Release v0.4.0: bootstrap5, pipeline support and drops python 3.7, 3.8 · oegedijk/explainerdashboard

Version 0.4.0: upgrade bootstrap5, drop python 3.6 and 3.7 support and improved pipeline support

Upgrades the dashboard to bootstrap5 and dash-bootstrap-components v1 (which is also based on bootstrap5), this
may break older custom dashboards that included bootstrap5 components from dash-bootstrap-components<1
Support terminated for python 3.6 and 3.7 as the latest version of scikit-learn (1.1) dropped support as well
and explainerdashboard depends on the improved pipeline feature naming in scikit-learn>=1.1

Better support for large datasets through dynamic server-side index dropdown option selection. This means that not all indexes have to be stored client side in the browser, but
get rather automatically updated as you start typing. This should help especially with large datasets with large number of indexes.
This new server-side dynamic index dropdowns get activated if the number of rows > max_idxs_in_dropdown (defaults to 1000).
Both sklearn and imblearn Pipelines are now supported with automated feature names generated, as long as all the transformers have a .get_feature_names_out() method
Adds shap_kwargs parameter to the explainers that allow you to pass additional kwargs to the shap values generating call, e.g. shap_kwargs=dict(check_addivity=False)
Can now specify absolute path with explainerfile_absolute_path when dumping dashboard.yaml with db.to_yaml(...)

Suppresses warnings when extracting final model from pipeline that was not fitted on a dataframe.

No longer limiting werkzeug version due to upstream bug fixes of dash and jupyter-dash