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:


If you want to know more, you can watch our recent workshop “Refactor your 
Jupyter notebooks using Kedro ” on YouTube:


Follow us on the Fediverse and join our community in Slack:


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

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