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{ lib
, buildPythonPackage
, fetchFromGitHub
, pythonOlder
# build inputs
, networkx
, numpy
, scipy
, scikit-learn
, pandas
, pyparsing
, torch
, statsmodels
, tqdm
, joblib
, opt-einsum
# check inputs
, pytestCheckHook
, pytest-cov
, coverage
, mock
, black
}:
let
pname = "pgmpy";
version = "0.1.24";
# optional-dependencies = {
# all = [ daft ];
# };
in
buildPythonPackage {
inherit pname version;
format = "setuptools";
disabled = pythonOlder "3.7";
src = fetchFromGitHub {
owner = "pgmpy";
repo = pname;
rev = "refs/tags/v${version}";
hash = "sha256-IMlo4SBxO9sPoZl0rQGc3FcvvIN/V/WZz+1BD7aBfzs=";
};
propagatedBuildInputs = [
networkx
numpy
scipy
scikit-learn
pandas
pyparsing
torch
statsmodels
tqdm
joblib
opt-einsum
];
disabledTests = [
"test_to_daft" # requires optional dependency daft
];
nativeCheckInputs = [
pytestCheckHook
# xdoctest
pytest-cov
coverage
mock
black
];
meta = with lib; {
description = "Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks";
homepage = "https://github.com/pgmpy/pgmpy";
changelog = "https://github.com/pgmpy/pgmpy/releases/tag/v${version}";
license = licenses.mit;
maintainers = with maintainers; [ happysalada ];
};
}
|