2020-01-28 14:59:40 +00:00
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{ lib
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, pythonOlder
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, buildPythonPackage
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, fetchPypi
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, cvxopt
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, ecos
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, multiprocess
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, numpy
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, osqp
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, scipy
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, scs
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, six
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# Check inputs
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2020-08-27 14:13:27 +01:00
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, pytestCheckHook
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2020-01-28 14:59:40 +00:00
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, nose
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}:
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buildPythonPackage rec {
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pname = "cvxpy";
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2020-10-25 09:06:51 +00:00
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version = "1.1.7";
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2020-01-28 14:59:40 +00:00
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disabled = pythonOlder "3.5";
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src = fetchPypi {
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inherit pname version;
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2020-10-25 09:06:51 +00:00
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sha256 = "330eb76e8369c360b68d9231c6eb350848e373b5952134f9bfebaed1a4c4211f";
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2020-01-28 14:59:40 +00:00
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};
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propagatedBuildInputs = [
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cvxopt
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ecos
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multiprocess
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2020-04-02 16:42:33 +01:00
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numpy
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2020-01-28 14:59:40 +00:00
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osqp
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2020-04-02 16:42:33 +01:00
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scipy
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2020-01-28 14:59:40 +00:00
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scs
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six
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];
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2020-08-27 14:13:27 +01:00
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checkInputs = [ pytestCheckHook nose ];
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pytestFlagsArray = [ "./cvxpy" ];
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# Disable the slowest benchmarking tests, cuts test time in half
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disabledTests = [
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"test_tv_inpainting"
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"test_diffcp_sdp_example"
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];
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2020-01-28 14:59:40 +00:00
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2020-04-02 16:42:33 +01:00
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meta = with lib; {
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2020-01-28 14:59:40 +00:00
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description = "A domain-specific language for modeling convex optimization problems in Python.";
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homepage = "https://www.cvxpy.org/";
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2020-04-09 22:47:27 +01:00
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downloadPage = "https://github.com/cvxgrp/cvxpy/releases";
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2020-08-27 14:13:27 +01:00
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changelog = "https://github.com/cvxgrp/cvxpy/releases/tag/v${version}";
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2020-04-02 16:42:33 +01:00
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license = licenses.asl20;
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maintainers = with maintainers; [ drewrisinger ];
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2020-01-28 14:59:40 +00:00
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};
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}
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