push sheeet

pkgs/development/python-modules/mlxtend/0001-StackingCVClassifier-fit-ensure-compatibility-with-s.patch

@@ -0,0 +1,80 @@
+From 1fb59eb42f4bef229b953de313c7e78f0857ea42 Mon Sep 17 00:00:00 2001
+From: Philip Wilk <p.wilk@student.reading.ac.uk>
+Date: Sun, 23 Mar 2025 16:14:51 +0000
+Subject: [PATCH] StackingCVClassifier/fit: ensure compatibility with
+ *scikit-learn* versions 1.4 and above by dynamically selecting between
+ `fit_params` and `params`
+
+---
+ mlxtend/classifier/stacking_cv_classification.py | 5 ++++-
+ mlxtend/regressor/stacking_cv_regression.py      | 6 +++++-
+ 2 files changed, 9 insertions(+), 2 deletions(-)
+
+diff --git a/mlxtend/classifier/stacking_cv_classification.py b/mlxtend/classifier/stacking_cv_classification.py
+index 5bff6907..f4c45b8c 100644
+--- a/mlxtend/classifier/stacking_cv_classification.py
++++ b/mlxtend/classifier/stacking_cv_classification.py
+@@ -15,6 +15,7 @@ from sklearn.base import TransformerMixin, clone
+ from sklearn.model_selection import cross_val_predict
+ from sklearn.model_selection._split import check_cv
+ from sklearn.preprocessing import LabelEncoder
++from sklearn import __version__ as sklearn_version
+ 
+ from ..externals.estimator_checks import check_is_fitted
+ from ..externals.name_estimators import _name_estimators
+@@ -266,6 +267,8 @@ class StackingCVClassifier(
+             if self.verbose > 1:
+                 print(_name_estimators((model,))[0][1])
+ 
++            param_name = "fit_params" if sklearn_version < "1.4" else "params"
++
+             prediction = cross_val_predict(
+                 model,
+                 X,
+@@ -273,10 +276,10 @@ class StackingCVClassifier(
+                 groups=groups,
+                 cv=final_cv,
+                 n_jobs=self.n_jobs,
+-                fit_params=fit_params,
+                 verbose=self.verbose,
+                 pre_dispatch=self.pre_dispatch,
+                 method="predict_proba" if self.use_probas else "predict",
++                **{param_name: fit_params},
+             )
+ 
+             if not self.use_probas:
+diff --git a/mlxtend/regressor/stacking_cv_regression.py b/mlxtend/regressor/stacking_cv_regression.py
+index a1faf2ff..d2fb1c49 100644
+--- a/mlxtend/regressor/stacking_cv_regression.py
++++ b/mlxtend/regressor/stacking_cv_regression.py
+@@ -19,6 +19,7 @@ from sklearn.base import RegressorMixin, TransformerMixin, clone
+ from sklearn.model_selection import cross_val_predict
+ from sklearn.model_selection._split import check_cv
+ from sklearn.utils import check_X_y
++from sklearn import __version__ as sklearn_version
+ 
+ from ..externals.estimator_checks import check_is_fitted
+ from ..externals.name_estimators import _name_estimators
+@@ -211,6 +212,9 @@ class StackingCVRegressor(_BaseXComposition, RegressorMixin, TransformerMixin):
+             fit_params = None
+         else:
+             fit_params = dict(sample_weight=sample_weight)
++
++        param_name = "fit_params" if sklearn_version < "1.4" else "params"
++
+         meta_features = np.column_stack(
+             [
+                 cross_val_predict(
+@@ -221,8 +225,8 @@ class StackingCVRegressor(_BaseXComposition, RegressorMixin, TransformerMixin):
+                     cv=kfold,
+                     verbose=self.verbose,
+                     n_jobs=self.n_jobs,
+-                    fit_params=fit_params,
+                     pre_dispatch=self.pre_dispatch,
++                    **{param_name: fit_params},
+                 )
+                 for regr in self.regr_
+             ]
+-- 
+2.47.1
+

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

@@ -0,0 +1,75 @@
+{
+  lib,
+  buildPythonPackage,
+  fetchFromGitHub,
+  isPy27,
+  setuptools,
+  pytestCheckHook,
+  scipy,
+  numpy,
+  scikit-learn,
+  pandas,
+  matplotlib,
+  joblib,
+}:
+
+buildPythonPackage rec {
+  pname = "mlxtend";
+  version = "0.23.4";
+  pyproject = true;
+
+  disabled = isPy27;
+
+  src = fetchFromGitHub {
+    owner = "rasbt";
+    repo = "mlxtend";
+    tag = "v${version}";
+    hash = "sha256-xoAHYRmqN5SrEWlc18ntTZ6WAznBlVZdf+x5Yev3ysE=";
+  };
+
+  build-system = [ setuptools ];
+
+  dependencies = [
+    scipy
+    numpy
+    scikit-learn
+    pandas
+    matplotlib
+    joblib
+  ];
+
+  patches = [
+    # https://github.com/rasbt/mlxtend/issues/1117
+    ./0001-StackingCVClassifier-fit-ensure-compatibility-with-s.patch
+  ];
+
+  nativeCheckInputs = [ pytestCheckHook ];
+
+  pytestFlags = [ "-sv" ];
+
+  disabledTests = [
+    # Type changed in numpy2 test should be updated
+    "test_invalid_labels_1"
+    "test_default"
+    "test_nullability"
+  ];
+
+  disabledTestPaths = [
+    "mlxtend/evaluate/f_test.py" # need clean
+    "mlxtend/evaluate/tests/test_feature_importance.py" # urlopen error
+    "mlxtend/evaluate/tests/test_bias_variance_decomp.py" # keras.api._v2
+    "mlxtend/evaluate/tests/test_bootstrap_point632.py" # keras.api._v2
+    # Failing tests, most likely an upstream issue. See https://github.com/rasbt/mlxtend/issues/1117
+    "mlxtend/classifier/tests/test_ensemble_vote_classifier.py"
+    "mlxtend/classifier/tests/test_stacking_classifier.py"
+    "mlxtend/classifier/tests/test_stacking_cv_classifier.py"
+  ];
+
+  meta = {
+    description = "Library of Python tools and extensions for data science";
+    homepage = "https://github.com/rasbt/mlxtend";
+    license = lib.licenses.bsd3;
+    maintainers = with lib.maintainers; [ evax ];
+    platforms = lib.platforms.unix;
+  };
+}