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{
lib,
buildPythonPackage,
fetchFromGitHub,
# build-system
hatch-vcs,
hatchling,
# dependencies
dask-glm,
distributed,
multipledispatch,
numba,
numpy,
packaging,
pandas,
scikit-learn,
scipy,
dask,
# tests
pytest-mock,
pytestCheckHook,
}:
buildPythonPackage rec {
pname = "dask-ml";
version = "2025.1.0";
pyproject = true;
src = fetchFromGitHub {
owner = "dask";
repo = "dask-ml";
tag = "v${version}";
hash = "sha256-DHxx0LFuJmGWYuG/WGHj+a5XHAEekBmlHUUb90rl2IY=";
};
build-system = [
hatch-vcs
hatchling
];
dependencies = [
dask-glm
distributed
multipledispatch
numba
numpy
packaging
pandas
scikit-learn
scipy
]
++ dask.optional-dependencies.array
++ dask.optional-dependencies.dataframe;
pythonImportsCheck = [
"dask_ml"
"dask_ml.naive_bayes"
"dask_ml.wrappers"
"dask_ml.utils"
];
nativeCheckInputs = [
pytest-mock
pytestCheckHook
];
disabledTestPaths = [
# RuntimeError: Attempting to use an asynchronous Client in a synchronous context of `dask.compute`
# https://github.com/dask/dask-ml/issues/1016
"tests/model_selection/test_hyperband.py"
"tests/model_selection/test_incremental.py"
"tests/model_selection/test_incremental_warns.py"
"tests/model_selection/test_successive_halving.py"
];
disabledTests = [
# AssertionError: Regex pattern did not match.
"test_unknown_category_transform_array"
# ValueError: cannot broadcast shape (nan,) to shape (nan,)
# https://github.com/dask/dask-ml/issues/1012
"test_fit_array"
"test_fit_frame"
"test_fit_transform_frame"
"test_laziness"
"test_lr_score"
"test_ok"
"test_scoring_string"
];
__darwinAllowLocalNetworking = true;
meta = {
description = "Scalable Machine Learn with Dask";
homepage = "https://github.com/dask/dask-ml";
license = lib.licenses.bsd3;
maintainers = with lib.maintainers; [ GaetanLepage ];
};
}
|