Log Message:
math/py-numba: Update to 0.61.0

Changelog:
Version 0.61.0 (16 January 2025)
================================

This is a major Numba release. Numba now supports Python 3.13 as
well as NumPy 2.1. The minimum supported Python and NumPy versions
have been bumped to 3.10 and 1.24 respectively. The built-in CUDA
target ``numba.cuda`` is now deprecated and ``numba-cuda`` is the
preferred place to get CUDA support from this release onwards.
LLVM 15 is now supported via llmlite 0.44.0 as the default LLVM version.

Please find a summary of all noteworthy items below.

Highlights
~~~~~~~~~~

Add initial implementation for a new type system
------------------------------------------------

This adds a new type system that will allow Numba to
differentiate between Python and NumPy scalars.

This has been achieved as follows:

- Retain Numba's old type system as default.
- Add a config flag ``USE_LEGACY_TYPE_SYSTEM`` set to ``1`` (on) by default.
  Switching it to ``0`` (off) will activate new type system.
- Within the new type system, Python and NumPy scalars will be treated
  and returned separately as different entities through JIT compiled functions.

(`9662`__)

Python 3.13 support
-------------------

Support for Python 3.13 is added. Note that this does not include support for \ 
free-threading.

(`9682`__)

Dropped support for Python 3.9
------------------------------

This release drops official support for Python 3.9. Numba now supports Python \ 
3.10 and later.

(`9726`__)

Update the minimum supported NumPy version to 1.24
--------------------------------------------------

This release updates the minimum supported version of NumPy to 1.24.

(`9739`__)

Added Support for NumPy 2.1
---------------------------

This release adds support for NumPy 2.1 (excluding the NEP-050 semantics).

(`9741`__)

New Features
~~~~~~~~~~~~

Schedule guvectorize'd functions over ``dask.distributed``
----------------------------------------------------------

Functions decorated with ``@guvectorize`` can now be scheduled over distributed
`Dask <https://www.dask.org/>`_ clusters.

(`9495`__)

Added compile-time code coverage
--------------------------------

Support for emitting compile-time coverage data is added.
This feature is automatically activated when running Python under ``coverage``.
It collects data during the compiler's lowering phase, showing source lines
compiled into LLVM-IR, excluding dead-code eliminated lines.

(`9508`__)

Improvements
~~~~~~~~~~~~

First-class function improvements
---------------------------------

Passing a jit function as a parameter to another jit function that accepts it as
a ``FunctionType`` has two new improvements.

First, the compiler can now inline a jit function that is passed as a non-local
variable (like a global variable) to another jit function. Previously, the
interpreter had to introspect the function address for first-class function
calls, which prevented inlining. With this improvement, the compiler can
statically determine the referenced jit function and link in the corresponding
LLVM module for optimization, bypassing the need for the GIL entirely.

Second, jit functions used as first-class functions can now raise exceptions.
Before this improvement, they were subject to the same restrictions as
``@cfunc`` decorated functions, where any exceptions raised were ignored.

(`9077`__)

Improve reorderable ufunc support and add NumPy reduce related tests
--------------------------------------------------------------------

Improve reorderable ufunc support and add NumPy ufunc.reduce related tests.

(`9295`__)

Add ``axis`` support to ``np.take``
-----------------------------------

Add support for ``axis`` keyword in ``np.take``.

(`9297`__)

Allow caching of Numba functions within Zip files
-------------------------------------------------

This change enables Numba functions imported from a file within a Zip archive to
be cached, by recognizing a Zip file and using a user-wide cache directory
for the cache. Previously, Numba would fail.

For context, Zip archives are a supported-but-less-common way to distribute
Python packages, and heavily used in PySpark.

(`9630`__)

Improvements in how Pass Manager objects are created for optimizations
----------------------------------------------------------------------

Move creation of ``ModulePassManager`` object to ``_optimize_final_module``
function, preventing the usage of the same pass manager object for
compiling multiple Python functions. This would allow for better control
while optimizing unrelated modules and possibly under different settings
(degree of vectorization, optimization level, etc.).

(`9670`__)

Fixed ``typed.List __repr__()`` to display ellipsis appropriately
-----------------------------------------------------------------

``typed.List __repr__()`` has been fixed to display the list elements
without appending the ellipsis at the end, up until a maximum of 1000 elements.
Previously, the list ``repr`` would append the ellipsis at the end of the list
regardless of the number of elements in the list.

(`9693`__)

Use of dead branch pruning improved
-----------------------------------

Dead-branch pruning use is improved to support cases when the predicate
expression is dependent on a variable that later changes type.

(`9711`__)

``find_topo_sort`` reliabililty improvement
-------------------------------------------

Improves the reliability of the ``find_topo_sort`` function for complex CFGs
(typically through generated code) by replacing the recursive post order traversal
with an iterative one. This removes a risk of hitting the Python recursion limit.

(`9718`__)

NumPy Support
~~~~~~~~~~~~~

