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Import py-numexpr 2.6.2, ok daniel@

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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).
This commit is contained in:
shadchin 2017-04-23 17:45:20 +00:00
parent ae4e50785f
commit d84983268e
4 changed files with 73 additions and 0 deletions
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33
math/py-numexpr/Makefile Normal file
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# $OpenBSD: Makefile,v 1.1.1.1 2017/04/23 17:45:20 shadchin Exp $
COMMENT = fast numerical expression evaluator for NumPy
MODPY_EGG_VERSION = 2.6.2
DISTNAME = numexpr-${MODPY_EGG_VERSION}
PKGNAME = py-${DISTNAME}
CATEGORIES = math
MAINTAINER = Alexandr Shadchin <shadchin@openbsd.org>
# MIT
PERMIT_PACKAGE_CDROM = Yes
WANTLIB += m pthread ${MODPY_WANTLIB} ${LIBCXX}
MODULES = lang/python
MODPY_PI = Yes
MODPY_SETUPTOOLS = Yes
RUN_DEPENDS = math/py-numpy${MODPY_FLAVOR}
BUILD_DEPENDS = ${RUN_DEPENDS}
TEST_DEPENDS = ${RUN_DEPENDS}
FLAVORS = python3
FLAVOR ?=
do-test: fake
PYTHONPATH=${WRKINST}${MODPY_SITEPKG} ${MODPY_BIN} -c \
"import numexpr; numexpr.test()"
.include <bsd.port.mk>

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math/py-numexpr/distinfo Normal file
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SHA256 (numexpr-2.6.2.tar.gz) = arj/XBnn9FKWa/WjIguEXPMkT+C5ZUT3+aztzC21xwU=
SIZE (numexpr-2.6.2.tar.gz) = 90970

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math/py-numexpr/pkg/DESCR Normal file
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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).

31
math/py-numexpr/pkg/PLIST Normal file
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@comment $OpenBSD: PLIST,v 1.1.1.1 2017/04/23 17:45:20 shadchin Exp $
lib/python${MODPY_VERSION}/site-packages/numexpr/
lib/python${MODPY_VERSION}/site-packages/numexpr-${MODPY_EGG_VERSION}-py${MODPY_VERSION}.egg-info/
lib/python${MODPY_VERSION}/site-packages/numexpr-${MODPY_EGG_VERSION}-py${MODPY_VERSION}.egg-info/PKG-INFO
lib/python${MODPY_VERSION}/site-packages/numexpr-${MODPY_EGG_VERSION}-py${MODPY_VERSION}.egg-info/SOURCES.txt
lib/python${MODPY_VERSION}/site-packages/numexpr-${MODPY_EGG_VERSION}-py${MODPY_VERSION}.egg-info/dependency_links.txt
lib/python${MODPY_VERSION}/site-packages/numexpr-${MODPY_EGG_VERSION}-py${MODPY_VERSION}.egg-info/not-zip-safe
lib/python${MODPY_VERSION}/site-packages/numexpr-${MODPY_EGG_VERSION}-py${MODPY_VERSION}.egg-info/requires.txt
lib/python${MODPY_VERSION}/site-packages/numexpr-${MODPY_EGG_VERSION}-py${MODPY_VERSION}.egg-info/top_level.txt
lib/python${MODPY_VERSION}/site-packages/numexpr/__config__.py
lib/python${MODPY_VERSION}/site-packages/numexpr/__init__.py
${MODPY_COMMENT}lib/python${MODPY_VERSION}/site-packages/numexpr/${MODPY_PYCACHE}/
lib/python${MODPY_VERSION}/site-packages/numexpr/${MODPY_PYCACHE}__config__.${MODPY_PYC_MAGIC_TAG}pyc
lib/python${MODPY_VERSION}/site-packages/numexpr/${MODPY_PYCACHE}__init__.${MODPY_PYC_MAGIC_TAG}pyc
lib/python${MODPY_VERSION}/site-packages/numexpr/${MODPY_PYCACHE}cpuinfo.${MODPY_PYC_MAGIC_TAG}pyc
lib/python${MODPY_VERSION}/site-packages/numexpr/${MODPY_PYCACHE}expressions.${MODPY_PYC_MAGIC_TAG}pyc
lib/python${MODPY_VERSION}/site-packages/numexpr/${MODPY_PYCACHE}necompiler.${MODPY_PYC_MAGIC_TAG}pyc
lib/python${MODPY_VERSION}/site-packages/numexpr/${MODPY_PYCACHE}utils.${MODPY_PYC_MAGIC_TAG}pyc
lib/python${MODPY_VERSION}/site-packages/numexpr/${MODPY_PYCACHE}version.${MODPY_PYC_MAGIC_TAG}pyc
lib/python${MODPY_VERSION}/site-packages/numexpr/cpuinfo.py
lib/python${MODPY_VERSION}/site-packages/numexpr/expressions.py
lib/python${MODPY_VERSION}/site-packages/numexpr/interpreter.so
lib/python${MODPY_VERSION}/site-packages/numexpr/necompiler.py
lib/python${MODPY_VERSION}/site-packages/numexpr/tests/
lib/python${MODPY_VERSION}/site-packages/numexpr/tests/__init__.py
${MODPY_COMMENT}lib/python${MODPY_VERSION}/site-packages/numexpr/tests/${MODPY_PYCACHE}/
lib/python${MODPY_VERSION}/site-packages/numexpr/tests/${MODPY_PYCACHE}__init__.${MODPY_PYC_MAGIC_TAG}pyc
lib/python${MODPY_VERSION}/site-packages/numexpr/tests/${MODPY_PYCACHE}test_numexpr.${MODPY_PYC_MAGIC_TAG}pyc
lib/python${MODPY_VERSION}/site-packages/numexpr/tests/test_numexpr.py
lib/python${MODPY_VERSION}/site-packages/numexpr/utils.py
lib/python${MODPY_VERSION}/site-packages/numexpr/version.py