Release Release 4.3.3 · Blosc/python-blosc2

Changes from 4.3.1 to 4.3.3

note: 4.3.2 was an internal pre-release that was not published to PyPI.

This is a maintenance release focused on CTable display ergonomics, indexed-query
correctness, and query-planner performance.

Pandas-like CTable display by default: str(table) / print(table) now use
a compact, pandas/DuckDB-style table representation, including a displayed
logical row index, numeric alignment, compact spacing, and a trailing footer
such as [726017 rows x 5 columns].
Configurable display options: added blosc2.set_printoptions() and
blosc2.get_printoptions() for CTable rendering. The supported options are
display_index, display_rows, display_precision, and fancy.
CTable.to_string(): added a one-off formatting API for producing CTable
string representations without changing global print options.
Compact truncation for large tables: when a table exceeds the configured
display_rows threshold, only the first five and last five rows are shown,
with an ellipsis row in between.
Float display refinements: compact mode uses pandas-like fixed precision
for floating-point columns, and integer-valued float columns are displayed
with a single decimal place.
Fancy display preserved: set_printoptions(fancy=True) restores the more
decorated display with dtype rows, separator rules, and hidden row/column
counts.

Cross-column exact index refinement: multi-column conjunctions can now use
exact positions from a selective indexed column (FULL, PARTIAL, or OPSI)
as a compact pre-filter, then refine the remaining predicates on those
positions instead of scanning the full table.
NaN-safe index boundary navigation: fixed sorted-boundary navigation for
floating-point indexes containing NaN values, so indexed results match scan
results for bucket/full index lookups.
Better index-planner heuristics: the planner now avoids low-value indexed
paths when segment pruning is unlikely to help, and avoids expensive scalar
specialization for non-scalar arrays.
Faster filtered sorting: small filtered views can be materialized and
sorted directly, avoiding an extra gather of sort keys.

Avoid full materialization of valid_rows in several CTable code paths.
Keep row counts lazy for views and avoid unnecessary nrows calls in the
query planner.
Reduced overhead in root-column iteration and small query-planner operations.
Fixed dictionary-column capacity handling during Arrow import and a regression
affecting dictionary columns.
Marked additional long-running tests as heavy to reduce default test-suite
runtime.

Updated the containers tutorial with dedicated ListArray and CTable
sections, including CTable's columnar storage model and support for columns
backed by NDArray, BatchArray, ObjectArray, ListArray, and related
containers.