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freebsd-ports/devel/py-rbtree/Makefile

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- New port devel/py-rbtree An RBTree is a fast, balanced efficient data structure with the following properties: get O(log n) set O(log n) delete O(log n) min O(log n) max O(log n) contains O(log n) Because the worst case timing is minimal across the range of standard dict and ordered data operations it makes sense to use this when you have volatile/dynamic sorted data. In common usage its nearly as fast as the Python dict impl but has a slightly more expensive usage of the compare function as the keys are ordered and not hashed. WWW: http://www.python.org/pypi/RBTree/
2006-05-08 14:25:19 +00:00
# New ports collection makefile for: py-rbtree
# Date created: 08 Mai 2006
# Whom: Marcus Alves Grando <mnag@FreeBSD.org>
#
# $FreeBSD$
#
PORTNAME= rbtree
- Update to 0.8.0 - Fix DOCSDIR - Assign to python@FreeBSD.org Approved by: clsung (mentor)
2007-04-05 02:17:16 +00:00
PORTVERSION= 0.8.0
- New port devel/py-rbtree An RBTree is a fast, balanced efficient data structure with the following properties: get O(log n) set O(log n) delete O(log n) min O(log n) max O(log n) contains O(log n) Because the worst case timing is minimal across the range of standard dict and ordered data operations it makes sense to use this when you have volatile/dynamic sorted data. In common usage its nearly as fast as the Python dict impl but has a slightly more expensive usage of the compare function as the keys are ordered and not hashed. WWW: http://www.python.org/pypi/RBTree/
2006-05-08 14:25:19 +00:00
CATEGORIES= devel python
- Add backup MASTER_SITE - Remove contiguous blank lines Approved by: clsung (mentor)
2007-04-07 23:35:16 +00:00
MASTER_SITES= http://cheeseshop.python.org/packages/source/r/rbtree/ \
http://www.cs.nctu.edu.tw/~lwhsu/ports/distfiles/
- New port devel/py-rbtree An RBTree is a fast, balanced efficient data structure with the following properties: get O(log n) set O(log n) delete O(log n) min O(log n) max O(log n) contains O(log n) Because the worst case timing is minimal across the range of standard dict and ordered data operations it makes sense to use this when you have volatile/dynamic sorted data. In common usage its nearly as fast as the Python dict impl but has a slightly more expensive usage of the compare function as the keys are ordered and not hashed. WWW: http://www.python.org/pypi/RBTree/
2006-05-08 14:25:19 +00:00
PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX}
- Update to 0.8.0 - Fix DOCSDIR - Assign to python@FreeBSD.org Approved by: clsung (mentor)
2007-04-05 02:17:16 +00:00
DIST_SUBDIR= python
- New port devel/py-rbtree An RBTree is a fast, balanced efficient data structure with the following properties: get O(log n) set O(log n) delete O(log n) min O(log n) max O(log n) contains O(log n) Because the worst case timing is minimal across the range of standard dict and ordered data operations it makes sense to use this when you have volatile/dynamic sorted data. In common usage its nearly as fast as the Python dict impl but has a slightly more expensive usage of the compare function as the keys are ordered and not hashed. WWW: http://www.python.org/pypi/RBTree/
2006-05-08 14:25:19 +00:00
- Update to 0.8.0 - Fix DOCSDIR - Assign to python@FreeBSD.org Approved by: clsung (mentor)
2007-04-05 02:17:16 +00:00
MAINTAINER= python@FreeBSD.org
- New port devel/py-rbtree An RBTree is a fast, balanced efficient data structure with the following properties: get O(log n) set O(log n) delete O(log n) min O(log n) max O(log n) contains O(log n) Because the worst case timing is minimal across the range of standard dict and ordered data operations it makes sense to use this when you have volatile/dynamic sorted data. In common usage its nearly as fast as the Python dict impl but has a slightly more expensive usage of the compare function as the keys are ordered and not hashed. WWW: http://www.python.org/pypi/RBTree/
2006-05-08 14:25:19 +00:00
COMMENT= A fast tree with ordered data and expanded iterator support
- Needs pyrex with new python
2007-07-30 17:49:35 +00:00
