# 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="Lo scopo di questa libreria è fornire uno strumento completo per il rilascio di modelli predittivi basati su serie temporali nell'ambito della Telemedicina, al fine di supportare la gestione e la pianificazione delle attività sulla Piattaforma Nazionale di Telemedicina (PNT)"

HOMEPAGE=""
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=""
DEPENDENCIES="dev-python/dtaidistance[${PYTHON_USEDEP}]
	dev-python/geopandas[${PYTHON_USEDEP}]
	dev-python/hierarchicalforecast[${PYTHON_USEDEP}]
	dev-python/holidays[${PYTHON_USEDEP}]
	~dev-python/matplotlib-3.7.1[${PYTHON_USEDEP}]
	dev-python/mlflow[${PYTHON_USEDEP}]
	~dev-python/pandas-2.0.0[${PYTHON_USEDEP}]
	~dev-python/plotly-5.14.1[${PYTHON_USEDEP}]
	dev-python/prophet[${PYTHON_USEDEP}]
	~dev-python/scikit-learn-1.2.2[${PYTHON_USEDEP}]
	~dev-python/scipy-1.11.1[${PYTHON_USEDEP}]
	~dev-python/seaborn-0.12.2[${PYTHON_USEDEP}]
	~dev-python/statsmodels-0.14.0[${PYTHON_USEDEP}]
	dev-python/streamlit[${PYTHON_USEDEP}]
	~dev-python/tabulate-0.9.0[${PYTHON_USEDEP}]
	~dev-python/tomli-2.0.1[${PYTHON_USEDEP}]
	~dev-python/typing-extensions-4.7.1[${PYTHON_USEDEP}]
	dev-python/xgboost[${PYTHON_USEDEP}]
	dev-python/fastparquet[${PYTHON_USEDEP}]
	dev-python/telemedbasics[${PYTHON_USEDEP}]"
BDEPEND="${DEPENDENCIES}"
RDEPEND="${DEPENDENCIES}"