Tue Aug 6 20:00:42 2019 UTC ()
py-numba: updated to 0.45.1

Version 0.45.1
This patch release addresses some regressions reported in the 0.45.0 release and adds support for NumPy 1.17:

* accept scalar/0d-arrays
* Fix. Parfors reduction vars not deleted.
* Use process level locks for fork() only.
* Try to fix.
* Fix np1.17 isnan, isinf, isfinite ufuncs
* Fix np.interp for np1.17 nan handling
* Fix nump1.17 random function non-aliasing

Version 0.45.0
In this release, Numba gained an experimental numba.typed.List container as a future replacement of the reflected list. In addition, functions decorated with parallel=True can now be cached to reduce compilation overhead associated with the auto-parallelization.

Enhancements from user contributed PRs (with thanks!):

James Bourbeau added the Numba version to reportable error messages, added the signature parameter to inspect_types, improved the docstring of normalize_signatur, and fixed by adding reference counting to register_dispatcher
Guilherme Leobas implemented the dominator tree and dominance frontier algorithms
Nick White fixed the issue with round in the CUDA target.
Joshua Adelman added support for determining if a value is in a range (i.e. x in range(...)), and added windowing functions (np.bartlett, np.hamming, np.blackman, np.hanning, np.kaiser) from NumPy.
Lucio Fernandez-Arjona added support for np.select
Rob Ennis added support for np.flatnonzero
Keith Kraus extended the __cuda_array_interface__ with an optional mask attribute.
Gregory R. Lee replaced deprecated use of inspect.getargspec


(adam)
diff -r1.10 -r1.11 pkgsrc/math/py-numba/Makefile
diff -r1.9 -r1.10 pkgsrc/math/py-numba/distinfo
cvs diff -r1.10 -r1.11 pkgsrc/math/py-numba/Makefile (expand / switch to unified diff)

--- pkgsrc/math/py-numba/Makefile 2019/06/21 08:07:47 1.10
+++ pkgsrc/math/py-numba/Makefile 2019/08/06 20:00:42 1.11
@@ -1,16 +1,16 @@ @@ -1,16 +1,16 @@
1# $NetBSD: Makefile,v 1.10 2019/06/21 08:07:47 adam Exp $ 1# $NetBSD: Makefile,v 1.11 2019/08/06 20:00:42 adam Exp $
2 2
3DISTNAME= numba-0.44.1 3DISTNAME= numba-0.45.1
4PKGNAME= ${PYPKGPREFIX}-${DISTNAME} 4PKGNAME= ${PYPKGPREFIX}-${DISTNAME}
5CATEGORIES= math python 5CATEGORIES= math python
6MASTER_SITES= ${MASTER_SITE_PYPI:=n/numba/} 6MASTER_SITES= ${MASTER_SITE_PYPI:=n/numba/}
7 7
8MAINTAINER= pkgsrc-users@NetBSD.org 8MAINTAINER= pkgsrc-users@NetBSD.org
9HOMEPAGE= http://numba.pydata.org/ 9HOMEPAGE= http://numba.pydata.org/
10COMMENT= NumPy aware dynamic Python compiler using LLVM 10COMMENT= NumPy aware dynamic Python compiler using LLVM
11LICENSE= 2-clause-bsd 11LICENSE= 2-clause-bsd
12 12
13DEPENDS+= ${PYPKGPREFIX}-llvmlite>=0.29.0:../../devel/py-llvmlite 13DEPENDS+= ${PYPKGPREFIX}-llvmlite>=0.29.0:../../devel/py-llvmlite
14 14
15USE_LANGUAGES= c c++ 15USE_LANGUAGES= c c++
16 16
cvs diff -r1.9 -r1.10 pkgsrc/math/py-numba/distinfo (expand / switch to unified diff)

--- pkgsrc/math/py-numba/distinfo 2019/06/21 08:07:47 1.9
+++ pkgsrc/math/py-numba/distinfo 2019/08/06 20:00:42 1.10
@@ -1,7 +1,7 @@ @@ -1,7 +1,7 @@
1$NetBSD: distinfo,v 1.9 2019/06/21 08:07:47 adam Exp $ 1$NetBSD: distinfo,v 1.10 2019/08/06 20:00:42 adam Exp $
2 2
3SHA1 (numba-0.44.1.tar.gz) = 46fb3983e7b437e4538d9120a2e2547ee9684fba 3SHA1 (numba-0.45.1.tar.gz) = 145161745447afea32a4dcdd0bf4875896d220df
4RMD160 (numba-0.44.1.tar.gz) = 95a485234bbfba71e854f4ef6d70ff2a86de8ee5 4RMD160 (numba-0.45.1.tar.gz) = a996debccb1a6889789c926d3b4d28262c30aceb
5SHA512 (numba-0.44.1.tar.gz) = b29f413ede9ac3396a25fabaaa107cc4b0b71c4d6fd4c5d57d3b22accbb1c922f77b8f4eea060fdf857e3d27f2ab4433405a3765f272bb1a7ab749547beb2ea4 5SHA512 (numba-0.45.1.tar.gz) = a35a151dce050e0b90420d2ce073687e5ee069255a1a8c2ef6df2a0e16c4540215ce7bc1f0d8081558fa6abb8e8c786ed35903d345ac209c95d4a0d947045e46
6Size (numba-0.44.1.tar.gz) = 1692943 bytes 6Size (numba-0.45.1.tar.gz) = 1782845 bytes
7SHA1 (patch-numba_npyufunc_workqueue.c) = 0bcbeff869174265a2d776f847e880a99676d812 7SHA1 (patch-numba_npyufunc_workqueue.c) = 0bcbeff869174265a2d776f847e880a99676d812