[rpms/python-imbalanced-learn] f45: Retired: Fails to install: https://forge.fedoraproject.org/releng/tickets/issues/13473

[rpms/python-imbalanced-learn] f45: Retired: Fails to install: https://forge.fedoraproject.org/releng/tickets/issues/13473

[@ 2026-08-18 13:32 UTC (permalink / raw)]

A new commit has been pushed.

Repo   : rpms/python-imbalanced-learn
Branch : f45
Commit : 78fa2817eca89c1b8aff624e5a78b5d5ceefa711
Author : Miro Hrončok <miro@hroncok.cz>
Date   : 2026-08-18T15:32:29+02:00
Stats  : +1/-355 in 9 file(s)
URL    : https://src.fedoraproject.org/rpms/python-imbalanced-learn/c/78fa2817eca89c1b8aff624e5a78b5d5ceefa711?branch=f45

Log:
Retired: Fails to install: https://forge.fedoraproject.org/releng/tickets/issues/13473

---
diff --git a/.gitignore b/.gitignore
deleted file mode 100644
index f915645..0000000
--- a/.gitignore
+++ /dev/null
@@ -1,14 +0,0 @@
-/imbalanced-learn-0.7.0.tar.gz
-/imbalanced-learn-0.8.0.tar.gz
-/imbalanced-learn-0.8.1.tar.gz
-/imbalanced-learn-0.9.0.tar.gz
-/imbalanced-learn-0.9.1.tar.gz
-/imbalanced-learn-0.10.0.tar.gz
-/imbalanced-learn-0.10.1.tar.gz
-/imbalanced-learn-0.11.0.tar.gz
-/imbalanced-learn-0.12.0.tar.gz
-/imbalanced-learn-0.12.2.tar.gz
-/imbalanced-learn-0.12.3.tar.gz
-/imbalanced-learn-0.12.4.tar.gz
-/imbalanced-learn-0.13.0.tar.gz
-/imbalanced-learn-0.14.0.tar.gz

diff --git a/.packit.yaml b/.packit.yaml
deleted file mode 100644
index e7385ed..0000000
--- a/.packit.yaml
+++ /dev/null
@@ -1,13 +0,0 @@
-upstream_project_url: https://github.com/scikit-learn-contrib/imbalanced-learn
-copy_upstream_release_description: false
- 
-jobs:
-  - job: pull_from_upstream
-    trigger: release
-    dist_git_branches:
-      - fedora-rawhide
-  - job: koji_build
-    trigger: commit
-    dist_git_branches:
-      - fedora-all
-

diff --git a/README.md b/README.md
deleted file mode 100644
index 5df60d2..0000000
--- a/README.md
+++ /dev/null
@@ -1,3 +0,0 @@
-# python-imbalanced-learn
-
-The python-imbalanced-learn package

diff --git a/README.packit b/README.packit
deleted file mode 100644
index 3ad54d6..0000000
--- a/README.packit
+++ /dev/null
@@ -1,3 +0,0 @@
-This repository is maintained by packit.
-https://packit.dev/
-The file was generated using packit 1.11.0.

