When you install the MLflow Python package, a set of core dependencies needed to use most MLflow functionality (tracking, projects, models APIs) is also installed.
However, in order to use certain framework-specific MLflow APIs or configuration options,
you need to install additional, "extra" dependencies. For example, the model persistence APIs under
the mlflow.sklearn module require scikit-learn to be installed. Some of the most common MLflow
extra dependencies can be installed via pip install mlflow[extras].
The full set of extra dependencies are documented, along with the modules that depend on them, in the following files:
- extra-ml-requirements.txt: ML libraries needed to use model persistence and inference APIs
- small-requirements.txt, large-requirements.txt: Libraries required to use non-default artifact-logging and tracking server configurations