Hi all, It fills us with astronomical joy to announce the release of Kedro 0.18.11! 🔶 Kedro is an open source, orchestrator-agnostic Python framework for creating reproducible, maintainable and modular data science code. It reduces technical debt when moving prototypes into production by providing a declarative data catalog, a solid project template, plumbing for creating data pipelines, and more. It features a rich ecosystem of plugins and third-party datasets and is currently an incubation-stage project of the LF AI & Data Foundation. You can install it using pip or conda/[micro]mamba: ``` pip install kedro==0.18.11 conda/[micro]mamba install kedro=0.18.11 --channel conda-forge ``` In this release, we added added a new `databricks-iris` official starter and significantly improved the documentation around Databricks deployments. We also fixed some bugs around micropackaging and remote datasets, updated the documentation for Prefect 2.0, and deprecated some class names. You can read the full release notes online: https://github.com/kedro-org/kedro/blob/main/RELEASE.md#release-01811 If you want to know more, you can watch our recent workshop “Refactor your Jupyter notebooks using Kedro ” on YouTube: https://youtu.be/qClSGY6B0r0 Follow us on the Fediverse and join our community in Slack: https://social.lfx.dev/@kedro https://slack.kedro.org/ Happy pipelining! -- Cano Rodríguez, Juan Luis Principal Product Manager & Lead Developer Advocate QuantumBlack, AI by McKinsey Pronouns: he/him/his M +34 686 75 72 97 +=============================================================+ This email is confidential and may be privileged. If you have received it in error, please notify us immediately, delete the email, and do not copy it, disclose its contents or use it for any purpose. +=============================================================+