Hi all,

It fills us with astronomical joy to announce the release of Kedro 0.18.8! 🔶

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
```

This release brought support for a new `KEDRO_LOGGING_CONFIG` environment 
variable to configure logging, better reproducibility for `kedro run`, lots of 
documentation improvements, and much more. For existing users, note that 
`kedro.extras.datasets` is deprecated in favor of the separate `kedro_datasets` 
package.

You can read the full release notes online:

https://github.com/kedro-org/kedro/blob/main/RELEASE.md#release-0188

If you want to know more, you can subscribe to our YouTube channel, follow us 
on the Fediverse or join our community in Slack:

https://youtube.com/@kedro-python
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


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