Release 4.14.1

Changes from 4.14.0 to 4.14.1

Python-Blosc2 4.14.1 is a security and feature release introducing safe
persisted-object deserialization by default, Caterva2 remote stores and
tables, compressed slicing for RemoteArray, and optimized expression
gather performance.

Safe persisted-object deserialization

• Persisted-input APIs now default to deserialize="safe". This includes
  open(), load(), from_cframe(), CFrame constructors (CFrameNDArray,
  CFrameCTable), store traversal (TreeStore, DictStore, EmbedStore),
  and CTable variable-length and batch columns. Safe mode rejects embedded
  objects, references, remote/source descriptors, proxies, and lazy recipes
  before reconstruction.
• Trusted callers that intentionally use rich persisted values must pass
  deserialize="full" explicitly. Blocked values raise the new public
  UnsafeDeserializationError. This default change is intentionally
  behavior-breaking for authority-bearing serialized values.

Caterva2 remote stores and tables

• blosc2.open() now opens Caterva2 groups as RemoteStore and Caterva2
  URLPath tables as RemoteCTable.
• RemoteCTable backed by Caterva2 supports on-demand reads, bounded row
  slices, column projection (select()), iteration, and materialization.
• Caterva2 tables fetch large row slices and materializations in bounded
  batches, preventing out-of-memory issues on large datasets. Materializing
  to urlpath= writes batches directly to disk and publishes only after the
  entire read succeeds.
• Caterva2 stores bind the active authentication token when opened and isolate
  disk cache entries per token, ensuring isolation across accounts.

Compressed slicing for RemoteArray

• Added RemoteArray.slice(item=(), **kwargs) to extract a requested selection
  directly as an independent compressed NDArray without assembling the
  complete selection as an uncompressed NumPy array.
• Output-construction keyword arguments such as cparams are forwarded directly
  to NDArray.slice.
• Fetching, compressed result assembly, and cache eviction are serialized into
  a single atomic operation, allowing selections to exceed the cache memory
  budget without cached chunks disappearing mid-construction.

Performance improvements

• Avoided zeroing full NumPy input blocks in aux_miniexpr during expression
  gather operations (#728, PR #728). Full blocks are overwritten directly by
  raw NumPy gather, keeping zero-padding only for partial edge blocks.
  Thanks to @Johnny-Kao.
• Sped up remote Caterva2 table verification in tests with column-wise
  comparisons and boundary row sampling.