# Maintainer: Rich Li pkgname='python-xray' pkgver=0.6.1 pkgrel=1 pkgdesc="N-D labeled arrays and datasets in Python" url="https://pypi.python.org/pypi/xray" arch=('any') license=('Apache') makedepends=('python-setuptools') depends=('python-numpy' 'python-pandas') optdepends=('python-netcdf4: NetCDF4 support' 'python-bottleneck: Faster NaN operations' 'python-cyordereddict: Speed up most internal operations' 'python-scipy: OPeNDAP support' 'python-matplotlib: Plotting support' 'python-dask: Enable out-of-core parallel computation') checkdepends=('python-nose') #source=(https://pypi.python.org/packages/source/x/xray/xray-"$pkgver".tar.gz) # I'm using the Github source instead of the PyPI source since the Github source includes the data files used for testing source=(https://github.com/xray/xray/archive/v"$pkgver".tar.gz) md5sums=('201ef4249182771a4013e256d330bf96') sha1sums=('a4ac7c719a76bfa47ab5dec2d63af4468461754b') sha256sums=('758baad3c29a9e7f505e55314f3a05ba9cce55c2759433dabd81a58c9436abce') build() { cd "$srcdir/xray-$pkgver" python setup.py build } check() { cd "$srcdir/xray-$pkgver" nosetests } package() { cd "$srcdir/xray-$pkgver" python setup.py install --prefix=/usr --root="$pkgdir/" --optimize=1 } # vim:set ts=2 sw=2 et: