The Teradata Package for Python product 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 Analytics Database in-database analytic functions. The Teradata Package for Python allows users to develop and run Python programs that take advantage of the Big Data and Machine Learning analytics capabilities of Vantage.
The Teradata Package for Python is teradataml, 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 Package for Python works over connections to:
- Vantage with Analytics Database and ML EngineMachine Learning Engine is a separate legacy engine that is not part of the current standard Vantage offer. If your system has the required ML Engine, you can find ML Engine Specific Settings and Examples here: ML Engine.
- VantageCloud Lake, VantageCloud Enterprise and VantageCore with Analytics Database onlyFor this type of connection, only Analytics Database analytic functions are accessible.
Teradata Vantage Modules for Jupyter
Teradata Package for Python is included in the Docker image of Teradata Vantage Modules for Jupyter, which also includes JupyterLab and other components to run as a Docker container on a client machine.
Teradata Vantage Modules for Jupyter allows users to access Vantage in Python, R or SQL from JupyterLab notebooks.
See Teradata Vantage™ Modules for Jupyter Installation Guide, B700-4010.