Index: head/math/py-numexpr/Makefile
===================================================================
--- head/math/py-numexpr/Makefile	(revision 398617)
+++ head/math/py-numexpr/Makefile	(revision 398618)
@@ -1,28 +1,25 @@
 # Created by: Ju Pengfei <ju.pengfei@gmail.com>
 # $FreeBSD$
 
 PORTNAME=	numexpr
-PORTVERSION=	2.4
-DISTVERSIONPREFIX=	v
-PORTREVISION=	1
+PORTVERSION=	2.4.4
 CATEGORIES=	math python
+MASTER_SITES=	CHEESESHOP
 PKGNAMEPREFIX=	${PYTHON_PKGNAMEPREFIX}
 
 MAINTAINER=	sunpoet@FreeBSD.org
 COMMENT=	Fast numerical array expression evaluator for Python and NumPy
 
 LICENSE=	MIT
+LICENSE_FILE=	${WRKSRC}/LICENSE.txt
 
 BUILD_DEPENDS=	${PYNUMPY}
 RUN_DEPENDS:=	${BUILD_DEPENDS}
 
 USE_PYTHON=	autoplist concurrent distutils
 USES=		python
-
-GH_ACCOUNT=	pydata
-USE_GITHUB=	yes
 
 post-install:
 	${STRIP_CMD} ${STAGEDIR}${PYTHON_SITELIBDIR}/numexpr/interpreter.so
 
 .include <bsd.port.mk>
Index: head/math/py-numexpr/distinfo
===================================================================
--- head/math/py-numexpr/distinfo	(revision 398617)
+++ head/math/py-numexpr/distinfo	(revision 398618)
@@ -1,2 +1,2 @@
-SHA256 (pydata-numexpr-v2.4_GH0.tar.gz) = b3d5f998d1e489c6e3e672d75c2e6b4a871d67fefc6b6154b90795010bee14c0
-SIZE (pydata-numexpr-v2.4_GH0.tar.gz) = 89752
+SHA256 (numexpr-2.4.4.tar.gz) = dfa2fad1af040e93a8022fbe4437f2183bf80e5f64d466381ad589308a73565b
+SIZE (numexpr-2.4.4.tar.gz) = 87133
Index: head/math/py-numexpr/pkg-descr
===================================================================
--- head/math/py-numexpr/pkg-descr	(revision 398617)
+++ head/math/py-numexpr/pkg-descr	(revision 398618)
@@ -1,16 +1,17 @@
-numexpr - Fast numerical array expression evaluator for Python and NumPy. 
+numexpr - Fast numerical array expression evaluator for Python and NumPy.
 
 The numexpr package evaluates multiple-operator array expressions many times
 faster than NumPy can. It accepts the expression as a string, analyzes it,
 rewrites it more efficiently, and compiles it to faster Python code on the fly.
-It's the next best thing to writing the expression in C and compiling it with
-a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler
-at runtime.  
+It's the next best thing to writing the expression in C and compiling it with a
+specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at
+runtime.
 
 Also, numexpr has support for the Intel VML (Vector Math Library) -- integrated
 in Intel MKL (Math Kernel Library) --, allowing nice speed-ups when computing
 transcendental functions (like trigonometrical, exponentials...) on top of
 Intel-compatible platforms. This support also allows to use multiple cores in
-your computations. 
+your computations.
 
+WWW: https://pypi.python.org/pypi/numexpr
 WWW: https://github.com/pydata/numexpr