[](https://www.factset.com)
# Quantitative Research Environment client library for Python
[](https://pypi.org/project/fds.sdk.QuantitativeResearchEnvironment/)
[](https://www.apache.org/licenses/LICENSE-2.0)
TBD
This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
- API version: 0.0.0
- Package version: 0.21.6
- Build package: org.openapitools.codegen.languages.PythonClientCodegen
## Requirements
* Python >= 3.7
## Installation
### Poetry
```shell
poetry add fds.sdk.utils fds.sdk.QuantitativeResearchEnvironment
```
### pip
```shell
pip install fds.sdk.utils fds.sdk.QuantitativeResearchEnvironment
```
## Usage
1. [Generate authentication credentials](../../../../README.md#authentication).
2. Setup Python environment.
1. Install and activate python 3.7+. If you're using [pyenv](https://github.com/pyenv/pyenv):
```sh
pyenv install 3.9.7
pyenv shell 3.9.7
```
2. (optional) [Install poetry](https://python-poetry.org/docs/#installation).
3. [Install dependencies](#installation).
4. Run the following:
```python
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)
# NOTE: The parameter variable defined below is just an example and may potentially contain non valid values. So please replace this with valid values.
id = "id_example" # str | From url, provided by location header or response body in the calculation start endpoint
try:
# Get calculation status by id
# example passing only required values which don't have defaults set
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.
```python
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`](https://docs.python.org/3/library/logging.html#module-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](https://docs.python.org/3/library/http.client.html).
**Note**: This prints out sensitive information (e.g. the full request and response). Use with care.
```python
import logging
import fds.sdk.QuantitativeResearchEnvironment
logging.basicConfig(level=logging.DEBUG)
configuration = fds.sdk.QuantitativeResearchEnvironment.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`).
```python
import fds.sdk.QuantitativeResearchEnvironment
configuration = fds.sdk.QuantitativeResearchEnvironment.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.
```python
import fds.sdk.QuantitativeResearchEnvironment
configuration = fds.sdk.QuantitativeResearchEnvironment.Configuration(
# ...
ssl_ca_cert='/path/to/ca.pem'
)
```
## 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**](https://github.com/FactSet/enterprise-sdk/tree/main/code/python/QuantitativeResearchEnvironment/v1/docs/CalculationsApi.md#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**](https://github.com/FactSet/enterprise-sdk/tree/main/code/python/QuantitativeResearchEnvironment/v1/docs/CalculationsApi.md#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**](https://github.com/FactSet/enterprise-sdk/tree/main/code/python/QuantitativeResearchEnvironment/v1/docs/CalculationsApi.md#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**](https://github.com/FactSet/enterprise-sdk/tree/main/code/python/QuantitativeResearchEnvironment/v1/docs/CalculationsApi.md#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**](https://github.com/FactSet/enterprise-sdk/tree/main/code/python/QuantitativeResearchEnvironment/v1/docs/FilesApi.md#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**](https://github.com/FactSet/enterprise-sdk/tree/main/code/python/QuantitativeResearchEnvironment/v1/docs/FilesApi.md#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](https://github.com/FactSet/enterprise-sdk/tree/main/code/python/QuantitativeResearchEnvironment/v1/docs/Calculation.md)
- [CalculationStatus](https://github.com/FactSet/enterprise-sdk/tree/main/code/python/QuantitativeResearchEnvironment/v1/docs/CalculationStatus.md)
- [FileUploadStatus](https://github.com/FactSet/enterprise-sdk/tree/main/code/python/QuantitativeResearchEnvironment/v1/docs/FileUploadStatus.md)
