Installation¶

Ubunye Engine runs on Python 3.10 to 3.13, on Linux, Windows and macOS. Every one of those is tested on every change.

Core install¶

pip install ubunye-engine

This installs the CLI, config loader, plugin registry, and lineage tracker. The engines that move data are optional extras: pick the one you need.

Install extras¶

pandas (no Java)SparkMLDev (contributors)

pip install "ubunye-engine[pandas]"

Adds pandas and pyarrow. Runs a task on your laptop or in CI with no Spark and no Java, reading and writing exactly as Spark does. See Execution backends.

pip install "ubunye-engine[spark]"

Adds pyspark. Required for format: hive, format: delta, and format: unity. Add delta for Delta Lake outside Databricks: pip install "ubunye-engine[spark,delta]".

pip install "ubunye-engine[ml]"

Adds scikit-learn, mlflow, and the ML plugin wrappers.

git clone https://github.com/ubunye-ai-ecosystems/ubunye_engine.git
cd ubunye_engine
pip install -e ".[dev]"
pre-commit install

See Contributing for the test tiers.

Verify the install¶

ubunye version

prints the version you installed, for example:

Ubunye Engine v0.7.0

See which engines you can run on, and what each can do:

ubunye backends

System requirements¶

Requirement	Tested
Python	3.10, 3.11, 3.12, 3.13
Operating system	Linux, Windows, macOS
pandas backend	pandas 2.2 or newer with pyarrow 14 or newer (24 or newer on Windows)
Spark backend	Spark 3.5 with Java 11, Spark 4 with Java 17 or 21

The oldest versions listed are the ones the package accepts, and CI installs exactly those and runs the tests on them.

Databricks

On Databricks the cluster already has PySpark installed. Install only the core package on the driver:

%pip install ubunye-engine