ZenML is an open-source MLOps framework that helps you build reproducible, production-ready ML pipelines. It provides a unified interface for orchestrating pipelines, managing infrastructure, and tracking experiments across various backends (local, cloud, Kubernetes). The current version is 0.94.3, with frequent releases (multiple per month). It requires Python >=3.10,<3.14.
pip install zenmlNo compatibility data collected yet for this library.
Verified import paths — ran on the pinned version, not inferred.
Define and run a simple two-step pipeline locally.
Update code to handle lists of artifact versions instead of single artifacts.
Skip `zenml init` unless instructed by the documentation for ZenML Pro.
Run the provided script to delete pipelines with `latest_run_status is None` before server upgrade.
Update custom step operators to implement the new methods.
Use `from zenml import pipeline, step` instead.
Use `from zenml import ArtifactConfig`.
Iterate over the list: for artifact in step_run.regular_inputs['key']: ...
Run `zenml upgrade` or manually delete and reinitialize the database (careful with production data).