git: 7b98bdd020b1 - main - devel/py-pykdtree: Add py-pykdtree 1.3.7.post0

The branch main has been updated by sunpoet:

URL: https://cgit.FreeBSD.org/ports/commit/?id=7b98bdd020b1fa27dd7273303461332eb3010682

commit 7b98bdd020b1fa27dd7273303461332eb3010682
Author:     Po-Chuan Hsieh <sunpoet@FreeBSD.org>
AuthorDate: 2023-08-21 16:51:54 +0000
Commit:     Po-Chuan Hsieh <sunpoet@FreeBSD.org>
CommitDate: 2023-08-21 17:01:58 +0000

    devel/py-pykdtree: Add py-pykdtree 1.3.7.post0
    
    pykdtree is a kd-tree implementation for fast nearest neighbour search in
    Python. The aim is to be the fastest implementation around for common use cases
    (low dimensions and low number of neighbours) for both tree construction and
    queries.
    
    The implementation is based on scipy.spatial.cKDTree and libANN by combining the
    best features from both and focus on implementation efficiency.
    
    The interface is similar to that of scipy.spatial.cKDTree except only Euclidean
    distance measure is supported.
    
    Queries are optionally multithreaded using OpenMP.
---
 devel/Makefile              |  1 +
 devel/py-pykdtree/Makefile  | 23 +++++++++++++++++++++++
 devel/py-pykdtree/distinfo  |  3 +++
 devel/py-pykdtree/pkg-descr | 12 ++++++++++++
 4 files changed, 39 insertions(+)

diff --git a/devel/Makefile b/devel/Makefile
index 998961787754..8ed8329ce0d4 100644
--- a/devel/Makefile
+++ b/devel/Makefile
@@ -5282,6 +5282,7 @@
     SUBDIR += py-pyintelowl
     SUBDIR += py-pyjq
     SUBDIR += py-pyjsparser
+    SUBDIR += py-pykdtree
     SUBDIR += py-pylama
     SUBDIR += py-pylev
     SUBDIR += py-pylibsrtp
diff --git a/devel/py-pykdtree/Makefile b/devel/py-pykdtree/Makefile
new file mode 100644
index 000000000000..152d9fb520d2
--- /dev/null
+++ b/devel/py-pykdtree/Makefile
@@ -0,0 +1,23 @@
+PORTNAME=	pykdtree
+PORTVERSION=	1.3.7.post0
+CATEGORIES=	devel python
+MASTER_SITES=	PYPI
+PKGNAMEPREFIX=	${PYTHON_PKGNAMEPREFIX}
+
+MAINTAINER=	sunpoet@FreeBSD.org
+COMMENT=	Fast kd-tree implementation with OpenMP-enabled queries
+WWW=		https://github.com/storpipfugl/pykdtree
+
+LICENSE=	LGPL3
+LICENSE_FILE=	${WRKSRC}/LICENSE.txt
+
+BUILD_DEPENDS=	${PYTHON_PKGNAMEPREFIX}numpy>=0,1:math/py-numpy@${PY_FLAVOR}
+RUN_DEPENDS=	${PYTHON_PKGNAMEPREFIX}numpy>=0,1:math/py-numpy@${PY_FLAVOR}
+
+USES=		python
+USE_PYTHON=	autoplist concurrent distutils
+
+post-install:
+	${FIND} ${STAGEDIR}${PYTHON_SITELIBDIR} -name '*.so' -exec ${STRIP_CMD} {} +
+
+.include <bsd.port.mk>
diff --git a/devel/py-pykdtree/distinfo b/devel/py-pykdtree/distinfo
new file mode 100644
index 000000000000..16b8c479e9fc
--- /dev/null
+++ b/devel/py-pykdtree/distinfo
@@ -0,0 +1,3 @@
+TIMESTAMP = 1692211615
+SHA256 (pykdtree-1.3.7.post0.tar.gz) = eca1d61d33db621ef8027eb691ae88db9c65d196aba4b2cc90c190cb90bb508e
+SIZE (pykdtree-1.3.7.post0.tar.gz) = 84509
diff --git a/devel/py-pykdtree/pkg-descr b/devel/py-pykdtree/pkg-descr
new file mode 100644
index 000000000000..aaae7459c719
--- /dev/null
+++ b/devel/py-pykdtree/pkg-descr
@@ -0,0 +1,12 @@
+pykdtree is a kd-tree implementation for fast nearest neighbour search in
+Python. The aim is to be the fastest implementation around for common use cases
+(low dimensions and low number of neighbours) for both tree construction and
+queries.
+
+The implementation is based on scipy.spatial.cKDTree and libANN by combining the
+best features from both and focus on implementation efficiency.
+
+The interface is similar to that of scipy.spatial.cKDTree except only Euclidean
+distance measure is supported.
+
+Queries are optionally multithreaded using OpenMP.