For all users
object mode
pip
@jit
nopython
nogil
cache
parallel
@vectorize
@guvectorize
@jitclass
as_numba_type
numba.typed
@cfunc
numba.types.Record.make_c_struct
@stencil
neighborhood
func_or_mode
cval
standard_indexing
StencilFunc
out
objmode
jit_module
@jit(forceobj=True)
gdb
parallel=True
typed
CUDA initialized before forking
array
cmath
collections
ctypes
enum
math
operator
functools
random
heapq
cffi
stride_tricks
numba.pycc
NUMBA_CAPTURED_ERRORS
For CUDA users
For advanced users & developers
numba.experimental.structref
jit
@overload
towncrier
maint/gitlog2changelog.py
Rewrite
Rewrite.match()
Rewrite.apply()
RewriteArrayExprs.match()
RewriteArrayExprs.apply()
_lower_array_expr()
numba.jit()
numba.extending.overload()
PYTHONHASHSEED
sys.monitoring
Literal
LOAD_FAST_AND_CLEAR
Expr.undef
UndefVar
This is a maintenance release that adds support for NumPy 1.26 and fixes a bug.
Support for NumPy 1.26 is added.
(PR-#9227)
Float default arguments in inline closures would produce incorrect results since updates for Python 3.11 - these are now handled correctly again.
(PR-#9222)
PR #9220: Support passing arbitrary flags to NVVM (gmarkall)
PR #9227: Support NumPy 1.26 (PR aimed at review / merge) (Tialo gmarkall)
PR #9228: Fix #9222 - Don’t replace . with _ in func arg names in inline closures (gmarkall)
gmarkall
Tialo