v0.5.4: support dash-bootstrap-components v2

Version 0.5.4:

Breaking Changes

• Require Dash >=3.0.4 to support dash-bootstrap-components 2.x

Improvements

• Relaxed dash-bootstrap-components upper bound to allow 2.x releases
• Updated DropdownMenu alignment to use align_end for dbc 2.x
• Adjusted logistic regression test fixture to avoid convergence warnings

Bug Fixes

• Avoid sklearn feature-name warnings in PDP computations by passing numpy arrays to estimators without feature_names_in_
• Consistent model-input handling in PDP and prediction helpers to prevent warning noise

v0.5.3: relax numpy v2

Version 0.5.3:

Improvements

• Allow NumPy 2.x but cap to <2.4 on Python 3.11+ to avoid numba/llvmlite downgrade issues

v0.5.2: dash v3 and plotly v6 compatibility + dtreeviz fixes

Version 0.5.2:

Breaking Changes

• Dropped support for Python 3.8 and 3.9 (Python 3.9 reached end-of-life). Minimum Python version is now 3.10
• Now explicitly supports and tests on Python 3.10, 3.11, 3.12, and 3.13

Improvements

• Removed upper version constraints for dash and plotly dependencies, now supports Dash 2.10+ and 3.0+, and Plotly 5.0+ and 6.0+
• Added backward compatibility code to support both Dash 2.x (app.run_server()) and Dash 3.x (app.run()) APIs
• Fixed Plotly 6.0 compatibility by updating titlefont to title.font format
• Improved integration test setup with automatic ChromeDriver management via webdriver-manager
• Fixed threading issues with Plotly validator initialization by switching to recommended plotly.graph_objects import
• Made torch and skorch optional dependencies on Intel Macs (where torch wheels are not available)

Bug Fixes

• Fixed SystemExit warnings in integration tests caused by Plotly validator initialization in multi-threaded contexts
• Updated .gitignore to exclude webdriver-manager cache directories and uv.lock file
• XGBoost 3.1+ compatibility: Fixed handling of string-formatted predictions and base_score values returned by XGBoost 3.1+. Added robust string-to-numeric conversion with proper regex fallback to handle various string formats (e.g., '[3.2967056E1]', '[8.563135E-2,7.169811E-1,1.9738752E-1]')
• XGBoost SHAP initialization: Fixed base_score conversion in both get_params() and booster's internal JSON configuration to ensure SHAP TreeExplainer initializes correctly with XGBoost 3.1+
• RandomForest dtreeviz compatibility: Fixed dtype handling for y_train (now uses int instead of int16) and observation array conversion for predict_path() to work with newer dtreeviz versions
• Dtreeviz decisiontree_view: Ensure observations are passed as numpy arrays to avoid pandas label lookup errors when dtreeviz indexes features by integer position
• PyPI packaging: Removed duplicate wheel entries from hatchling build config to fix "Duplicate filename in local headers" upload errors
• Pandas deprecation warnings: Removed deprecated pd.option_context("future.no_silent_downcasting") and copy=False parameter from .infer_objects() calls
• Runtime warnings: Fixed divide-by-zero warnings in classification plots and residuals plots (log-ratio calculations) by adding proper zero checks and using np.divide() with where parameter

v0.5.0: migrate to pyproject.toml and uv

migrating to modern pyproject.toml (and deprecating old setup.py)

v0.4.8: sklearn 1.6 compatibility

minor changes to ensure sklearn 1.6 compatibility.

Certain models like xgboost or skorch have not updated their sklearn_tags properties, but presumably these will be be fixed upstream soon.

V0.4.7: categorical bug fixes

Version 0.4.7:

Bug Fixes

• fix merge_categorical_columns when there are no cats
• Handle pandas option setting context in case it doesn't exist
• Remove is_categorical_dtype as it is getting deprecated

v0.4.6.1: bump because pypi token expired

Update upload_to_pypi.yml

v0.4.6: compatibility with shap>0.45

Bug Fixes

• should now work with the format of shap 0.45 that returns a three dimensional np.array instead of a list of 2-dimensional np.arrays for classifiers

Improvements

• Fixed several pandas warning about to be deprecated behaviours

v0.4.5: drop numpy<1.25 restriction

• it seems numba and numpy are getting along better again

v0.4.4: minor skorch check_additivity warning

Bug Fixes

• Add warning to set shap_kwargs=dict(check_additivity=True) for skorch models, and switch this on for the tests.