| Version | EAPI | Keywords | Slot |
|---|---|---|---|
| 1.3.1 | 8 | ~amd64 ~x86 | 0 |
# automatically generated by g-sorcery
# please do not edit this file
EAPI=8
REALNAME="${PN}"
LITERALNAME="${PN}"
REALVERSION="${PV}"
DIGEST_SOURCES="yes"
PYTHON_COMPAT=( python{3_11,3_12,3_13,3_14} )
DISTUTILS_USE_PEP517=standalone
inherit python-r1 gs-pypi
DESCRIPTION="vtreat is a pandas.DataFrame processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner."
HOMEPAGE="https://github.com/WinVector/pyvtreat"
LICENSE="License :: OSI Approved :: BSD 3-clause License"
SRC_URI="https://files.pythonhosted.org/packages/source/${REALNAME::1}/${REALNAME}/${REALNAME}-${REALVERSION}.tar.gz"
SOURCEFILE="${REALNAME}-${REALVERSION}.tar.gz"
RESTRICT="test"
SLOT="0"
KEYWORDS="~amd64 ~x86"
IUSE="all db-adapter"
DEPENDENCIES="<dev-python/numpy-2.0[${PYTHON_USEDEP}]
<dev-python/pandas-3.0[${PYTHON_USEDEP}]
<dev-python/scipy-2.0[${PYTHON_USEDEP}]
<dev-python/scikit-learn-2.0[${PYTHON_USEDEP}]
all? ( dev-python/data-algebra[${PYTHON_USEDEP}] )
db-adapter? ( dev-python/data-algebra[${PYTHON_USEDEP}] )"
BDEPEND="${DEPENDENCIES}"
RDEPEND="${DEPENDENCIES}"
<dev-python/numpy-2.0[${PYTHON_USEDEP}]
<dev-python/pandas-3.0[${PYTHON_USEDEP}]
<dev-python/scipy-2.0[${PYTHON_USEDEP}]
<dev-python/scikit-learn-2.0[${PYTHON_USEDEP}]
all? ( dev-python/data-algebra[${PYTHON_USEDEP}] )
db-adapter? ( dev-python/data-algebra[${PYTHON_USEDEP}] )
<dev-python/numpy-2.0[${PYTHON_USEDEP}]
<dev-python/pandas-3.0[${PYTHON_USEDEP}]
<dev-python/scipy-2.0[${PYTHON_USEDEP}]
<dev-python/scikit-learn-2.0[${PYTHON_USEDEP}]
all? ( dev-python/data-algebra[${PYTHON_USEDEP}] )
db-adapter? ( dev-python/data-algebra[${PYTHON_USEDEP}] )
| Type | File | Size | Source URLs |
|---|---|---|---|
| DIST | vtreat-1.3.1.tar.gz | 56806 bytes | https://files.pythonhosted.org/packages/source/${REALNAME::1}/vtreat/vtreat-1.3.1.tar.gz |