diff --git a/changelog b/changelog
deleted file mode 100644
index c540373..0000000
--- a/changelog
+++ /dev/null
@@ -1,68 +0,0 @@
-* Thu Apr 27 2023 Sandro <devel@penguinpee.nl> - 0.10.1-1
-- Update to 0.10.1
-
-* Fri Jan 20 2023 Fedora Release Engineering <releng@fedoraproject.org> - 0.10.0-2
-- Rebuilt for https://fedoraproject.org/wiki/Fedora_38_Mass_Rebuild
-
-* Wed Dec 14 2022 Benjamin A. Beasley <code@musicinmybrain.net> - 0.10.0-1
-- Update to 0.10.0 (close RHBZ#2152162)
-
-* Wed Dec 14 2022 Benjamin A. Beasley <code@musicinmybrain.net> - 0.9.1-2
-- Remove bundled Sphinx extensions in %%prep
-- Confirm License is SPDX MIT
-- Drop unnecessary pytest-cov BR
-- Port to pyproject-rpm-macros
-
-* Sun Sep 11 2022 Iztok Fister Jr. <iztokf AT fedoraproject DOT org> - 0.9.1-1
-- New version - 0.9.1
-
-* Fri Jul 22 2022 Fedora Release Engineering <releng@fedoraproject.org> - 0.9.0-5
-- Rebuilt for https://fedoraproject.org/wiki/Fedora_37_Mass_Rebuild
-
-* Mon Jul 04 2022 Python Maint <python-maint@redhat.com> - 0.9.0-4
-- Rebuilt for Python 3.11
-
-* Thu Jan 27 2022 Iztok Fister Jr. <iztokf AT fedoraproject DOT org> - 0.9.0-3
-- Disable one additional test
-
-* Fri Jan 21 2022 Fedora Release Engineering <releng@fedoraproject.org> - 0.9.0-2
-- Rebuilt for https://fedoraproject.org/wiki/Fedora_36_Mass_Rebuild
-
-* Tue Jan 11 2022 Iztok Fister Jr. <iztokf AT fedoraproject DOT org> - 0.9.0-1
-- New version - 0.9.0
-
-* Wed Sep 29 2021 Iztok Fister Jr. <iztokf AT fedoraproject DOT org> - 0.8.1-1
-- New version - 0.8.1
-
-* Wed Jul 21 2021 Iztok Fister Jr. <iztokf AT fedoraproject DOT org> - 0.8.0-5
-- Install additional docs
-
-* Fri Jun 04 2021 Python Maint <python-maint@redhat.com> - 0.8.0-4
-- Rebuilt for Python 3.10
-
-* Tue Apr 20 22:59:49 CEST 2021 Robert-André Mauchin <zebob.m@gmail.com> - 0.8.0-3
-- Remove unneeded patch
-- Reenable tests
-
-* Tue Mar 23 2021 Iztok Fister Jr. <iztokf AT fedoraproject DOT org> - 0.8.0-2
-- New patch: use Fedora dependencies
-- Remove provides macro
-
-* Sat Mar 13 2021 Iztok Fister Jr. <iztokf AT fedoraproject DOT org> - 0.8.0-1
-- New version - 0.8.0
-
-* Sun Feb 14 2021 Iztok Fister Jr. <iztokf AT fedoraproject DOT org> - 0.7.0-5
-- Removing dependency generator
-- Fresh rebuilt
-
-* Wed Jan 27 2021 Fedora Release Engineering <releng@fedoraproject.org> - 0.7.0-4
-- Rebuilt for https://fedoraproject.org/wiki/Fedora_34_Mass_Rebuild
-
-* Tue Jan 19 2021 Iztok Fister Jr. <iztokf AT fedoraproject DOT org> - 0.7.0-3
-- disabling tests - too many problems with missing keras/tensorflow dependencies
-
-* Fri Jan 8 2021 Iztok Fister Jr. <iztokf AT fedoraproject DOT org> - 0.7.0-2
-- disabling one test - test_cluster_centroids_n_jobs
-
-* Sun Nov 29 2020 Iztok Fister Jr. <iztokf AT fedoraproject DOT org> - 0.7.0-1
-- Initial package

diff --git a/dead.package b/dead.package
new file mode 100644
index 0000000..d035a64
--- /dev/null
+++ b/dead.package
@@ -0,0 +1 @@
+Retired: Fails to install: https://forge.fedoraproject.org/releng/tickets/issues/13473

