Install this version:
emerge -a =dev-python/dask-ml-2025.1.0If this version is masked, you can unmask it using the autounmask tool or standard emerge options:
autounmask =dev-python/dask-ml-2025.1.0Or alternatively:
emerge --autounmask-write -a =dev-python/dask-ml-2025.1.0# Copyright 1999-2026 Gentoo Authors
# Distributed under the terms of the GNU General Public License v2
EAPI=8
DISTUTILS_USE_PEP517=hatchling
PYTHON_COMPAT=( python3_{12..14} )
inherit distutils-r1 pypi
DESCRIPTION="Distributed and parallel machine learning with Dask"
HOMEPAGE="
https://github.com/dask/dask-ml
https://ml.dask.org/
https://pypi.org/project/dask-ml/
"
LICENSE="BSD"
SLOT="0"
KEYWORDS="~amd64 ~arm64"
RDEPEND="
>=dev-python/dask-glm-0.2.0[${PYTHON_USEDEP}]
>=dev-python/dask-2025.1.0[${PYTHON_USEDEP}]
>=dev-python/distributed-2025.1.0[${PYTHON_USEDEP}]
>=dev-python/multipledispatch-0.4.9[${PYTHON_USEDEP}]
>=dev-python/numba-0.51.0[${PYTHON_USEDEP}]
>=dev-python/numpy-1.24.0[${PYTHON_USEDEP}]
dev-python/packaging[${PYTHON_USEDEP}]
>=dev-python/pandas-2.0[${PYTHON_USEDEP}]
>=dev-python/scikit-learn-1.6.1[${PYTHON_USEDEP}]
dev-python/scipy[${PYTHON_USEDEP}]
"
BDEPEND="dev-python/hatch-vcs[${PYTHON_USEDEP}]"
# hatch-vcs (setuptools_scm) cannot derive a version from the gitless sdist.
export SETUPTOOLS_SCM_PRETEND_VERSION="${PV}"
# Test suite spins up a distributed cluster and exercises the full ML
# matrix (xgboost, tensorflow); fragile out of tree, upstream-tested.
RESTRICT="test"
>=dev-python/dask-glm-0.2.0[] >=dev-python/dask-2025.1.0[] >=dev-python/distributed-2025.1.0[] >=dev-python/multipledispatch-0.4.9[] >=dev-python/numba-0.51.0[] >=dev-python/numpy-1.24.0[] dev-python/packaging[] >=dev-python/pandas-2.0[] >=dev-python/scikit-learn-1.6.1[] dev-python/scipy[]
dev-python/hatch-vcs[]