fds.sdk.AxiomaEquityOptimizer 0.21.3

Axioma Equity Optimizer client library for Python

Axioma Equity Optimizer client library for Python

Allow clients to fetch Analytics through APIs.

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

• API version: 3
• Package version: 0.21.3
• 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.AxiomaEquityOptimizer

pip

pip install fds.sdk.utils fds.sdk.AxiomaEquityOptimizer

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

# Enter a context with an instance of the API client
with fds.sdk.AxiomaEquityOptimizer.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = axp_optimizer_api.AXPOptimizerApi(api_client)
    id = "id_example" # str | from url, provided from the location header in the Create and Run Axioma optimization endpoint

    try:
        # Cancel Axioma optimization by id
        api_instance.cancel_optimization_by_id(id)
    except fds.sdk.AxiomaEquityOptimizer.ApiException as e:
        print("Exception when calling AXPOptimizerApi->cancel_optimization_by_id: %s\n" % e)

    # Get response, http status code and response headers
    # try:
    #     # Cancel Axioma optimization by id
    #     api_response, http_status_code, response_headers = api_instance.cancel_optimization_by_id_with_http_info(id)
    # except fds.sdk.AxiomaEquityOptimizer.ApiException as e:
    #     print("Exception when calling AXPOptimizerApi->cancel_optimization_by_id: %s\n" % e)

    # Get response asynchronous
    # try:
    #     # Cancel Axioma optimization by id
    #     async_result = api_instance.cancel_optimization_by_id_async(id)
    # except fds.sdk.AxiomaEquityOptimizer.ApiException as e:
    #     print("Exception when calling AXPOptimizerApi->cancel_optimization_by_id: %s\n" % e)

    # Get response, http status code and response headers asynchronous
    # try:
    #     # Cancel Axioma optimization by id
    #     async_result = api_instance.cancel_optimization_by_id_with_http_info_async(id)
    # except fds.sdk.AxiomaEquityOptimizer.ApiException as e:
    #     print("Exception when calling AXPOptimizerApi->cancel_optimization_by_id: %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.AxiomaEquityOptimizer

logging.basicConfig(level=logging.DEBUG)

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

Documentation for API Endpoints

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

Class	Method	HTTP request	Description
AXPOptimizerApi	cancel_optimization_by_id	DELETE /analytics/engines/axp/v3/optimizations/{id}	Cancel Axioma optimization by id
AXPOptimizerApi	get_optimization_parameters	GET /analytics/engines/axp/v3/optimizations/{id}	Get Axioma optimization parameters by id
AXPOptimizerApi	get_optimization_result	GET /analytics/engines/axp/v3/optimizations/{id}/result	Get Axioma optimization result by id
AXPOptimizerApi	get_optimization_status_by_id	GET /analytics/engines/axp/v3/optimizations/{id}/status	Get Axioma optimization status by id
AXPOptimizerApi	post_and_optimize	POST /analytics/engines/axp/v3/optimizations	Create and Run Axioma optimization
AXPOptimizerApi	put_and_optimize	PUT /analytics/engines/axp/v3/optimizations/{id}	Create or Update Axioma optimization and run it.
AccountsApi	get_accounts	GET /analytics/lookups/v3/accounts/{path}	Get accounts and sub-directories in a directory
CurrenciesApi	get_currencies	GET /analytics/lookups/v3/currencies	Get currencies
StrategyDocumentsApi	get_axioma_equity_strategy_documents	GET /analytics/engines/axp/v3/strategies/{path}	Get Axioma Equity strategy documents and sub-directories in a directory

Documentation For Models

• AccountDirectories
• AccountDirectoriesRoot
• AxiomaEquityOptimizationParameters
• AxiomaEquityOptimizationParametersRoot
• CalculationInfo
• CalculationInfoRoot
• ClientErrorResponse
• Currency
• CurrencyRoot
• DocumentDirectories
• DocumentDirectoriesRoot
• Error
• ErrorSource
• ObjectRoot
• OptimalPortfolio
• Optimization
• OptimizerAccount
• OptimizerAccountOverrides
• OptimizerOptimalHoldings
• OptimizerOutputTypes
• OptimizerStrategy
• OptimizerStrategyOverrides
• OptimizerTradesList

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