Release 4.9.1

Changes from 4.9.0 to 4.9.1

A small hot-fix release for the Arrow interop work in 4.9.0: a real
performance regression in dictionary-column export, and a clearer error
message when opening a nonexistent CTable in append mode.

Improvements

• CTable.iter_arrow_batches() (and therefore to_arrow() and the Arrow
  PyCapsule interchange, __arrow_c_stream__) no longer recomputes the
  full live-row-position array from scratch on every batch, for every
  dictionary column — an O(n_rows) scan that was repeated
  O(n_rows / batch_size) times. The position array is now computed once
  per export call instead. Measured 6-14x faster export for
  dictionary-encoded string columns (e.g. company) on a 1M-row table.
• Reminder for anyone consuming a CTable through the Arrow PyCapsule
  protocol (DuckDB, pyarrow, Polars, pandas): the raw Arrow C Stream
  interface has no column-projection pushdown, so a consumer that only
  needs a few columns still triggers export of every column in the table.
  Use CTable.select([...]) to project down to the columns you actually
  need before handing the table to the consumer, particularly if any
  column is an expensive nested/list type.

Bug fixes

• Opening a CTable with mode="a" at a path that doesn't exist yet now
  raises a clear FileNotFoundError ("mode='a' opens an existing table;
  use mode='w' to create a new one") instead of silently falling through
  and creating a new, empty table.