vantage_model_cataloging 1.0.1
Other Releases
Version Released Download
teradataml 17 Nov 2021
1.0.0 19 Jul 2020
1.0.0 28 Jun 2020
About this download

Teradata Python Package Product Overview

Note: Teradata recommends teradataml pip install from https://pypi.org/project/teradataml/.
Download from downloads.teradata.com location if your organization does not allow you to install directly from https://pypi.org/project/teradataml/.

The Teradata Python Package teradataml combines the benefits of the open source Python language environment with the massive parallel processing capabilities of Teradata Vantage, which includes the Machine Learning Engine analytic functions and the Advanced SQL Engine in-database analytic functions. The Teradata Python package allows users to develop and run Python programs that take advantage of the Big Data and Machine Learning analytics capabilities of Vantage.

The Teradata Python package teradataml is a Python library package like other open source Python packages. The package interface makes available to Python users a collection of functions for analytics that reside on Vantage, so that Python users can perform analytics with no SQL coding required. Specifically, the teradataml package provides functions for data manipulation and transformation, data filtering and sub- setting, and can be used in conjunction with open source Python libraries. The teradataml package uses SQLAlchemy and provides an interface similar to the Pandas Python library.
The Teradata Python Package works over connections to:
    -  Teradata Vantage with Advanced SQL Engine and ML Engine
    -  Teradata Vantage with Advanced SQL Engine only

Sandbox environment

The sandbox environment is based on a SLES12 SP3 docker image that contains a Python distribution (interpreter and add-on libraries) based on the latest Teradata In-nodes Python release for SLES12-SP3:

  • Python interpreter (Version 3.7.7)
  • Add-on libraries for Python

User can choose to setup the docker environment and test Python scripts by running them inside the docker container, or user can directly execute scripts on Vantage.

The sandbox environment docker image  name is "stosandbox:1.0".

The docker image size is about 4 GB. Due to the large size, Teradata recommends downloading it beforehand, and saving it into a local folder.

Model Cataloging

Model Cataloging allows users to save the model related information in such a way that it can be reused using the supported functions from the Vantage Advanced SQL and Machine Learning Engines via SQL, Teradata Python Package (teradataml) or Teradata R client Package (tdplyr) client analytic libraries

teradataml offers APIs to use Model Cataloging, allowing users to:

  • Save a model and related information to the Advanced SQL database;
  • List the saved models;
  • Describe a model;
  • Retrieve a model;
  • Publish a model;
  • Delete a model.

In order for any user to use the model cataloging feature in teradataml, setup must be performed by the administrator on the Vantage system. The required scripts along with the instructions to set up the Vantage system are part of this bundle vantage_model_cataloging_1.0.0.tar.gz.

General product information is available in the Teradata Documentation Website.

Teradata Python Package User Guide – B700-4006

Teradata Python Package Function Reference – B700-4008

For community support, please visit the Connectivity Forum.

For Teradata customer support, please visit Teradata Access.