pkgs/development/python-modules/tbats/default.nix

   1 {
   2   lib,
   3   buildPythonPackage,
   4   fetchFromGitHub,
   5   setuptools,
   6   numpy,
   7   pmdarima,
   8   scikit-learn,
   9   scipy,
  10   pytestCheckHook,
  11 }:
  12
  13 buildPythonPackage rec {
  14   pname = "tbats";
  15   version = "1.1.3";
  16   pyproject = true;
  17
  18   src = fetchFromGitHub {
  19     owner = "intive-DataScience";
  20     repo = "tbats";
  21     rev = version;
  22     hash = "sha256-f6QqDq/ffbnFBZRAT6KQRlqvZZSE+Pff2/o+htVabZI=";
  23   };
  24
  25   nativeBuildInputs = [ setuptools ];
  26
  27   propagatedBuildInputs = [
  28     numpy
  29     pmdarima
  30     scikit-learn
  31     scipy
  32   ];
  33
  34   nativeCheckInputs = [ pytestCheckHook ];
  35   pytestFlagsArray = [
  36     # test_R folder is just for comparison of results with R lib
  37     # we need only test folder
  38     "test/"
  39
  40     # several tests has same name, so we use --deselect instead of disableTests
  41
  42     # Test execution is too long > 15 min
  43     "--deselect=test/tbats/TBATS_test.py::TestTBATS::test_fit_predict_trigonometric_seasonal"
  44   ];
  45
  46   pythonImportsCheck = [ "tbats" ];
  47
  48   meta = with lib; {
  49     description = "BATS and TBATS forecasting methods";
  50     homepage = "https://github.com/intive-DataScience/tbats";
  51     changelog = "https://github.com/intive-DataScience/tbats/releases/tag/${src.rev}";
  52     license = licenses.mit;
  53     maintainers = with maintainers; [ mbalatsko ];
  54   };
  55 }