativeResearchEnvironment

logging.basicConfig(level=logging.DEBUG)

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

Documentation for API Endpoints

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

Class	Method	HTTP request	Description
CalculationsApi	analytics_quant_qre_v1_calculations_id_get	GET /analytics/quant/qre/v1/calculations/{id}	Get calculation status by id
CalculationsApi	analytics_quant_qre_v1_calculations_id_log_get	GET /analytics/quant/qre/v1/calculations/{id}/log	Get calculation log for a specific calculation
CalculationsApi	analytics_quant_qre_v1_calculations_id_output_get	GET /analytics/quant/qre/v1/calculations/{id}/output	Get calculation output for a specific calculation
CalculationsApi	analytics_quant_qre_v1_calculations_post	POST /analytics/quant/qre/v1/calculations	Starts a new script calculation
FilesApi	analytics_quant_qre_v1_files_server_file_post	POST /analytics/quant/qre/v1/files/{server}/{file}	Starts a file upload
FilesApi	analytics_quant_qre_v1_files_uploads_id_get	GET /analytics/quant/qre/v1/files/uploads/{id}	Get upload status by id

Documentation For Models

• Calculation
• CalculationStatus
• FileUploadStatus

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