Commit Graph

22 Commits

Author SHA1 Message Date
sthen
c3246a42a5 replace patch with a dep on oldest-supported-numoy, now that we have it 2022-11-26 09:58:02 +00:00
sthen
dae9f91e31 bump for MODPY_DEFAULT_VERSION_3 change 2022-11-13 15:28:39 +00:00
sthen
2206a80000 rename MODPY_PEP517 to MODPY_PYBUILD which is a bit less of a
magic-numbers name and more of a nod at the frontend we're actually
using for the build.
2022-09-13 20:56:17 +00:00
sthen
0ebbedb44b update to py3-numexpr-2.8.3 2022-08-27 18:09:57 +00:00
naddy
ab45f39af6 drop RCS Ids 2022-03-11 19:36:11 +00:00
kmos
bd85d18172 Remove obsolete uses of the TESTLIBDIR construct in favor of
MODPY_TEST_LIBDIR from the lang/python module

Fix tests for geo/py-fiona while here
2022-01-26 22:58:21 +00:00
sthen
3fb7cdbcf6 bump REVISION for switch from Python 3.8 -> 3.9 2021-11-02 00:01:35 +00:00
sthen
ecfe58d04a update to py3-numexpr-2.7.3 2021-10-26 19:01:51 +00:00
sthen
d80c418015 regen PLISTs for python ports with .so files that end up renamed due to
the EXT_SUFFIX change in Python 3.8.7
2021-01-04 14:06:26 +00:00
bket
fc8c6604a4 Drop py2-flavor
OK paco@
2020-08-10 15:30:06 +00:00
sthen
d9cfe4113e bump REVISION; python 3 default changed to 3.8 2020-07-03 21:12:24 +00:00
kmos
281a81cea2 Move testing instances using uname -r with backticks to the
better OSREV
2019-11-26 16:11:34 +00:00
kmos
20b79cf822 Move py-numexpr to using MODPY_PYTEST for testing. 2019-11-25 20:12:19 +00:00
sthen
3318ced016 replace simple PERMIT_PACKAGE_CDROM=Yes with PERMIT_PACKAGE=Yes 2019-07-12 20:46:54 +00:00
kmos
c45cd79fc7 Add RUN_DEPENDS to TEST_DEPENDS automatically for ports using the
lang/python port module. I've not yet come up with a port that
would not need this and one can always set MODPY_TESTDEP to "no"
to prevent the module from touching TEST_DEPENDS.

Idea from afresh1 who pointed out the cpan module already does this.

aja "I support this move."

OK sthen@
2019-05-15 12:04:34 +00:00
danj
7219f4e6bd Remove shadchin@ as maintainer per his request 2019-05-13 19:03:51 +00:00
sthen
d7f0752227 bump all the py3 things, _SYSTEM_VERSION didn't quite work out how
we expected and it's easier|safer to do it this way than fiddle with
pkg_add now. thanks aja for update tests with a quick bulk.
2019-04-28 20:51:26 +00:00
sthen
25f0e460f2 Add COMPILER lines to c++ ports which currently use the default. Adjust
some existing COMPILER lines with arch restrictions etc. In the usual
case this is now using "COMPILER = base-clang ports-gcc base-gcc" on
ports with c++ libraries in WANTLIB.

This is basically intended to be a noop on architectures using clang
as the system compiler, but help with other architectures where we
currently have many ports knocked out due to building with an unsuitable
compiler -

- some ports require c++11/newer so the GCC version in base that is used
on these archirtectures is too old.

- some ports have conflicts where an executable is built with one compiler
(e.g. gcc from base) but a library dependency is built with a different
one (e.g. gcc from ports), resulted in mixing incompatible libraries in the
same address space.

devel/gmp is intentionally skipped as it's on the path to building gcc -
the c++ library there is unused in ports (and not built by default upstream)
so intending to disable building gmpcxx in a future commit.
2018-10-24 14:27:57 +00:00
shadchin
fa948278d8 Update to py-numexpr 2.6.4 2018-02-23 16:45:26 +00:00
sthen
5e964ab0df bump LIBCXX/LIBECXX/COMPILER_LIBCXX ports. 2017-07-26 22:45:14 +00:00
espie
8ac47fd9c6 use COMPILER_LIBCXX where applicable 2017-07-16 19:18:47 +00:00
shadchin
d84983268e Import py-numexpr 2.6.2, ok daniel@
Numexpr is a fast numerical expression evaluator for NumPy. With it,                                                                                                   expressions that operate on arrays (like "3*a+4*b") are accelerated                                                                                                    and use less memory than doing the same calculation in Python.                                                                                                                                                                                                                                                                                In addition, its multi-threaded capabilities can make use of all your                                                                                                  cores, which may accelerate computations, most specially if they are                                                                                                   not memory-bounded (e.g. those using transcendental functions).
2017-04-23 17:45:20 +00:00