Loading pkgs/development/python-modules/tbats/default.nix 0 → 100644 +56 −0 Original line number Diff line number Diff line { lib , buildPythonPackage , fetchFromGitHub , setuptools , numpy , pmdarima , scikit-learn , scipy , pytestCheckHook }: buildPythonPackage rec { pname = "tbats"; version = "1.1.3"; pyproject = true; src = fetchFromGitHub { owner = "intive-DataScience"; repo = "tbats"; rev = version; hash = "sha256-f6QqDq/ffbnFBZRAT6KQRlqvZZSE+Pff2/o+htVabZI="; }; nativeBuildInputs = [ setuptools ]; propagatedBuildInputs = [ numpy pmdarima scikit-learn scipy ]; nativeCheckInputs = [ pytestCheckHook ]; pytestFlagsArray = [ # test_R folder is just for comparison of results with R lib # we need only test folder "test/" # several tests has same name, so we use --deselect instead of disableTests # Test execution is too long > 15 min "--deselect=test/tbats/TBATS_test.py::TestTBATS::test_fit_predict_trigonometric_seasonal" ]; pythonImportsCheck = [ "tbats" ]; meta = with lib; { description = "BATS and TBATS forecasting methods"; homepage = "https://github.com/intive-DataScience/tbats"; changelog = "https://github.com/intive-DataScience/tbats/releases/tag/${src.rev}"; license = licenses.mit; maintainers = with maintainers; [ mbalatsko ]; }; } pkgs/top-level/python-packages.nix +2 −0 Original line number Diff line number Diff line Loading @@ -12782,6 +12782,8 @@ self: super: with self; { taxi = callPackage ../development/python-modules/taxi { }; tbats = callPackage ../development/python-modules/tbats { }; tblib = callPackage ../development/python-modules/tblib { }; tblite = callPackage ../development/libraries/science/chemistry/tblite/python.nix { Loading Loading
pkgs/development/python-modules/tbats/default.nix 0 → 100644 +56 −0 Original line number Diff line number Diff line { lib , buildPythonPackage , fetchFromGitHub , setuptools , numpy , pmdarima , scikit-learn , scipy , pytestCheckHook }: buildPythonPackage rec { pname = "tbats"; version = "1.1.3"; pyproject = true; src = fetchFromGitHub { owner = "intive-DataScience"; repo = "tbats"; rev = version; hash = "sha256-f6QqDq/ffbnFBZRAT6KQRlqvZZSE+Pff2/o+htVabZI="; }; nativeBuildInputs = [ setuptools ]; propagatedBuildInputs = [ numpy pmdarima scikit-learn scipy ]; nativeCheckInputs = [ pytestCheckHook ]; pytestFlagsArray = [ # test_R folder is just for comparison of results with R lib # we need only test folder "test/" # several tests has same name, so we use --deselect instead of disableTests # Test execution is too long > 15 min "--deselect=test/tbats/TBATS_test.py::TestTBATS::test_fit_predict_trigonometric_seasonal" ]; pythonImportsCheck = [ "tbats" ]; meta = with lib; { description = "BATS and TBATS forecasting methods"; homepage = "https://github.com/intive-DataScience/tbats"; changelog = "https://github.com/intive-DataScience/tbats/releases/tag/${src.rev}"; license = licenses.mit; maintainers = with maintainers; [ mbalatsko ]; }; }
pkgs/top-level/python-packages.nix +2 −0 Original line number Diff line number Diff line Loading @@ -12782,6 +12782,8 @@ self: super: with self; { taxi = callPackage ../development/python-modules/taxi { }; tbats = callPackage ../development/python-modules/tbats { }; tblib = callPackage ../development/python-modules/tblib { }; tblite = callPackage ../development/libraries/science/chemistry/tblite/python.nix { Loading