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 +=============================================================+ This email is confidential and may be privileged. If you have received it in error, please notify us immediately, delete the email, and do not copy it, disclose its contents or use it for any purpose. +=============================================================+