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:
If you want to know more, you can watch our recent workshop “Refactor your Jupyter notebooks using Kedro” on YouTube:
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Cano Rodríguez, Juan Luis
Developer Advocate at QuantumBlack Labs
McKinsey & Company
M +34 686 75 72 97
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