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mirror of https://git.FreeBSD.org/ports.git synced 2025-01-30 10:38:37 +00:00

math/py-munkres10: Remove obsoleted port

Use math/py-munkres instead.
This commit is contained in:
Po-Chuan Hsieh 2024-04-01 04:49:00 +08:00
parent 76c4e81029
commit dbed85c591
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5 changed files with 1 additions and 35 deletions

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@ -3066,3 +3066,4 @@ lang/ruby30||2024-03-31|Has expired: Please migrate to newer versions. Ruby 3.0
devel/py-pybind11210|devel/py-pybind11|2024-03-31|Remove obsoleted port. Use devel/py-pybind11 instead
devel/py-y-py|devel/py-pycrdt|2024-03-31|Remove obsoleted port. Use devel/py-pycrdt instead
devel/py-ypy-websocket|devel/py-pycrdt-websocket|2024-03-31|Remove obsoleted port. Use devel/py-pycrdt-websocket instead
math/py-munkres10|math/py-munkres|2024-03-31|Remove obsoleted port. Use math/py-munkres instead

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@ -990,7 +990,6 @@
SUBDIR += py-moarchiving
SUBDIR += py-mpmath
SUBDIR += py-munkres
SUBDIR += py-munkres10
SUBDIR += py-ndindex
SUBDIR += py-networkx
SUBDIR += py-nevergrad

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@ -1,25 +0,0 @@
PORTNAME= munkres
PORTVERSION= 1.0.12
DISTVERSIONPREFIX= release-
CATEGORIES= math python
PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX}
PKGNAMESUFFIX= 10
MAINTAINER= sunpoet@FreeBSD.org
COMMENT= Munkres implementation for Python
WWW= https://software.clapper.org/munkres/
LICENSE= APACHE20
USES= python
USE_PYTHON= autoplist concurrent distutils
NO_ARCH= yes
# munkres 1.1.1+ requires Python 3.5+
PORTSCOUT= limit:^1\.0\.
GH_ACCOUNT= bmc
USE_GITHUB= yes
.include <bsd.port.mk>

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@ -1,3 +0,0 @@
TIMESTAMP = 1548177176
SHA256 (bmc-munkres-release-1.0.12_GH0.tar.gz) = 70b3b32b4fed3b354e5c42e4d1273880a33a13ab8c108a4247140eb661767a0b
SIZE (bmc-munkres-release-1.0.12_GH0.tar.gz) = 12126

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@ -1,6 +0,0 @@
The Munkres module provides an implementation of the Munkres algorithm (also
called the Hungarian algorithm or the Kuhn-Munkres algorithm). The algorithm
models an assignment problem as an NxM cost matrix, where each element
represents the cost of assigning the ith worker to the jth job, and it figures
out the least-cost solution, choosing a single item from each row and column in
the matrix, such that no row and no column are used more than once.