## 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](../../../../CONTRIBUTING.md).
## 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.
Raw data
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"keywords": "FactSet,API,SDK",
"author": "FactSet Research Systems",
"author_email": "",
"download_url": "",
"platform": null,
"description": "[](https://www.factset.com)\n\n# Quantitative Research Environment client library for Python\n\n[](https://pypi.org/project/fds.sdk.QuantitativeResearchEnvironment/)\n[](https://www.apache.org/licenses/LICENSE-2.0)\n\nTBD\n\nThis Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:\n\n- API version: 0.0.0\n- Package version: 0.21.6\n- Build package: org.openapitools.codegen.languages.PythonClientCodegen\n\n## Requirements\n\n* Python >= 3.7\n\n## Installation\n\n### Poetry\n\n```shell\npoetry add fds.sdk.utils fds.sdk.QuantitativeResearchEnvironment\n```\n\n### pip\n\n```shell\npip install fds.sdk.utils fds.sdk.QuantitativeResearchEnvironment\n```\n\n## Usage\n\n1. [Generate authentication credentials](../../../../README.md#authentication).\n2. Setup Python environment.\n 1. Install and activate python 3.7+. If you're using [pyenv](https://github.com/pyenv/pyenv):\n\n ```sh\n pyenv install 3.9.7\n pyenv shell 3.9.7\n ```\n\n 2. (optional) [Install poetry](https://python-poetry.org/docs/#installation).\n3. [Install dependencies](#installation).\n4. Run the following:\n\n```python\nfrom fds.sdk.utils.authentication import ConfidentialClient\n\nimport fds.sdk.QuantitativeResearchEnvironment\nfrom fds.sdk.QuantitativeResearchEnvironment.api import calculations_api\nfrom fds.sdk.QuantitativeResearchEnvironment.models import *\nfrom dateutil.parser import parse as dateutil_parser\nfrom pprint import pprint\n\n# See configuration.py for a list of all supported configuration parameters.\n\n# Examples for each supported authentication method are below,\n# choose one that satisfies your use case.\n\n# (Preferred) OAuth 2.0: FactSetOAuth2\n# See https://github.com/FactSet/enterprise-sdk#oauth-20\n# for information on how to create the app-config.json file\n# See https://github.com/FactSet/enterprise-sdk-utils-python#authentication\n# for more information on using the ConfidentialClient class\nconfiguration = fds.sdk.QuantitativeResearchEnvironment.Configuration(\n fds_oauth_client=ConfidentialClient('/path/to/app-config.json')\n)\n\n# Basic authentication: FactSetApiKey\n# See https://github.com/FactSet/enterprise-sdk#api-key\n# for information how to create an API key\n# configuration = fds.sdk.QuantitativeResearchEnvironment.Configuration(\n# username='USERNAME-SERIAL',\n# password='API-KEY'\n# )\n\n# Enter a context with an instance of the API client\nwith fds.sdk.QuantitativeResearchEnvironment.ApiClient(configuration) as api_client:\n # Create an instance of the API class\n api_instance = calculations_api.CalculationsApi(api_client)\n # NOTE: The parameter variable defined below is just an example and may potentially contain non valid values. So please replace this with valid values.\n id = \"id_example\" # str | From url, provided by location header or response body in the calculation start endpoint\n\n try:\n # Get calculation status by id\n # example passing only required values which don't have defaults set\n api_response = api_instance.analytics_quant_qre_v1_calculations_id_get(id)\n\n pprint(api_response)\n except fds.sdk.QuantitativeResearchEnvironment.ApiException as e:\n print(\"Exception when calling CalculationsApi->analytics_quant_qre_v1_calculations_id_get: %s\\n\" % e)\n\n # # Get response, http status code and response headers\n # try:\n # # Get calculation status by id\n # api_response, http_status_code, response_headers = api_instance.analytics_quant_qre_v1_calculations_id_get_with_http_info(id)\n\n\n # pprint(api_response)\n # pprint(http_status_code)\n # pprint(response_headers)\n # except fds.sdk.QuantitativeResearchEnvironment.ApiException as e:\n # print(\"Exception when calling CalculationsApi->analytics_quant_qre_v1_calculations_id_get: %s\\n\" % e)\n\n # # Get response asynchronous\n # try:\n # # Get calculation status by id\n # async_result = api_instance.analytics_quant_qre_v1_calculations_id_get_async(id)\n # api_response = async_result.get()\n\n\n # pprint(api_response)\n # except fds.sdk.QuantitativeResearchEnvironment.ApiException as e:\n # print(\"Exception when calling CalculationsApi->analytics_quant_qre_v1_calculations_id_get: %s\\n\" % e)\n\n # # Get response, http status code and response headers asynchronous\n # try:\n # # Get calculation status by id\n # async_result = api_instance.analytics_quant_qre_v1_calculations_id_get_with_http_info_async(id)\n # api_response, http_status_code, response_headers = async_result.get()\n\n\n # pprint(api_response)\n # pprint(http_status_code)\n # pprint(response_headers)\n # except fds.sdk.QuantitativeResearchEnvironment.ApiException as e:\n # print(\"Exception when calling CalculationsApi->analytics_quant_qre_v1_calculations_id_get: %s\\n\" % e)\n\n```\n\n### Using Pandas\n\nTo convert an API response to a Pandas DataFrame, it is necessary to transform it first to a dictionary.\n```python\nimport pandas as pd\n\nresponse_dict = api_response.to_dict()['data']\n\nsimple_json_response = pd.DataFrame(response_dict)\nnested_json_response = pd.json_normalize(response_dict)\n```\n\n### Debugging\n\nThe SDK uses the standard library [`logging`](https://docs.python.org/3/library/logging.html#module-logging) module.\n\nSetting `debug` to `True` on an instance of the `Configuration` class sets the log-level of related packages to `DEBUG`\nand enables additional logging in Pythons [HTTP Client](https://docs.python.org/3/library/http.client.html).\n\n**Note**: This prints out sensitive information (e.g. the full request and response). Use with care.\n\n```python\nimport logging\nimport fds.sdk.QuantitativeResearchEnvironment\n\nlogging.basicConfig(level=logging.DEBUG)\n\nconfiguration = fds.sdk.QuantitativeResearchEnvironment.Configuration(...)\nconfiguration.debug = True\n```\n\n### Configure a Proxy\n\nYou can pass proxy settings to the Configuration class:\n\n* `proxy`: The URL of the proxy to use.\n* `proxy_headers`: a dictionary to pass additional headers to the proxy (e.g. `Proxy-Authorization`).\n\n```python\nimport fds.sdk.QuantitativeResearchEnvironment\n\nconfiguration = fds.sdk.QuantitativeResearchEnvironment.Configuration(\n # ...\n proxy=\"http://secret:password@localhost:5050\",\n proxy_headers={\n \"Custom-Proxy-Header\": \"Custom-Proxy-Header-Value\"\n }\n)\n```\n\n### Custom SSL Certificate\n\nTLS/SSL certificate verification can be configured with the following Configuration parameters:\n\n* `ssl_ca_cert`: a path to the certificate to use for verification in `PEM` format.\n* `verify_ssl`: setting this to `False` disables the verification of certificates.\n Disabling the verification is not recommended, but it might be useful during\n local development or testing.\n\n```python\nimport fds.sdk.QuantitativeResearchEnvironment\n\nconfiguration = fds.sdk.QuantitativeResearchEnvironment.Configuration(\n # ...