Hi all, It fills us with astronomical joy to announce the release of Kedro 0.18.9! 🔶 Kedro is an open source, opinionated 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 conda/[micro]mamba install kedro --channel conda-forge ``` In this release, we added support for a metadata attribute in datasets, introduced a new `kedro.logging.RichHandler` that is more flexible and configurable, and fixed some bugs with `OmegaConfigLoader`. We also added substantial improvements to our deployment docs, and we keep making progress towards following modern Python packaging standards. You can read the full release notes online: https://github.com/kedro-org/kedro/blob/main/RELEASE.md#release-0189 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 Developer Advocate at QuantumBlack Labs Pronouns: he/him/his McKinsey & Company 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. +=============================================================+