Wallaroo SDK Essentials Guide

Reference Guide for the most essential Wallaroo SDK Commands

The following commands are the most essential when working with Wallaroo. They are listed in the order that a typical workflow would follow as the following:

Supported Model Versions and Libraries

The following ML Model versions and Python libraries are supported by Wallaroo. When using the Wallaroo autoconversion library or working with a local version of the Wallaroo SDK, use the following versions for maximum compatibility.

Library Supported Version
Python 3.8.6 and above
onnx 1.12.0
tensorflow 2.9.1
keras 2.9.0
pytorch Latest stable version. When converting from PyTorch to onnx, verify that the onnx version matches the version above.
sk-learn aka scikit-learn 1.1.2
XGBoost 1.6.2
MLFlow 1.30.0

Wallaroo SDK Essentials Guide: Client Connection

How to connect to a Wallaroo instance through the Wallaroo SDK

Wallaroo SDK Essentials Guide: Workspace Management

How to create and use Wallaroo Workspaces through the Wallaroo SDK

Wallaroo SDK Essentials Guide: Model Management

How to create and manage Wallaroo Models through the Wallaroo SDK

Wallaroo SDK Essentials Guide: User Management

How to create and manage Wallaroo Users through the Wallaroo SDK

Wallaroo SDK Essentials Guide: Pipeline Management

How to create and manage Wallaroo Pipelines through the Wallaroo SDK

Wallaroo SDK Essentials Guide: Tag Management

How to create and manage Wallaroo Tags through the Wallaroo SDK

Wallaroo SDK Essentials Guide: Inferencing

How to use Wallaroo for model inferencing through the Wallaroo SDK

Wallaroo SDK Essentials Guide: Assays Management

How to create and manage Wallaroo Assays through the Wallaroo SDK