facebookresearch/balance 0.14.0 on GitHub

New Features

Enhanced adjusted sample summary output
- Sample.__str__() now displays adjustment details (method, trimming
  parameters, design effect, effective sample size) when printing adjusted
  samples (#194,
  #57).
Richer Sample.summary() diagnostics
- Adjusted sample summary now groups covariate diagnostics, reports design
  effect alongside ESSP/ESS, and surfaces weighted outcome means when
  available.
Warning of high-cardinality categorical features in .adjust()
- Categorical features where ≥80% of values are unique are flagged before
  weight fitting to help identify problematic columns like user IDs
  (#195,
  #65).
Ignored column handling for Sample inputs
- Sample.from_frame accepts ignore_columns for columns that should remain
  on the dataframe but be excluded from covariates and outcome statistics.
  Ignored columns appear in Sample.df and can be retrieved via
  Sample.ignored_columns().

Consolidated diagnostics helpers
- Added _concat_metric_val_var() helper and balance.util._coerce_scalar
  for robust diagnostics row construction and scalar-to-float conversion.
- Breaking change: Sample.diagnostics() for IPW now always emits
  iteration/intercept summaries plus hyperparameter settings.

Early validation of null weight inputs
- Sample.from_frame now raises ValueError when weights contain None,
  NaN, or pd.NA values with count and preview of affected rows.
Percentile weight trimming across platforms
- trim_weights() now computes thresholds via percentile quantiles with
  explicit clipping bounds for consistent behavior across Python/NumPy
  versions.
- Breaking change: percentile-based clipping may shift by roughly one
  observation at typical limits.
IPW diagnostics improvements
- Fixed multi_class reporting, normalized scalar hyperparameters to floats,
  removed deprecated penalty argument warnings, and deduplicated metric
  entries for stable counts across sklearn versions.

Added Windows and macOS CI testing support
- Expanded GitHub Actions to run on ubuntu-latest, macos-latest, and
  windows-latest for Python 3.9-3.14.
- Added tempfile_path() context manager for cross-platform temp file
  handling and configured matplotlib Agg backend via conftest.py.