Date: Thu, 18 Apr 2019 18:00:53 +0000 (UTC) From: Sunpoet Po-Chuan Hsieh <sunpoet@FreeBSD.org> To: ports-committers@freebsd.org, svn-ports-all@freebsd.org, svn-ports-head@freebsd.org Subject: svn commit: r499298 - head/science/py-pyteomics Message-ID: <201904181800.x3II0r9E083365@repo.freebsd.org>
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Author: sunpoet Date: Thu Apr 18 18:00:52 2019 New Revision: 499298 URL: https://svnweb.freebsd.org/changeset/ports/499298 Log: Update to 4.1 - Update pkg-descr - Update WWW - Take maintainership Changes: https://pyteomics.readthedocs.io/en/latest/changelog.html Modified: head/science/py-pyteomics/Makefile head/science/py-pyteomics/distinfo head/science/py-pyteomics/pkg-descr Modified: head/science/py-pyteomics/Makefile ============================================================================== --- head/science/py-pyteomics/Makefile Thu Apr 18 18:00:47 2019 (r499297) +++ head/science/py-pyteomics/Makefile Thu Apr 18 18:00:52 2019 (r499298) @@ -1,13 +1,12 @@ # $FreeBSD$ PORTNAME= pyteomics -PORTVERSION= 3.5.1 -PORTREVISION= 1 +PORTVERSION= 4.1 CATEGORIES= science python MASTER_SITES= CHEESESHOP PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX} -MAINTAINER= ports@FreeBSD.org +MAINTAINER= sunpoet@FreeBSD.org COMMENT= Python modules for proteomics data analysis LICENSE= APACHE20 @@ -15,10 +14,13 @@ LICENSE_FILE= ${WRKSRC}/LICENSE RUN_DEPENDS= ${PYTHON_PKGNAMEPREFIX}lxml>=0:devel/py-lxml@${PY_FLAVOR} \ ${PYTHON_PKGNAMEPREFIX}matplotlib>=0:math/py-matplotlib@${PY_FLAVOR} \ - ${PYNUMPY} + ${PYNUMPY} \ + ${PYTHON_PKGNAMEPREFIX}pandas>=0:math/py-pandas@${PY_FLAVOR} \ + ${PYTHON_PKGNAMEPREFIX}sqlalchemy13>=0:databases/py-sqlalchemy13@${PY_FLAVOR} USES= python -USE_PYTHON= autoplist distutils +USE_PYTHON= autoplist concurrent distutils + NO_ARCH= yes .include <bsd.port.mk> Modified: head/science/py-pyteomics/distinfo ============================================================================== --- head/science/py-pyteomics/distinfo Thu Apr 18 18:00:47 2019 (r499297) +++ head/science/py-pyteomics/distinfo Thu Apr 18 18:00:52 2019 (r499298) @@ -1,3 +1,3 @@ -TIMESTAMP = 1543441181 -SHA256 (pyteomics-3.5.1.tar.gz) = acd95d8e139e42c113f3f0bc4f512b9a7081d94eefd5bd73e183e1b4a848c364 -SIZE (pyteomics-3.5.1.tar.gz) = 184709 +TIMESTAMP = 1555592418 +SHA256 (pyteomics-4.1.tar.gz) = d7eaa5a1c6f25a39a42c4846e8c39e23cd3ba6f1aeeeedb730c3911c82bf6633 +SIZE (pyteomics-4.1.tar.gz) = 209776 Modified: head/science/py-pyteomics/pkg-descr ============================================================================== --- head/science/py-pyteomics/pkg-descr Thu Apr 18 18:00:47 2019 (r499297) +++ head/science/py-pyteomics/pkg-descr Thu Apr 18 18:00:52 2019 (r499298) @@ -1,16 +1,21 @@ -Pyteomics is a collection of lightweight and handy tools for Python -that help to handle various sorts of proteomics data. Pyteomics -provides a growing set of modules to facilitate the most common -tasks in proteomics data analysis, such as: +Pyteomics is a collection of lightweight and handy tools for Python that help to +handle various sorts of proteomics data. Pyteomics provides a growing set of +modules to facilitate the most common tasks in proteomics data analysis, such +as: +- calculation of basic physico-chemical properties of polypeptides: + - mass and isotopic distribution + - charge and pI + - chromatographic retention time +- access to common proteomics data: + - MS or LC-MS data + - FASTA databases + - search engines output +- easy manipulation of sequences of modified peptides and proteins - * calculation of basic physico-chemical properties of polypeptides: - . mass and isotopic distribution - . charge and pI - . chromatographic retention time - * access to common proteomics data: - . MS or LC-MS data - . FASTA databases - . search engines output - * easy manipulation of sequences of modified peptides and proteins +The goal of the Pyteomics project is to provide a versatile, reliable and +well-documented set of open tools for the wide proteomics community. One of the +project's key features is Python itself, an open source language increasingly +popular in scientific programming. The main applications of the library are +reproducible statistical data analysis and rapid software prototyping. -WWW: https://pypi.org/project/pyteomics/ +WWW: https://pyteomics.readthedocs.io/
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