Autoviz Python Library

Running the Autoviz

As the core visualization library of Autoviz is written in Java, this project is using the JPype module to manage the JVM and create the bridge between the Python process and visualization classes. Due to that, a proper installation of Java JDK is required as well as setting the JAVA_HOME environment variable.

After then, you can use the library as in the following example

from h2o_autoviz import Autoviz

autoviz = Autoviz()
histogram = autoviz.histogram("path/to/data.csv", "variable_name")

Note that the result of the call is a Vega-lite definition of the histogram.

Building the package

This package is using uv for project management.

Setup

Install uv following the official instructions, then sync the project dependencies:

uv sync

Running tests

make test

Linting and formatting

This project uses ruff for linting and formatting, and ty for type checking.

make lint
make format

Building the wheel

uv build

Common issues

Mac users with M1 and M2 processors may encounter a regular problem with incompatible JDK for their ARM processor.

To resolve the issue, you'll need to get the ARM-compatible JDK, such as this one. Follow this Github thread for more details