diff --git a/fix-scikit-learn-1.8-compat.patch b/fix-scikit-learn-1.8-compat.patch
deleted file mode 100644
index 9ad9522..0000000
--- a/fix-scikit-learn-1.8-compat.patch
+++ /dev/null
@@ -1,153 +0,0 @@
-From c263ef00c93ffbb771f95b1ba68f559cb0f862b2 Mon Sep 17 00:00:00 2001
-From: Charalampos Stratakis <cstratak@redhat.com>
-Date: Thu, 4 Dec 2025 00:22:15 +0100
-Subject: [PATCH 1/2] Fix compatibility with scikit-learn 1.8+
-
-scikit-learn 1.8.0+ removed the algorithm parameter from AdaBoostClassifier
-
-https://github.com/scikit-learn/scikit-learn/pull/32262
-
-The changes maintain compatibility with previous version of scikit-learn
----
- doc/ensemble.rst                                         | 3 +--
- examples/ensemble/plot_comparison_ensemble_classifier.py | 8 +++++++-
- imblearn/ensemble/_easy_ensemble.py                      | 6 ++++--
- 3 files changed, 12 insertions(+), 5 deletions(-)
-
-diff --git a/doc/ensemble.rst b/doc/ensemble.rst
-index e79be14d8..85524e7ef 100644
---- a/doc/ensemble.rst
-+++ b/doc/ensemble.rst
-@@ -97,8 +97,7 @@ Several methods taking advantage of boosting have been designed.
- a boosting iteration :cite:`seiffert2009rusboost`::
- 
-   >>> from imblearn.ensemble import RUSBoostClassifier
--  >>> rusboost = RUSBoostClassifier(n_estimators=200, algorithm='SAMME.R',
--  ...                               random_state=0)
-+  >>> rusboost = RUSBoostClassifier(n_estimators=200, random_state=0)
-   >>> rusboost.fit(X_train, y_train)
-   RUSBoostClassifier(...)
-   >>> y_pred = rusboost.predict(X_test)
-diff --git a/examples/ensemble/plot_comparison_ensemble_classifier.py b/examples/ensemble/plot_comparison_ensemble_classifier.py
-index 8c318e5bc..856cb3a33 100644
---- a/examples/ensemble/plot_comparison_ensemble_classifier.py
-+++ b/examples/ensemble/plot_comparison_ensemble_classifier.py
-@@ -194,10 +194,16 @@
- 
- # %%
- from sklearn.ensemble import AdaBoostClassifier
-+from sklearn.utils.fixes import parse_version
- 
- from imblearn.ensemble import EasyEnsembleClassifier, RUSBoostClassifier
-+from imblearn.utils._sklearn_compat import sklearn_version
-+
-+if sklearn_version < parse_version("1.6"):
-+    estimator = AdaBoostClassifier(n_estimators=10, algorithm="SAMME")
-+else:
-+    estimator = AdaBoostClassifier(n_estimators=10)
- 
--estimator = AdaBoostClassifier(n_estimators=10, algorithm="SAMME")
- eec = EasyEnsembleClassifier(n_estimators=10, estimator=estimator)
- eec.fit(X_train, y_train)
- y_pred_eec = eec.predict(X_test)
-diff --git a/imblearn/ensemble/_easy_ensemble.py b/imblearn/ensemble/_easy_ensemble.py
-index afd0cae22..7d5398424 100644
---- a/imblearn/ensemble/_easy_ensemble.py
-+++ b/imblearn/ensemble/_easy_ensemble.py
-@@ -226,12 +226,14 @@ def _validate_y(self, y):
-             self._sampling_strategy = self.sampling_strategy
-         return y_encoded
- 
--    def _validate_estimator(self, default=AdaBoostClassifier(algorithm="SAMME")):
-+    def _validate_estimator(self, default=None):
-         """Check the estimator and the n_estimator attribute, set the
-         `estimator_` attribute."""
-         if self.estimator is not None:
-             estimator = clone(self.estimator)
-         else:
-+            if default is None:
-+                default = self._get_estimator()
-             estimator = clone(default)
- 
-         sampler = RandomUnderSampler(
-@@ -279,7 +281,7 @@ def base_estimator_(self):
