Standard Datafeed client library for Python
Project description
Standard Datafeed client library for Python
The Standard DataFeed (SDF) Download API provides an alternative method for users to request and retrieve SDF packages (schemas & bundles). This service is not a direct replacement and does not have 100% feature parity with the Loader Application. This API provides an alternative for users who are unable to utilize the Loader application due to following reasons:
- Inability to install 3rd party executables due to Corporate Security policies
- Inability to utilize the Loader application due to limitations or restrictions with the environment used to consume Standard Datafeed
- Clients who are utilizing existing delivery method like FTP, who may want to use a more secured & modern solution
This API allows users to retrieve maximum of latest 30 days of data
Additional parameters are available to filter requests to get the exact files users are looking for.
QFL data is delivered through Content API & Bulk Data API (SDF API)
- Content API : Provides direct access to FactSet-hosted QFL data. Suitable for interactive, ad hoc QFL requests. Constraints on large extracts. Costs are based on consumption, i.e. more calls can result in more costs.
- Bulk Data API : Provides access to download locations of zip files for client download. Suitable for production processes within a client environment. Cost is based on the use case and fixed unless scope changes (same as other SDFs).
This Python package is automatically generated by the OpenAPI Generator project:
- API version: 1.2.0
- Package version: 0.21.11
- Build package: org.openapitools.codegen.languages.PythonClientCodegen
Requirements
- Python >= 3.7
Installation
Poetry
poetry add fds.sdk.utils fds.sdk.StandardDatafeed==0.21.11
pip
pip install fds.sdk.utils fds.sdk.StandardDatafeed==0.21.11
Usage
- Generate authentication credentials.
- Setup Python environment.
-
Install and activate python 3.7+. If you're using pyenv:
pyenv install 3.9.7 pyenv shell 3.9.7
-
(optional) Install poetry.
-
- Install dependencies.
- 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.StandardDatafeed
from fds.sdk.StandardDatafeed.api import sdf_and_qfl_content_library_api
from fds.sdk.StandardDatafeed.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.StandardDatafeed.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.StandardDatafeed.Configuration(
# username='USERNAME-SERIAL',
# password='API-KEY'
# )
# Enter a context with an instance of the API client
with fds.sdk.StandardDatafeed.ApiClient(configuration) as api_client:
# Create an instance of the API class
api_instance = sdf_and_qfl_content_library_api.SDFAndQFLContentLibraryApi(api_client)
schema = "schema_example" # str | schema name</p> </p> **Example: acta_v1, fgp_v1, yn_v1** QFL:- To query QFL data, please use value: **qfl_v1** (optional)
bundle = "bundle_example" # str | bundle name</p> If this parameter is not passed in the request, all the bundles a client is subscribed to are returned. QFL:- - For QFL its the factor group name - If this parameter is not passed in the request, all the the factor families & factor groups subscribed to by the user are returned. - Supports comma separated list of multiple factor groups (optional)
type = "full" # str | file type = Full or Delta</p> Full files are weekly files generated every weekend (Saturday). **The date range should include weekend dates if requesting for \"Full\" files** (optional)
start_date = "startDate_example" # str | The earliest date of the feed file the API should fetch for based on the fileTimestamp.</p> - If the schema parameter is specified in the request, date range can be greater than 10 days maximum upto latest 30 days. - If startDate and endDate parameters are not specified in the request, this endpoint returns past 10 days data by default. - startDate can be absolute- YYYY-MM-DD or relative:- -1 for yesterday (optional)
end_date = "endDate_example" # str | The latest date of the feed file the API should fetch for based on the fileTimestamp If startDate and endDate parameters are not specified in the request, this endpoint returns past 10 days data by default. endDate can be in absolute- YYYY-MM-DD or relative date:- 0 for today (optional)
