Hi all,
It fills us with astronomical joy to announce the release of Kedro 0.18.9! đź”¶
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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