BUILD_DEPENDS= pyrexc:${PORTSDIR}/devel/pyrex
- New port devel/py-rbtree An RBTree is a fast, balanced efficient data structure with the following properties: get O(log n) set O(log n) delete O(log n) min O(log n) max O(log n) contains O(log n) Because the worst case timing is minimal across the range of standard dict and ordered data operations it makes sense to use this when you have volatile/dynamic sorted data. In common usage its nearly as fast as the Python dict impl but has a slightly more expensive usage of the compare function as the keys are ordered and not hashed. WWW: http://www.python.org/pypi/RBTree/
2006-05-08 14:25:19 +00:00
USE_PYTHON= yes
- Make Python 2.5.1 the default Python version - Add significantly better support in bsd.python.mk for working with Python Eggs and the easy_install system Tested by: pointyhat runs Approved by: pav (portmgr) Most work by: perky Thanks to: pav
2007-07-30 09:42:28 +00:00
USE_PYDISTUTILS= easy_install
PYEASYINSTALL_ARCHDEP= yes
- New port devel/py-rbtree An RBTree is a fast, balanced efficient data structure with the following properties: get O(log n) set O(log n) delete O(log n) min O(log n) max O(log n) contains O(log n) Because the worst case timing is minimal across the range of standard dict and ordered data operations it makes sense to use this when you have volatile/dynamic sorted data. In common usage its nearly as fast as the Python dict impl but has a slightly more expensive usage of the compare function as the keys are ordered and not hashed. WWW: http://www.python.org/pypi/RBTree/
2006-05-08 14:25:19 +00:00
- Update to 0.8.0 - Fix DOCSDIR - Assign to python@FreeBSD.org Approved by: clsung (mentor)
2007-04-05 02:17:16 +00:00
.if !defined(NOPORTDOCS)
DOCSDIR= ${PREFIX}/share/doc/py-${PORTNAME}
- New port devel/py-rbtree An RBTree is a fast, balanced efficient data structure with the following properties: get O(log n) set O(log n) delete O(log n) min O(log n) max O(log n) contains O(log n) Because the worst case timing is minimal across the range of standard dict and ordered data operations it makes sense to use this when you have volatile/dynamic sorted data. In common usage its nearly as fast as the Python dict impl but has a slightly more expensive usage of the compare function as the keys are ordered and not hashed. WWW: http://www.python.org/pypi/RBTree/
2006-05-08 14:25:19 +00:00
PORTDOCS= *
- Update to 0.8.0 - Fix DOCSDIR - Assign to python@FreeBSD.org Approved by: clsung (mentor)
2007-04-05 02:17:16 +00:00
.endif
- Force our idea of OPSYS to get predictable egg name
2007-08-01 22:31:39 +00:00
pre-build:
@cd ${WRKSRC} && ${PYTHON_CMD} setup.py setopt -c build -o build-platlib -s lib.${PYEASYINSTALL_OSARCH:S/^-//}
@cd ${WRKSRC} && ${PYTHON_CMD} setup.py setopt -c build -o build-temp -s temp.${PYEASYINSTALL_OSARCH:S/^-//}-${PYTHON_VER}
@cd ${WRKSRC} && ${PYTHON_CMD} setup.py setopt -c bdist_egg -o plat-name -s ${PYEASYINSTALL_OSARCH:S/^-//}
@cd ${WRKSRC} && ${PYTHON_CMD} setup.py setopt -c bdist -o plat-name -s ${PYEASYINSTALL_OSARCH:S/^-//}
- New port devel/py-rbtree An RBTree is a fast, balanced efficient data structure with the following properties: get O(log n) set O(log n) delete O(log n) min O(log n) max O(log n) contains O(log n) Because the worst case timing is minimal across the range of standard dict and ordered data operations it makes sense to use this when you have volatile/dynamic sorted data. In common usage its nearly as fast as the Python dict impl but has a slightly more expensive usage of the compare function as the keys are ordered and not hashed. WWW: http://www.python.org/pypi/RBTree/
2006-05-08 14:25:19 +00:00
post-install:
.if !defined(NOPORTDOCS)
@${MKDIR} ${DOCSDIR}
${INSTALL_DATA} ${WRKSRC}/README.txt ${DOCSDIR}
.endif
test: build
(cd ${WRKSRC} && ${PYTHON_CMD} test_rbtree.py)
- Make Python 2.5.1 the default Python version - Add significantly better support in bsd.python.mk for working with Python Eggs and the easy_install system Tested by: pointyhat runs Approved by: pav (portmgr) Most work by: perky Thanks to: pav
2007-07-30 09:42:28 +00:00
.include <bsd.port.mk>
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