- 
-     def _get_estimator(self):
-         if self.estimator is None:
--            if parse_version("1.4") <= sklearn_version < parse_version("1.6"):
-+            if sklearn_version < parse_version("1.6"):
-                 return AdaBoostClassifier(algorithm="SAMME")
-             else:
-                 return AdaBoostClassifier()
-
-From 2685b68c3ac2d775dac3eb5ed8b1b705a4f07512 Mon Sep 17 00:00:00 2001
-From: Charalampos Stratakis <cstratak@redhat.com>
-Date: Thu, 4 Dec 2025 01:58:53 +0100
-Subject: [PATCH 2/2] Support scikit-learn 1.8+ _check_targets API change
-
-In scikit-learn 1.8, the _check_targets() function signature changed
-to accept and return sample_weight as an extra value.
-
-See: https://github.com/scikit-learn/scikit-learn/pull/31701
-
-This commit adds version checking to handle both APIs.
-
-This maintains backward compatibility with scikit-learn < 1.8.
----
- imblearn/metrics/_classification.py | 25 +++++++++++++++++++------
- 1 file changed, 19 insertions(+), 6 deletions(-)
-
-diff --git a/imblearn/metrics/_classification.py b/imblearn/metrics/_classification.py
-index 17797a9a7..a222e95a3 100644
---- a/imblearn/metrics/_classification.py
-+++ b/imblearn/metrics/_classification.py
-@@ -25,10 +25,11 @@
- from sklearn.metrics._classification import _check_targets, _prf_divide
- from sklearn.preprocessing import LabelEncoder
- from sklearn.utils._param_validation import Interval, StrOptions
-+from sklearn.utils.fixes import parse_version
- from sklearn.utils.multiclass import unique_labels
- from sklearn.utils.validation import check_consistent_length, column_or_1d
- 
--from ..utils._sklearn_compat import validate_params
-+from ..utils._sklearn_compat import sklearn_version, validate_params
- 
- 
- @validate_params(
-@@ -166,7 +167,12 @@ def sensitivity_specificity_support(
-     if average not in average_options and average != "binary":
-         raise ValueError("average has to be one of " + str(average_options))
- 
--    y_type, y_true, y_pred = _check_targets(y_true, y_pred)
-+    if sklearn_version >= parse_version("1.8"):
-+        y_type, y_true, y_pred, sample_weight = _check_targets(
-+            y_true, y_pred, sample_weight
-+        )
-+    else:
-+        y_type, y_true, y_pred = _check_targets(y_true, y_pred)
-     present_labels = unique_labels(y_true, y_pred)
- 
-     if average == "binary":
-@@ -1119,11 +1125,18 @@ def macro_averaged_mean_absolute_error(y_true, y_pred, *, sample_weight=None):
-     >>> macro_averaged_mean_absolute_error(y_true_imbalanced, y_pred)
-     0.16...
-     """
--    _, y_true, y_pred = _check_targets(y_true, y_pred)
--    if sample_weight is not None:
--        sample_weight = column_or_1d(sample_weight)
-+    if sklearn_version >= parse_version("1.8"):
-+        _, y_true, y_pred, sample_weight = _check_targets(
-+            y_true, y_pred, sample_weight
-+        )
-+        if sample_weight is None:
-+            sample_weight = np.ones(y_true.shape)
-     else:
--        sample_weight = np.ones(y_true.shape)
-+        _, y_true, y_pred = _check_targets(y_true, y_pred)
-+        if sample_weight is not None:
-+            sample_weight = column_or_1d(sample_weight)
-+        else:
-+            sample_weight = np.ones(y_true.shape)
-     check_consistent_length(y_true, y_pred, sample_weight)
-     labels = unique_labels(y_true, y_pred)
-     mae = []

