System Requirements | Teradata Package for Python 20.00.00.09 - Teradata Package for Python System Requirements - Teradata Package for Python

Teradata® Package for Python User Guide

Deployment
VantageCloud
VantageCore
Edition
VMware
Enterprise
IntelliFlex
Product
Teradata Package for Python
Release Number
20.00
Published
March 2025
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en-US
ft:lastEdition
2026-02-20
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Product Category
Teradata Vantage

Required Software on Teradata Vantage

Based on the connection to Vantage, the teradataml package requires the following minimum software versions be installed on Vantage:

Teradata Vantage with database release 16.20.16.01 or later or VantageCloud Lake.

Required Software on Client

The teradataml package requires a minimum version of the following software be installed on the client:
  • Python >= 3.8 (For IBM PowerPC Python >= 3.9)
  • Operating Systems:
    • Windows OS: Windows 7
    • macOS: os x 10.9
    • Linux: Ubuntu 16.04, CentOS 7.0, RHEL 7.1 with gcc 5.5, or SLES 12
    The teradataml package only supports 64-bit version of these operating systems.
  • Dependent packages:
    • teradatasql 17.10.00.11
    • teradatasqlalchemy 20.0.0.02
    • pandas 0.22.00
    • psutil
    • requests >=2.25.1
    • scikit-learn >= 0.24.2
    • IPython >= 8.10.0
    • imbalanced-learn >= 0.8.0
    • pyjwt >= 2.8.0
    • cryptography >= 42.0.5

Compatible Development Environment

The following third-party Integrated Development Environment (IDE) and data science user interface (UI) tool is compatible with Teradata Package for Python:

  • Jupyter
  • Spyder

Optional Dependency Installation

To use the the following Teradata Package for Python features, you need to manually install the corresponding optional dependencies.

Feature Required Packages
AutoML Family functions imbalanced-learn, scikit-learn
OpenSourceML scikit-learn, lightgbm
Visualization matplotlib, seaborn
Teradataml EDA UI teradatamlwidgets

Install any optional feature dependencies using:

pip install teradataml[<feature_name>]
Where <feature_name> can be one of:
  • automl – Installs dependencies for AutoML capabilities
    Example:
    pip install teradataml[autonml]
  • openml – Installs dependencies for OpenSourceML features
    Example:
    pip install teradataml[openml]
  • visualization – Installs visualization libraries
    Example:
    pip install teradataml[visualization]
  • eda-ui – Installs UI components for EDA workflows
    Example:
    pip install teradataml[eda-ui]