2021-01-25 09:26:54 +01:00
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{ lib
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2018-09-13 21:12:21 +02:00
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, buildPythonPackage
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, fetchPypi
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2019-12-10 09:18:07 +01:00
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, pythonOlder
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2018-09-13 21:12:21 +02:00
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, dask
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, numpy, toolz # dask[array]
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, numba
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, pandas
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, scikitlearn
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, scipy
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, dask-glm
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, six
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, multipledispatch
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, packaging
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, distributed
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}:
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buildPythonPackage rec {
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2021-02-06 06:02:14 +01:00
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version = "1.8.0";
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2018-09-13 21:12:21 +02:00
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pname = "dask-ml";
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2019-12-10 09:18:07 +01:00
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disabled = pythonOlder "3.6"; # >= 3.6
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2018-09-13 21:12:21 +02:00
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src = fetchPypi {
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inherit pname version;
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2021-02-06 06:02:14 +01:00
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sha256 = "8fc4ac3ec1915e382fb8cae9ff1ec9b5ac1bee0b6f4c6975d6e6cb7191a4a815";
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2018-09-13 21:12:21 +02:00
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};
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2019-12-10 09:18:07 +01:00
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propagatedBuildInputs = [
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dask
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dask-glm
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distributed
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multipledispatch
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numba
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numpy
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packaging
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pandas
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scikitlearn
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scipy
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six
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toolz
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];
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2018-09-13 21:12:21 +02:00
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2019-12-10 09:18:07 +01:00
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# has non-standard build from source, and pypi doesn't include tests
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2018-09-13 21:12:21 +02:00
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doCheck = false;
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2019-12-10 09:18:07 +01:00
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# in lieu of proper tests
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pythonImportsCheck = [
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"dask_ml"
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"dask_ml.naive_bayes"
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"dask_ml.wrappers"
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"dask_ml.utils"
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];
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2021-01-11 08:54:33 +01:00
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meta = with lib; {
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2020-04-01 03:11:51 +02:00
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homepage = "https://github.com/dask/dask-ml";
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2018-09-13 21:12:21 +02:00
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description = "Scalable Machine Learn with Dask";
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license = licenses.bsd3;
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maintainers = [ maintainers.costrouc ];
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};
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}
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