charex 0.4.1

charex 0.4.1

charex 0.4.1 is the pre-N-D checkpoint for the Numba 0.65.1 compatibility
work. It updates the package for the NumPy 1.x/2.x support window and lands the
current scalar, 0-D, and 1-D string operation surface before the larger
N-D/broadcasting work begins.

0.4.1 is a patch update over 0.4.0: it keeps the same public operation
surface, tightens StringDType empty/NUL edge-case coverage, avoids unsafe
zero-length libc comparison calls in generated code, and refreshes benchmark
plot readability.

Compatibility

• Python >=3.10,<3.15
• Numba >=0.65.1,<0.66
• NumPy supported/tested window: >=1.22,<1.27 or >=2.0,<2.5
• llvmlite 0.47.x

np.strings support is conditional on NumPy 2.x.

Highlights

• Adds NumPy 2.x np.strings overloads for the read-only catalog.
• Adds NumPy 2.x StringDType support for scalar, 0-D, and 1-D inputs.
• Supports default StringDType() and StringDType(na_object=...) variants.
• Supports StringDType comparisons, occurrence/search, and information
  predicates for the same read-only method families as fixed-width strings.
• Supports fixed-width S/U scalar, 0-D, and 1-D inputs, including strided,
  reversed, zero-stride, read-only, and empty views.
• Preserves separate np.char and np.strings semantics, including the
  trailing whitespace/NUL behavior difference.
• Adds packaging metadata and the native charex._stringdtype helper required
  for StringDType access.

Supported Read-Only Catalog

• comparisons: equal, not_equal, greater, greater_equal, less,
  less_equal;
• occurrence/search: count, startswith, endswith, find, rfind,
  index, rindex;
• information/predicates: str_len, isalpha, isalnum, isdigit,
  isdecimal, isnumeric, isspace, islower, isupper, istitle;
• np.char.compare_chararrays for fixed-width S/U.

Not In Scope

• N-D arrays and general broadcasting.
• Transformation/output-producing operations such as replace, case conversion,
  strip, pad, join, split, encode, and decode.
• Object array bridges.
• Max-performance experimental kernels that have not been distilled.

Next Milestone

0.5.0 is reserved for the shape/layout release: fixed-width and StringDType
N-D same-shape support, general broadcasting, and the corresponding audit and
benchmark refresh.

Benchmarks

The Numba 0.65.1 benchmark matrix in
docs/benchmarks/numba-v-0.65.1 includes
fixed-width np.char inputs and NumPy 2.x StringDType inputs through
np.strings.