\n ssl_ca_cert='/path/to/ca.pem'\n)\n```\n\n\n## Documentation for API Endpoints\n\nAll URIs are relative to *https://api.factset.com*\n\nClass | Method | HTTP request | Description\n------------ | ------------- | ------------- | -------------\n*CalculationsApi* | [**analytics_quant_qre_v1_calculations_id_get**](https://github.com/FactSet/enterprise-sdk/tree/main/code/python/QuantitativeResearchEnvironment/v1/docs/CalculationsApi.md#analytics_quant_qre_v1_calculations_id_get) | **GET** /analytics/quant/qre/v1/calculations/{id} | Get calculation status by id\n*CalculationsApi* | [**analytics_quant_qre_v1_calculations_id_log_get**](https://github.com/FactSet/enterprise-sdk/tree/main/code/python/QuantitativeResearchEnvironment/v1/docs/CalculationsApi.md#analytics_quant_qre_v1_calculations_id_log_get) | **GET** /analytics/quant/qre/v1/calculations/{id}/log | Get calculation log for a specific calculation\n*CalculationsApi* | [**analytics_quant_qre_v1_calculations_id_output_get**](https://github.com/FactSet/enterprise-sdk/tree/main/code/python/QuantitativeResearchEnvironment/v1/docs/CalculationsApi.md#analytics_quant_qre_v1_calculations_id_output_get) | **GET** /analytics/quant/qre/v1/calculations/{id}/output | Get calculation output for a specific calculation\n*CalculationsApi* | [**analytics_quant_qre_v1_calculations_post**](https://github.com/FactSet/enterprise-sdk/tree/main/code/python/QuantitativeResearchEnvironment/v1/docs/CalculationsApi.md#analytics_quant_qre_v1_calculations_post) | **POST** /analytics/quant/qre/v1/calculations | Starts a new script calculation\n*FilesApi* | [**analytics_quant_qre_v1_files_server_file_post**](https://github.com/FactSet/enterprise-sdk/tree/main/code/python/QuantitativeResearchEnvironment/v1/docs/FilesApi.md#analytics_quant_qre_v1_files_server_file_post) | **POST** /analytics/quant/qre/v1/files/{server}/{file} | Starts a file upload\n*FilesApi* | [**analytics_quant_qre_v1_files_uploads_id_get**](https://github.com/FactSet/enterprise-sdk/tree/main/code/python/QuantitativeResearchEnvironment/v1/docs/FilesApi.md#analytics_quant_qre_v1_files_uploads_id_get) | **GET** /analytics/quant/qre/v1/files/uploads/{id} | Get upload status by id\n\n\n## Documentation For Models\n\n - [Calculation](https://github.com/FactSet/enterprise-sdk/tree/main/code/python/QuantitativeResearchEnvironment/v1/docs/Calculation.md)\n - [CalculationStatus](https://github.com/FactSet/enterprise-sdk/tree/main/code/python/QuantitativeResearchEnvironment/v1/docs/CalculationStatus.md)\n - [FileUploadStatus](https://github.com/FactSet/enterprise-sdk/tree/main/code/python/QuantitativeResearchEnvironment/v1/docs/FileUploadStatus.md)\n\n\n## Documentation For Authorization\n\n\n## FactSetApiKey\n\n- **Type**: HTTP basic authentication\n\n\n## FactSetOAuth2\n\n- **Type**: OAuth\n- **Flow**: application\n- **Authorization URL**: \n- **Scopes**: N/A\n\n\n## Notes for Large OpenAPI documents\nIf the OpenAPI document is large, imports in fds.sdk.QuantitativeResearchEnvironment.apis and fds.sdk.QuantitativeResearchEnvironment.models may fail with a\nRecursionError indicating the maximum recursion limit has been exceeded. In that case, there are a couple of solutions:\n\nSolution 1:\nUse specific imports for apis and models like:\n- `from fds.sdk.QuantitativeResearchEnvironment.api.default_api import DefaultApi`\n- `from fds.sdk.QuantitativeResearchEnvironment.model.pet import Pet`\n\nSolution 2:\nBefore importing the package, adjust the maximum recursion limit as shown below:\n```\nimport sys\nsys.setrecursionlimit(1500)\nimport fds.sdk.QuantitativeResearchEnvironment\nfrom fds.sdk.QuantitativeResearchEnvironment.apis import *\nfrom fds.sdk.QuantitativeResearchEnvironment.models import *\n```\n\n## Contributing\n\nPlease refer to the [contributing guide](../../../../CONTRIBUTING.md).\n\n## Copyright\n\nCopyright 2022 FactSet Research Systems Inc\n\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at\n\n http://www.apache.org/licenses/LICENSE-2.0\n\nUnless required by applicable law or agreed to in writing, software\ndistributed under the License is distributed on an \"AS IS\" BASIS,\nWITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\nSee the License for the specific language governing permissions and\nlimitations under the License.\n\n\n\n",
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