Version 1.3.2

COPYING

@@ -1,6 +1,6 @@
 BSD 3-Clause License
 
-Copyright (c) 2007-2022 The scikit-learn developers.
+Copyright (c) 2007-2023 The scikit-learn developers.
 All rights reserved.
 
 Redistribution and use in source and binary forms, with or without

MANIFEST.in

@@ -22,6 +22,7 @@ recursive-exclude maint_tools *
 recursive-exclude benchmarks *
 recursive-exclude .binder *
 recursive-exclude .circleci *
+exclude .cirrus.star
 exclude .codecov.yml
 exclude .git-blame-ignore-revs
 exclude .mailmap

Makefile

@@ -61,5 +61,4 @@ doc-noplot: inplace
 	$(MAKE) -C doc html-noplot
 
 code-analysis:
-	flake8 sklearn | grep -v __init__ | grep -v external
-	pylint -E -i y sklearn/ -d E1103,E0611,E1101
+	build_tools/linting.sh

README.rst

@@ -1,23 +1,23 @@
 .. -*- mode: rst -*-
 
-|Azure|_ |Travis|_ |Codecov|_ |CircleCI|_ |Nightly wheels|_ |Black|_ |PythonVersion|_ |PyPi|_ |DOI|_ |Benchmark|_
+|Azure|_ |CirrusCI|_ |Codecov|_ |CircleCI|_ |Nightly wheels|_ |Black|_ |PythonVersion|_ |PyPi|_ |DOI|_ |Benchmark|_
 
 .. |Azure| image:: https://dev.azure.com/scikit-learn/scikit-learn/_apis/build/status/scikit-learn.scikit-learn?branchName=main
 .. _Azure: https://dev.azure.com/scikit-learn/scikit-learn/_build/latest?definitionId=1&branchName=main
 
-.. |CircleCI| image:: https://circleci.com/gh/scikit-learn/scikit-learn/tree/main.svg?style=shield&circle-token=:circle-token
+.. |CircleCI| image:: https://circleci.com/gh/scikit-learn/scikit-learn/tree/main.svg?style=shield
 .. _CircleCI: https://circleci.com/gh/scikit-learn/scikit-learn
 
-.. |Travis| image:: https://api.travis-ci.com/scikit-learn/scikit-learn.svg?branch=main
-.. _Travis: https://app.travis-ci.com/github/scikit-learn/scikit-learn
+.. |CirrusCI| image:: https://img.shields.io/cirrus/github/scikit-learn/scikit-learn/main?label=Cirrus%20CI
+.. _CirrusCI: https://cirrus-ci.com/github/scikit-learn/scikit-learn/main
 
 .. |Codecov| image:: https://codecov.io/gh/scikit-learn/scikit-learn/branch/main/graph/badge.svg?token=Pk8G9gg3y9
 .. _Codecov: https://codecov.io/gh/scikit-learn/scikit-learn
 
 .. |Nightly wheels| image:: https://github.com/scikit-learn/scikit-learn/workflows/Wheel%20builder/badge.svg?event=schedule
 .. _`Nightly wheels`: https://github.com/scikit-learn/scikit-learn/actions?query=workflow%3A%22Wheel+builder%22+event%3Aschedule
 
-.. |PythonVersion| image:: https://img.shields.io/badge/python-3.8%20%7C%203.9%20%7C%203.10-blue
+.. |PythonVersion| image:: https://img.shields.io/pypi/pyversions/scikit-learn.svg
 .. _PythonVersion: https://pypi.org/project/scikit-learn/
 
 .. |PyPi| image:: https://img.shields.io/pypi/v/scikit-learn
@@ -34,15 +34,15 @@
 
 .. |PythonMinVersion| replace:: 3.8
 .. |NumPyMinVersion| replace:: 1.17.3
-.. |SciPyMinVersion| replace:: 1.3.2
+.. |SciPyMinVersion| replace:: 1.5.0
 .. |JoblibMinVersion| replace:: 1.1.1
 .. |ThreadpoolctlMinVersion| replace:: 2.0.0
 .. |MatplotlibMinVersion| replace:: 3.1.3
 .. |Scikit-ImageMinVersion| replace:: 0.16.2
 .. |PandasMinVersion| replace:: 1.0.5
 .. |SeabornMinVersion| replace:: 0.9.0
-.. |PytestMinVersion| replace:: 5.3.1
-.. |PlotlyMinVersion| replace:: 5.10.0
+.. |PytestMinVersion| replace:: 7.1.2
+.. |PlotlyMinVersion| replace:: 5.14.0
 
 .. image:: https://raw.githubusercontent.com/scikit-learn/scikit-learn/main/doc/logos/scikit-learn-logo.png
   :target: https://scikit-learn.org/
@@ -189,7 +189,6 @@ Communication
 - Blog: https://blog.scikit-learn.org
 - Calendar: https://blog.scikit-learn.org/calendar/
 - Twitter: https://twitter.com/scikit_learn
-- Twitter (commits): https://twitter.com/sklearn_commits
 - Stack Overflow: https://stackoverflow.com/questions/tagged/scikit-learn
 - Github Discussions: https://github.com/scikit-learn/scikit-learn/discussions
 - Website: https://scikit-learn.org