pagination_limit = 20 # int | Specifies the number of results to return per page. Default is 20 & Maximum is 500 results per page (optional) if omitted the server will use the default value of 20
pagination_offset = 0 # int | Specifies the starting point for pagination. This parameter is used to identify the beginning of next set of results (optional) if omitted the server will use the default value of 0
sort = "startDate" # str | Enables to get the data in ascending or descending order based on startTime. Results are in reverse chronological order if this parameter is not used (optional) if omitted the server will use the default value of "startDate"
try:
# example passing only required values which don't have defaults set
# and optional values
api_response = api_instance.get_v1_list_files(schema=schema, bundle=bundle, type=type, start_date=start_date, end_date=end_date, pagination_limit=pagination_limit, pagination_offset=pagination_offset, sort=sort)
pprint(api_response)
except fds.sdk.StandardDatafeed.ApiException as e:
print("Exception when calling SDFAndQFLContentLibraryApi->get_v1_list_files: %s\n" % e)
# # Get response, http status code and response headers
# try:
# api_response, http_status_code, response_headers = api_instance.get_v1_list_files_with_http_info(schema=schema, bundle=bundle, type=type, start_date=start_date, end_date=end_date, pagination_limit=pagination_limit, pagination_offset=pagination_offset, sort=sort)
# pprint(api_response)
# pprint(http_status_code)
# pprint(response_headers)
# except fds.sdk.StandardDatafeed.ApiException as e:
# print("Exception when calling SDFAndQFLContentLibraryApi->get_v1_list_files: %s\n" % e)
# # Get response asynchronous
# try:
# async_result = api_instance.get_v1_list_files_async(schema=schema, bundle=bundle, type=type, start_date=start_date, end_date=end_date, pagination_limit=pagination_limit, pagination_offset=pagination_offset, sort=sort)
# api_response = async_result.get()
# pprint(api_response)
# except fds.sdk.StandardDatafeed.ApiException as e:
# print("Exception when calling SDFAndQFLContentLibraryApi->get_v1_list_files: %s\n" % e)
# # Get response, http status code and response headers asynchronous
# try:
# async_result = api_instance.get_v1_list_files_with_http_info_async(schema=schema, bundle=bundle, type=type, start_date=start_date, end_date=end_date, pagination_limit=pagination_limit, pagination_offset=pagination_offset, sort=sort)
# api_response, http_status_code, response_headers = async_result.get()
# pprint(api_response)
# pprint(http_status_code)
# pprint(response_headers)
# except fds.sdk.StandardDatafeed.ApiException as e:
# print("Exception when calling SDFAndQFLContentLibraryApi->get_v1_list_files: %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.StandardDatafeed
logging.basicConfig(level=logging.DEBUG)
configuration = fds.sdk.StandardDatafeed.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.StandardDatafeed
configuration = fds.sdk.StandardDatafeed.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 inPEM
format.verify_ssl
: setting this toFalse
disables the verification of certificates. Disabling the verification is not recommended, but it might be useful during local development or testing.
import fds.sdk.StandardDatafeed
configuration = fds.sdk.StandardDatafeed.Configuration(
# ...
ssl_ca_cert='/path/to/ca.pem'
)
Documentation for API Endpoints
All URIs are relative to https://api.factset.com/bulk-documents/sdf/v1
Class | Method | HTTP request | Description |
---|---|---|---|
SDFAndQFLContentLibraryApi | get_v1_list_files | GET /list-files | |
SchemaApi | get_v1_list_schemas | GET /list-schemas | schemas |
Documentation For Models
- Dataresponseitems
- DataresponseitemsRelatedBundles
- ListFiles200Response
- ListFiles200ResponseMeta
- ListFiles400Response
- ListSchema400Response
- ListSchemas
- Meta
- Pagination
- Partial
- SchemaDetails
- SchemaList
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.StandardDatafeed.apis and fds.sdk.StandardDatafeed.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.StandardDatafeed.api.default_api import DefaultApi
from fds.sdk.StandardDatafeed.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.StandardDatafeed
from fds.sdk.StandardDatafeed.apis import *
from fds.sdk.StandardDatafeed.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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