# -*- coding: utf-8; mode: tcl; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- vim:fenc=utf-8:ft=tcl:et:sw=4:ts=4:sts=4
# $Id$

PortSystem          1.0
PortGroup           python 1.0

name                py-dask
version             0.11.1
revision            0
categories-append   devel
platforms           darwin
license             BSD
supported_archs     noarch

python.versions     27 34 35

maintainers         stromnov openmaintainer

description         Minimal task scheduling abstraction.

long_description    Dask provides multi-core execution on larger-than-memory \
                    datasets using blocked algorithms and task scheduling. \
                    It maps high-level NumPy, Pandas, and list operations on \
                    large datasets on to many operations on small in-memory \
                    datasets. It then executes these graphs in parallel on a \
                    single machine. Dask lets us use traditional NumPy, \
                    Pandas, and list programming while operating on \
                    inconveniently large data in a small amount of space.

homepage            http://github.com/dask/dask/
master_sites        pypi:[string index ${python.rootname} 0]/${python.rootname}

distname            ${python.rootname}-${version}

checksums           rmd160  e13c8b5a612ff14b7b307fe50491d4ea786b5353 \
                    sha256  1d2d6d2c59aef19323ac840992cb89298876bc148c45bb54d5484643cc1340d7

if {${name} ne ${subport}} {
    depends_build-append \
                        port:py${python.version}-setuptools

    livecheck.type      none
} else {
    livecheck.type      pypi
}