diff --git a/python-imbalanced-learn.spec b/python-imbalanced-learn.spec
deleted file mode 100644
index afafd20..0000000
--- a/python-imbalanced-learn.spec
+++ /dev/null
@@ -1,100 +0,0 @@
-%bcond tests 1
-
-Name:           python-imbalanced-learn
-Version:        0.14.0
-Release:        %autorelease
-Summary:        A Python Package to Tackle the Imbalanced Datasets in Machine Learning
-
-%global forgeurl https://github.com/scikit-learn-contrib/imbalanced-learn
-%global tag %{version}
-%forgemeta
-
-# The entire source is (SPDX) MIT; some other licenses are mentioned in
-# doc/sphinxext/LICENSE.txt, but the code to which they apply does not seem to
-# be present, and the directory is removed in %%prep anyway.
-License:        MIT
-URL:            %forgeurl
-Source:         %forgesource
-
-# Fix compatibility with scikit-learn 1.8+
-# Sent upstream: https://github.com/scikit-learn-contrib/imbalanced-learn/pull/1152
-Patch:          fix-scikit-learn-1.8-compat.patch
-
-BuildArch:      noarch
-
-BuildRequires:  python3-devel
-BuildRequires:  tomcli
-
-# tests
-BuildRequires:  python3dist(pytest)
-BuildRequires:  python3dist(pytest-xdist)
-# Dependencies such as pytest-cov, flake8, black, and mypy are omitted:
-# https://docs.fedoraproject.org/en-US/packaging-guidelines/Python/#_linters
-
-%global _description %{expand:
-imbalanced-learn is a python package offering a number of re-sampling
-techniques commonly used in datasets showing strong between-class imbalance. It
-is compatible with scikit-learn and is part of scikit-learn-contrib projects.}
-
-%description %_description
-
-
-%package -n python3-imbalanced-learn
-Summary:        %{summary}
-
-%description -n python3-imbalanced-learn %_description
-
-%pyproject_extras_subpkg -n python3-imbalanced-learn optional
-
-
-%prep
-%forgeautosetup -p1
-
-# Remove the bundled Sphinx extensions. We don’t build the documentation, so we
-# don’t need to make an effort to unbundle them.
-rm -vrf doc/sphinxext/
-
-# Remove obsolete sklearn-compat dependency. Upstream dropped it post
-# release and it's not packaged for Fedora.
-# https://github.com/scikit-learn-contrib/imbalanced-learn/commit/e511ddbf44f819f3777a2689eb7a87e77bf2a0e5
-sed -i '/sklearn-compat/d' pyproject.toml
-
-# Erroring on these warnings is too strict for downstream packaging.
-tomcli set pyproject.toml lists delitem \
-    tool.pytest.ini_options.filterwarnings \
-    'error::(Deprecation|Future)Warning'
-
-
-%generate_buildrequires
-%pyproject_buildrequires -x optional
-
-
-%build
-%pyproject_wheel
-
-
-%install
-%pyproject_install
-%pyproject_save_files -l imblearn
-
-
-%if %{with tests}
-%check
-# some tests are skipped, because of keras and tensorflow deps
-k="${k-}${k+ and }not test_all_estimators"
-k="${k-}${k+ and }not test_classification_report_imbalanced_multiclass_with_unicode_label"
-k="${k-}${k+ and }not test_rusboost"
-k="${k-}${k+ and }not test_cluster_centroids_n_jobs"
-k="${k-}${k+ and }not test_fit_docstring"
-k="${k-}${k+ and }not keras"
-k="${k-}${k+ and }not test_function_sampler_validate"
-%pytest -v "${k+-k $k}" imblearn
-%endif
-
-
-%files -n python3-imbalanced-learn -f %{pyproject_files}
-%doc README.rst examples/
-
-
-%changelog
-%autochangelog

diff --git a/sources b/sources
deleted file mode 100644
index 56a0b98..0000000
--- a/sources
+++ /dev/null
@@ -1 +0,0 @@
-SHA512 (imbalanced-learn-0.14.0.tar.gz) = 599e7cd872b73bd2b2f86ba7550bade29e46595812d462468b1e255bf81f7da42fa41e3bbb76e7f33c75c6fb079b240128ff3f6948e2536ce2f5d2e1b22f3cee