Added support for ``np.setdiff1d()``, ``np.setxor1d()``, and ``np.in1d()`` \ 
functions, as well as argument ``assume_unique`` in ``np.intersect1d()``
-------------------------------------------------------------------------------- \ 
-------------------------------------------------------------------

Support is added for: ``numpy.setdiff1d()``, ``np.setxor1d()``, ``np.in1d()``, \ 
and ``np.isin()``; and the argument ``assume_unique`` in ``np.intersect1d()``.
For ``np.in1d()``, and ``np.isin()``, the keyword ``kind`` is *not* supported, \ 
and the behaviour reflects that of NumPy prior to version 1.24.
This is equivalent to setting ``kind="sort"`` in NumPy 1.24 and later.

(`9338`__)

Support for ``np.trapezoid``
----------------------------

Add support for NumPy 2.0 new function ``numpy.trapezoid``.

(`9719`__)

Bug Fixes
~~~~~~~~~

``memcpy`` static buffer content into newly allocated buffer
------------------------------------------------------------

Fix a bug where the static buffer used to store typecode representation is not
copied to the new allocated buffer as part of a ``realloc`` operation.

(`9119`__)

Fix parfor hoisting
-------------------

Traverse blocks in the right order so that getattrs will precede calls
so that the object of the getattr can be marked as multiply defined.

(`9397`__)

Fix ParallelAccelerator hoisting logic bug
------------------------------------------

A bug in the hoisting logic of the ParallelAccelerator is fixed.
The bug caused invalid hoisting of operations that depended on non-hoistable
operations, leading to incorrect execution. With this fix, the hoisting logic
now correctly identifies and handles dependencies on non-hoistable operations,
ensuring that operations are hoisted and executed correctly.

(`9586`__)

Fix calls to ``numpy.random`` distributions with ``size=()``
------------------------------------------------------------

Calling any of the ``numpy.random`` distributions with ``size=()`` is
now supported; previously it used to raise a ``TypingError`` while
being supported by NumPy.

(`9636`__)

Fix incorrect return type of ``numpy.sum`` on boolean arrays
------------------------------------------------------------

Calling ``numpy.sum`` with ``axis`` parameter on boolean arrays incorrectly
returns bool type, while it should return int type. Consequently,
calling ``numpy.count_nonzero`` on boolean arrays also incorrectly returns
bool type. This is now fixed.

(`9705`__)

Fixed numerical error and infinite loop bug in ``numpy.random.Generator.binomial``
----------------------------------------------------------------------------------

A bug impacting the correctness of numerical results is fixed alongside an issue
which led to executing an infinite loop under specific circumstances most easily
triggered by the aforementioned correctness bug.

(`9747`__)

Fix 0.60.0 objectmode fallback regression due to bug in label renaming
----------------------------------------------------------------------

A regression in objectmode fallback introduced in Numba 0.60 is fixed. The issue
relates to the "label renaming" code mutating the IR directly opposed to
constructing new terminator nodes, the mutations would impact copies of the IR
as present in objectmode fallback.

(`9755`__)

Fix Python reference leaks in unboxing of ``numpy.random.Generator`` instances
------------------------------------------------------------------------------

Some Python reference leaks in the unboxing of ``numpy.random.Generator``
instances have been fixed. Note that it was actually the referenced
``numpy.random.BitGenerator`` that was leaking on unboxing, but it is rare to
use these objects themselves as arguments.

(`9756`__)

Fix excessive memory use/poor memory behaviour in the dispatcher for \ 
non-fingerprintable types
-------------------------------------------------------------------------------- \ 
--------------

In the case of repeated dispatch on non-fingerprintable types, the dispatcher
now uses memory in proportion to the number of unique types seen opposed to in
proportion to the number of types in total.

(`9757`__)

Fix miscompile in branch pruning of SSA form IR
-----------------------------------------------

A miscompile occurring when a binop expression with constant arguments is used
as a predicate in SSA form IR is now fixed.

(`9758`__)

Fix regression in type-inference for star-arg arguments
-------------------------------------------------------

A regression, that occurred between versions 0.59.0 and 0.60.0, in the
type-inference associated with star-arg arguments has been fixed. The cause of
the regression was the code for star-args handling in type-inference not being
updated following the switch to use new-style error handling by default.

(`9799`__)

Make Numba internally compliant under "new_style" error handling.
-----------------------------------------------------------------

Numba now uses ``new_style`` error handling by default with no alternative
available. Numba's internal code is now compliant with this error handling
style, this to continue to allow extension writers the ability to add further
implementations of "overloads" without the compiler encountering \ 
"hard errors".

(`9837`__)

Fix for Python 3.13.1 comprehension bytecode change
---------------------------------------------------

Python 3.13.1 introduces an extra ``GET_ITER`` bytecode in comprehension
processing. This change breaks Numba's comprehension support.
This patch adds logic to ignore the new ``GET_ITER`` bytecode to maintain
compatibility.

(`9837`__)

Changes
~~~~~~~

