Skip to main content

Asset Cash Flow Projections client library for Python

Project description

FactSet

Asset Cash Flow Projections client library for Python

API Version PyPi Apache-2 license

Allow clients to upload scenario files through APIs.

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

  • API version: 0.3.0
  • SDK version: 0.11.0
  • Build package: org.openapitools.codegen.languages.PythonClientCodegen

For more information, please visit https://developer.factset.com/contact

Requirements

  • Python >= 3.7

Installation

Poetry

poetry add fds.sdk.utils fds.sdk.AssetCashFlowProjections==0.11.0

pip

pip install fds.sdk.utils fds.sdk.AssetCashFlowProjections==0.11.0

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:

[!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.AssetCashFlowProjections
from fds.sdk.AssetCashFlowProjections.api import batch_api
from fds.sdk.AssetCashFlowProjections.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.AssetCashFlowProjections.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.AssetCashFlowProjections.Configuration(
#     username='USERNAME-SERIAL',
#     password='API-KEY'
# )

# Enter a context with an instance of the API client
with fds.sdk.AssetCashFlowProjections.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = batch_api.BatchApi(api_client)
    create_batch_job = CreateBatchJob(
        data=CreateBatchJobRoot(
            document_name="document_name_example",
        ),
    ) # CreateBatchJob |  (optional)

    try:
        # Trigger batch job
        # example passing only required values which don't have defaults set
        # and optional values
        api_response = api_instance.post_batch(create_batch_job=create_batch_job)

        pprint(api_response)
    except fds.sdk.AssetCashFlowProjections.ApiException as e:
        print("Exception when calling BatchApi->post_batch: %s\n" % e)

    # # Get response, http status code and response headers
    # try:
    #     # Trigger batch job
    #     api_response, http_status_code, response_headers = api_instance.post_batch_with_http_info(create_batch_job=create_batch_job)


    #     pprint(api_response)
    #     pprint(http_status_code)
    #     pprint(response_headers)
    # except fds.sdk.AssetCashFlowProjections.ApiException as e:
    #     print("Exception when calling BatchApi->post_batch: %s\n" % e)

    # # Get response asynchronous
    # try:
    #     # Trigger batch job
    #     async_result = api_instance.post_batch_async(create_batch_job=create_batch_job)
    #     api_response = async_result.get()


    #     pprint(api_response)
    # except fds.sdk.AssetCashFlowProjections.ApiException as e:
    #     print("Exception when calling BatchApi->post_batch: %s\n" % e)

    # # Get response, http status code and response headers asynchronous
    # try:
    #     # Trigger batch job
    #     async_result = api_instance.post_batch_with_http_info_async(create_batch_job=create_batch_job)
    #     api_response, http_status_code, response_headers = async_result.get()


    #     pprint(api_response)
    #     pprint(http_status_code)
    #     pprint(response_headers)
    # except fds.sdk.AssetCashFlowProjections.ApiException as e:
    #     print("Exception when calling BatchApi->post_batch: %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.AssetCashFlowProjections

logging.basicConfig(level=logging.DEBUG)

configuration = fds.sdk.AssetCashFlowProjections.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.AssetCashFlowProjections

configuration = fds.sdk.AssetCashFlowProjections.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.
import fds.sdk.AssetCashFlowProjections

configuration = fds.sdk.AssetCashFlowProjections.Configuration(
    # ...
    ssl_ca_cert='/path/to/ca.pem'
)

Request Retries

In case the request retry behaviour should be customized, it is possible to pass a urllib3.Retry object to the retry property of the Configuration.

from urllib3 import Retry
import fds.sdk.AssetCashFlowProjections

configuration = fds.sdk.AssetCashFlowProjections.Configuration(
    # ...
)

configuration.retries = Retry(total=3, status_forcelist=[500, 502, 503, 504])

Documentation for API Endpoints

All URIs are relative to https://api.factset.com/analytics/asset-cash-flow-projections/v0

Class Method HTTP request Description
BatchApi post_batch POST /batch Trigger batch job
DocumentsApi get_document_details GET /documents/{documentPath} Retrieve a document
DocumentsApi get_documents GET /documents Gives all the ACFP documents in the given directory.
DocumentsApi post_document POST /documents Create new document based on existing document - Save as
DocumentsApi put_document PUT /documents/{documentPath} Update existing document - Save
ScenariosApi get_upload_status GET /scenarios/{uploadId}/status Get scenarios upload status
ScenariosApi upload_scenarios POST /scenarios Upload actuarial scenarios

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

Contributing

Please refer to the contributing guide.

Copyright

Copyright 2026 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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

fds_sdk_assetcashflowprojections-0.11.0.tar.gz (59.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

File details

Details for the file fds_sdk_assetcashflowprojections-0.11.0.tar.gz.

File metadata

File hashes

Hashes for fds_sdk_assetcashflowprojections-0.11.0.tar.gz
Algorithm Hash digest
SHA256 f816f0fb666b5ebc84e910fa3746b3c6e1e09f1accea75068fc4cb0386ad9975
MD5 67da23bae4dbe5c3e017aa398430c711
BLAKE2b-256 cf6f8ab83dbf1cd9d9d605067691dc9a12986fa9124c6ffbb5ede0b803ff2ef9

See more details on using hashes here.

File details

Details for the file fds_sdk_assetcashflowprojections-0.11.0-py3-none-any.whl.

File metadata

File hashes

Hashes for fds_sdk_assetcashflowprojections-0.11.0-py3-none-any.whl
Algorithm Hash digest
SHA256 aae14198b2495ef7cba39f38a014cf6b8546a786f00c87c2d055c61364badb81
MD5 79fe174e2d12e2cd7d2c8dfaa944d6a8
BLAKE2b-256 f4b2d7f58e858da3ab3c9c4a927e85c4e8904f0427cc993fdf7734a5334f033e

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page