| Version | EAPI | Keywords | Slot |
|---|---|---|---|
| 0.2.4.1 | 8 | ~amd64 ~x86 | 0 |
# automatically generated by g-sorcery
# please do not edit this file
EAPI=8
REALNAME="${PN}"
LITERALNAME="${PN}"
REALVERSION="${PV}"
DIGEST_SOURCES="yes"
PYTHON_COMPAT=( python{3_11,3_12,3_13,3_14} )
DISTUTILS_USE_PEP517=standalone
inherit python-r1 gs-pypi
DESCRIPTION="Combinaison of ML models for binary classification. Academic Project."
HOMEPAGE="https://github.com/g0bel1n/TinyAutoML"
LICENSE="MIT"
SRC_URI="https://files.pythonhosted.org/packages/source/${REALNAME::1}/${REALNAME}/${REALNAME}-${REALVERSION}.tar.gz"
SOURCEFILE="${REALNAME}-${REALVERSION}.tar.gz"
RESTRICT="test"
SLOT="0"
KEYWORDS="~amd64 ~x86"
IUSE=""
DEPENDENCIES="dev-python/pandas[${PYTHON_USEDEP}]
dev-python/scikit-learn[${PYTHON_USEDEP}]
dev-python/tqdm[${PYTHON_USEDEP}]
dev-python/numpy[${PYTHON_USEDEP}]
dev-python/statsmodels[${PYTHON_USEDEP}]
dev-python/matplotlib[${PYTHON_USEDEP}]
dev-python/xgboost[${PYTHON_USEDEP}]"
BDEPEND="${DEPENDENCIES}"
RDEPEND="${DEPENDENCIES}"
dev-python/pandas[${PYTHON_USEDEP}]
dev-python/scikit-learn[${PYTHON_USEDEP}]
dev-python/tqdm[${PYTHON_USEDEP}]
dev-python/numpy[${PYTHON_USEDEP}]
dev-python/statsmodels[${PYTHON_USEDEP}]
dev-python/matplotlib[${PYTHON_USEDEP}]
dev-python/xgboost[${PYTHON_USEDEP}]
dev-python/pandas[${PYTHON_USEDEP}]
dev-python/scikit-learn[${PYTHON_USEDEP}]
dev-python/tqdm[${PYTHON_USEDEP}]
dev-python/numpy[${PYTHON_USEDEP}]
dev-python/statsmodels[${PYTHON_USEDEP}]
dev-python/matplotlib[${PYTHON_USEDEP}]
dev-python/xgboost[${PYTHON_USEDEP}]
| Type | File | Size | Source URLs |
|---|---|---|---|
| DIST | TinyAutoML-0.2.4.1.tar.gz | 14505 bytes | https://files.pythonhosted.org/packages/source/${REALNAME::1}/TinyAutoML/TinyAutoML-0.2.4.1.tar.gz |