SECURITY.md

@@ -4,8 +4,8 @@
 
 | Version   | Supported          |
 | --------- | ------------------ |
-| 1.1.3     | :white_check_mark: |
-| < 1.1.3   | :x:                |
+| 1.3.1     | :white_check_mark: |
+| < 1.3.1   | :x:                |
 
 ## Reporting a Vulnerability
 

asv_benchmarks/asv.conf.json

@@ -71,13 +71,17 @@
     // pip (with all the conda available packages installed first,
     // followed by the pip installed packages).
     //
+    // The versions of the dependencies should be bumped in a dedicated commit
+    // to easily identify regressions/imrovements due to code changes from
+    // those due to dependency changes.
+    //
     "matrix": {
-        "numpy": [],
-        "scipy": [],
-        "cython": [],
-        "joblib": [],
-        "threadpoolctl": [],
-        "pandas": []
+        "numpy": ["1.25.2"],
+        "scipy": ["1.11.2"],
+        "cython": ["0.29.36"],
+        "joblib": ["1.3.2"],
+        "threadpoolctl": ["3.2.0"],
+        "pandas": ["2.1.0"]
     },
 
     // Combinations of libraries/python versions can be excluded/included

asv_benchmarks/benchmarks/cluster.py

@@ -1,7 +1,7 @@
 from sklearn.cluster import KMeans, MiniBatchKMeans
 
 from .common import Benchmark, Estimator, Predictor, Transformer
-from .datasets import _blobs_dataset, _20newsgroups_highdim_dataset
+from .datasets import _20newsgroups_highdim_dataset, _blobs_dataset
 from .utils import neg_mean_inertia
 
 

asv_benchmarks/benchmarks/common.py

@@ -1,11 +1,11 @@
-import os
+import itertools
 import json
-import timeit
+import os
 import pickle
-import itertools
+import timeit
 from abc import ABC, abstractmethod
-from pathlib import Path
 from multiprocessing import cpu_count
+from pathlib import Path
 
 import numpy as np
 

asv_benchmarks/benchmarks/datasets.py

@@ -1,21 +1,22 @@
+from pathlib import Path
+
 import numpy as np
 import scipy.sparse as sp
 from joblib import Memory
-from pathlib import Path
 
-from sklearn.decomposition import TruncatedSVD
 from sklearn.datasets import (
-    make_blobs,
     fetch_20newsgroups,
+    fetch_olivetti_faces,
     fetch_openml,
     load_digits,
-    make_regression,
+    make_blobs,
     make_classification,
-    fetch_olivetti_faces,
+    make_regression,
 )
-from sklearn.preprocessing import MaxAbsScaler, StandardScaler
+from sklearn.decomposition import TruncatedSVD
 from sklearn.feature_extraction.text import TfidfVectorizer
 from sklearn.model_selection import train_test_split
+from sklearn.preprocessing import MaxAbsScaler, StandardScaler
 
 # memory location for caching datasets
 M = Memory(location=str(Path(__file__).resolve().parent / "cache"))

asv_benchmarks/benchmarks/decomposition.py

@@ -1,8 +1,8 @@
 from sklearn.decomposition import PCA, DictionaryLearning, MiniBatchDictionaryLearning
 
 from .common import Benchmark, Estimator, Transformer
-from .datasets import _olivetti_faces_dataset, _mnist_dataset
-from .utils import make_pca_scorers, make_dict_learning_scorers
+from .datasets import _mnist_dataset, _olivetti_faces_dataset
+from .utils import make_dict_learning_scorers, make_pca_scorers
 
 
 class PCABenchmark(Transformer, Estimator, Benchmark):

asv_benchmarks/benchmarks/ensemble.py

@@ -1,7 +1,7 @@
 from sklearn.ensemble import (
-    RandomForestClassifier,
     GradientBoostingClassifier,
     HistGradientBoostingClassifier,
+    RandomForestClassifier,
 )
 
 from .common import Benchmark, Estimator, Predictor

asv_benchmarks/benchmarks/linear_model.py

@@ -1,9 +1,9 @@
 from sklearn.linear_model import (
-    LogisticRegression,
-    Ridge,
     ElasticNet,
     Lasso,
     LinearRegression,
+    LogisticRegression,
+    Ridge,
     SGDRegressor,
 )
 
@@ -164,7 +164,11 @@ def make_data(self, params):
         return data
 
     def make_estimator(self, params):
-        estimator = SGDRegressor(max_iter=1000, tol=1e-16, random_state=0)
+        (representation,) = params
+
+        max_iter = 60 if representation == "dense" else 300
+
+        estimator = SGDRegressor(max_iter=max_iter, tol=None, random_state=0)
 
         return estimator