As pointed in the Setting Up VantageCloud Lake for Open Analytics section, among the first steps in using Open Analytics Framework, you need to create a user environment, which is a user-configured space where users can run their external language scripts. User environments have user-specified characteristics such as a name, a description, an external language interpreter kind and version, associated language libraries, and user files.
The Open Analytics Framework backend provides a rich set of REST APIs to end users for interacting with their user environments. These APIs are designed to be called via simple HTTP(S) requests over the network and are unique to every VantageCloud Lake system. Furthermore, the Open Analytics Framework APIs works with the Analytic Compute Clusters by allowing the created user environments to be utilized for code execution when users run Apply Table Operator SQL queries.
User environments can be created and managed by users and database administrators (DBAs) alike. To make changes to an analytic compute group, users need first to have suitable permissions and set their current session to that group in their VantageCloud Lake system. See User Profile and User Sessions . The same procedures are applicable to all personas.
There are no SQL functions to call the Open Analytics Framework REST APIs. In that sense, a Teradata Vantage user cannot invoke any of these APIs in SQL prior to an APPLY table operator query. However, the Teradata Package for Python (teradataml) features a complete set of methods and properties that interface the Open Analytics Framework REST APIs as Python methods. In teradataml, a user's remote environment on a Open Analytics Framework system is represented by the Python class UserEnv. Through this class, Open Analytics Framework REST API is accessible through dedicated teradataml UserEnv methods and properties that implement Python wrappers for these API calls.