Key Feature Additions and Changes | Teradata Package for Python 20.00 - Key Feature Additions and Changes - Teradata Package for Python

Teradata® Package for Python User Guide

Teradata Package for Python
Release Number
March 2024
English (United States)
Last Update
Product Category
Teradata Vantage

The following table lists the key feature additions and changes in the Teradata Package for Python, teradataml.

Date Release Description
March 2024
  • Added new feature - teradataml open-source machine learning functions (teradataml OpenSourceML) that dynamically exposes open-source packages through Teradata Vantage. It provides an interface object through which exposed classes and functions of open-source packages can be accessed with the same syntax and arguments.
  • Added new feature - AutoML that automates the process of building, training, and validating machine learning models. It involves automation of various aspects of the machine learning workflow, such as feature exploration, feature engineering, data preparation, model training and evaluation for given dataset.
  • Added new deploy() method to deploy models generated after running script, in database when connected to VantageCloud Enterprise (as part of Script table operator), or in user environment when connected to VantageCloud Lake (as part of Apply table operator).
  • Added new DataFrame manipulation functions cube(), rollup(), replace.
  • Added eight categories of new DataFrame Column functions:
    • Bit Byte Manipulation Functions
    • Comparison Functions
    • Date Time Functions
    • Hyperbolic Functions
    • Regular Arithmetic Funstions
    • Regular Expression Functions
    • String Functions
    • Trigonometric Functions
  • Removed functionalities that have been deprecated:
    • Machine Learning Engine functions
    • Model Cataloging feature
    • Sandbox feature that supports testing script in both Script table operator and Apply table operator.
Feburary 2024 Updated Open Analytics Framework APIs to support VantageCloud Lake use of Anaconda for building conda environments to run Python analytic workload on Open Analytics Framework:
  • Updated create_env() with new argument conda_env to specify whether the environment to be created is a conda environment or not.
  • Output of list environment APIs have a new column "conda" to show whether the environment is a conda environment or not.
  • Updated set_auth_token to address Open Analytics Login Issue with teradataml and
  • Updated list_user_envs() with new argument conda_env to specify whether to filter the conda environments when listing user environments.
January 2024
  • New teradataml DataFrame Column functions:
    • 19 new Bit Byte Manipulation Functions
    • 4 new Regular Expression Functions
    • 2 new Display Functions
  • New and updated Open Analytics Framework APIs:
    • Updated create_env() so user can create one or more user environments using the new argument template by providing specifications in template json file.
    • New UserEnv Class property models, and methods install_model() and uninstall_model() to list, install and uninstall models in user environment.
    • New UserEnv Class method snapshot() to take snapshot of user environment.
  • New BYOM function DataRobotPredict() to score the data in Vantage using the model trained externally in datarobot and stored in Vantage.
  • Updated DataFrame functions:
    • DataFrame.describe() method to accept argument statistics to specify the aggregate operation to perform.
    • DataFrame.sort() method to accept ColumnExpression, and enable sorting.
    • DataFrame.sample() method to support column stratification.
  • Updated general function view_log() to download the APPLY query logs.
  • Updated Analytics Database analytic functions so arguments which accept floating numbers will accept integers.
  • Updated DataFrame.plot() function to ignore the null values while plotting data.
October 2023
  • New hyperparameter tuning feature to determine the optimal set of hyperparameters for the given dataset and learning model.
    • GridSearch algorithm covers all possible parameter values to identify optimal hyperparameters.
    • RandomSearch algorithm performs random sampling on hyperparameter space to identify optimal hyperparameters.
  • New plotting feature to visualize analytic results.
  • New teradataml DataFrame functions:
    • DataFrame.plot() to generate plots on teradataml DataFrame.
    • DataFrame.itertuples() to iterate over teradataml DataFrame rows as namedtuples or list.
  • New teradataml GeoDataFrame function GeoDataFrame.plot() to generate plots on teradataml GeoDataFrame.
  • New BYOM function DataikuPredict() to score the data in Vantage using the model trained externally in Dataiku UI and stored in Vantage.
  • New teradataml DataFrame Column functions:
    • Regular Arithmetic Functions
    • Trigonometric Functions
    • Hyperbolic Functions
    • String Functions
  • New general function async_run_status() to check the status of asynchronous runs using unique run ids.
  • New teradataml configuration option configure.indb_install_location to specify the installation location of in-database Python package.
  • Updated Open Analytics Framework APIs:
    • set_auth_token() does not accept username and password anymore. Instead, function opens up a browser session and user should authenticate in browser.
    • User environments, files and libraries related APIs updated to support R environment.
  • Updated Unbounded Array Framework (UAF) function ArimaEstimate() to support for CSS algorithm via algorithm argument.