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 RodrĂ­guez, Juan Luis
Developer Advocate at QuantumBlack Labs
Pronouns: he/him/his
McKinsey & Company
M +34 686 75 72 97

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