Add ``NUMBA_JIT_COVERAGE`` to control coverage support
------------------------------------------------------

The new ``NUMBA_JIT_COVERAGE`` environment variable enables or disables coverage
support. Coverage is disabled by default.

(`9887`__)

Removal of experimental RVSDG frontend
--------------------------------------

The experimental RVSDG frontend has been removed from the main Numba codebase.
This strategic decision allows for more focused and independent development of
the RVSDG frontend as a reusable component. Future development and
updates will be available at https://github.com/numba/numba-rvsdg and other new
repositories as they are developed.

(`9738`__)

POWER Support Update
--------------------

The Numba maintainers have not been actively testing or building packages for
the POWER architecture for some time. The code will be retained to ensure
compatibility with Linux distributions that may still support Power8, but POWER
support is now downgraded to unofficial status.

(`9763`__)

Disabling ``sys.monitoring`` support by default
-----------------------------------------------

The ``sys.monitoring`` support is disabled by default due to compatibility issues
with native code. In Python 3.12, the implementation and documentation lacks
clarity on native code support, which led to tools making incorrect assumptions
about Python frames and code objects. While Python 3.13 improves this situation,
many tools have not yet adapted to these changes. Consequently, tools may crash
when monitoring Numba-compiled functions. To address this, Numba disables
``sys.monitoring`` by default. Users can opt-in by setting the environment
variable ``NUMBA_ENABLE_SYS_MONITORING``.

(`9780`__)

Deprecations
~~~~~~~~~~~~

Built-in CUDA target deprecation
--------------------------------

The CUDA target built in to Numba (under ``numba.cuda``) is deprecated in
favour of further development in the NVIDIA ``numba-cuda`` package. Backward
compatibility is maintained between ``numba-cuda`` and ``numba.cuda``, and no
user code changes are needed.

(`9768`__)

Removal of ``NUMBA_CAPTURED_ERRORS``
------------------------------------

The ``NUMBA_CAPTURED_ERRORS`` environment variable and ``CAPTURED_ERRORS``
configuration variable have been removed, as per the deprecation schedule.

(`9773`__)

Infrastructure Related Changes
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Updated GHA versioning in towncrier script
------------------------------------------

Following recent updates in GitHub Actions, the version for the checkout action \ 
has been updated to v4 along with the version for setup-python GHA, which has \ 
been updated to v5.

(`9743`__)