Remove unused imports in private modules and provide tool script

.gitignore

@@ -357,6 +357,9 @@ MigrationBackup/
 # Python virtual environment
 .venv
 
+# Lock files (like uv.lock)
+*.lock
+
 # Build files from utils
 .eggs
 *.egg-info

pyproject.toml

@@ -112,7 +112,7 @@ extra-standard-library = [
 ]
 
 [tool.pyright]
-exclude = ["build", ".git"]
+exclude = ["build", ".git", ".venv*"]
 stubPath = "./stubs"
 pythonversion = "3.9" # Target oldest supported Python version
 typeCheckingMode = "standard"

stubs/skimage/_shared/coord.pyi

@@ -1,6 +1,3 @@
-import numpy as np
-from scipy.spatial import distance
-
 def _ensure_spacing(coord, spacing, p_norm, max_out): ...
 def ensure_spacing(
     coords,

stubs/skimage/_shared/filters.pyi

@@ -1,13 +1,9 @@
-from collections.abc import Iterable
 from typing import Literal
 
-import numpy as np
 from numpy.typing import ArrayLike, NDArray
-from scipy import ndimage as ndi
 
 from .._typing import Scalar
 from . import utils
-from .utils import _supported_float_type, convert_to_float, warn
 
 @utils.deprecate_multichannel_kwarg(multichannel_position=5)
 def gaussian(

stubs/skimage/_shared/lazy.pyi

@@ -1,7 +1,3 @@
-import importlib
-import importlib.util
-import os
-import sys
 from collections.abc import Mapping
 
 def attach(

stubs/skimage/_shared/setup.pyi

@@ -1,7 +1,5 @@
 #!/usr/bin/env python
 
-import os
-
 base_path = ...
 
 def configuration(parent_package="", top_path=None): ...

stubs/skimage/_shared/tester.pyi

@@ -1,5 +1,3 @@
-import os
-import sys
 from typing import Literal
 
 from numpy.typing import ArrayLike

stubs/skimage/_shared/testing.pyi

@@ -1,31 +1,5 @@
-import functools
-import os
-import re
-import struct
-import threading
-import warnings
-from tempfile import NamedTemporaryFile
-
-import numpy as np
-from numpy import testing
-from numpy.testing import (
-    TestCase,
-    assert_,
-    assert_allclose,
-    assert_almost_equal,
-    assert_array_almost_equal,
-    assert_array_almost_equal_nulp,
-    assert_array_equal,
-    assert_array_less,
-    assert_equal,
-    assert_no_warnings,
-    assert_warns,
-)
 from numpy.typing import ArrayLike
 
-from ..data._fetchers import _fetch
-from ._warnings import expected_warnings
-
 SKIP_RE = ...
 
 skipif = ...

stubs/skimage/_shared/utils.pyi

@@ -1,13 +1,6 @@
-import functools
-import inspect
-import sys
-import warnings
 from collections.abc import Iterable, Mapping
 from typing import Any, Literal
 
-import numpy as np
-import scipy
-from numpy.lib import NumpyVersion
 from numpy.typing import ArrayLike, NDArray
 
 from ._warnings import all_warnings, warn

stubs/skimage/_shared/version_requirements.pyi

@@ -1,7 +1,3 @@
-import sys
-
-from packaging import version as _version
-
 def ensure_python_version(min_version): ...
 def _check_version(actver, version, cmp_op): ...
 def get_module_version(module_name): ...

stubs/sklearn/__check_build/setup.pyi

@@ -1,7 +1,3 @@
-import numpy
-from numpy.distutils.core import setup
-from numpy.distutils.misc_util import Configuration
-
 # Author: Virgile Fritsch <virgile.fritsch@inria.fr>
 # License: BSD 3 clause
 

stubs/sklearn/_build_utils/openmp_helpers.pyi

@@ -1,10 +1,3 @@
-import os
-import sys
-import textwrap
-import warnings
-
-from .pre_build_helpers import compile_test_program as compile_test_program
-
 # This code is adapted for a large part from the astropy openmp helpers, which
 # can be found at: https://github.com/astropy/extension-helpers/blob/master/extension_helpers/_openmp_helpers.py  # noqa
 

stubs/sklearn/_build_utils/pre_build_helpers.pyi

@@ -1,9 +1,2 @@
-import glob
-import os
-import subprocess
-import sys
-import tempfile
-import textwrap
-
 def compile_test_program(code, extra_preargs: list = [], extra_postargs: list = []): ...
 def basic_check_build(): ...

stubs/sklearn/_config.pyi

@@ -1,5 +1,4 @@
 from collections.abc import Iterator
-from contextlib import contextmanager as contextmanager
 from typing import Literal
 
 from ._typing import Int

stubs/sklearn/_loss/glm_distribution.pyi

@@ -1,10 +1,6 @@
-import numbers
 from abc import ABCMeta, abstractmethod
-from collections import namedtuple as namedtuple
 
-import numpy as np
 from numpy import ndarray
-from scipy.special import xlogy as xlogy
 
 from .._typing import ArrayLike, Float
 

stubs/sklearn/_loss/link.pyi

@@ -2,13 +2,9 @@ from abc import ABC, abstractmethod
 from dataclasses import dataclass
 from typing import ClassVar
 
-import numpy as np
 from numpy import ndarray
-from scipy.special import expit as expit, logit as logit
-from scipy.stats import gmean as gmean
 
 from .._typing import ArrayLike, Float
-from ..utils.extmath import softmax as softmax
 
 @dataclass
 class Interval:

stubs/sklearn/_loss/loss.pyi

@@ -1,32 +1,14 @@
-import numbers
 from typing import ClassVar, Literal
 
-import numpy as np
 from numpy import ndarray
-from scipy.special import xlogy as xlogy
 
 from .._typing import ArrayLike, Float, Int, MatrixLike, Scalar
-from ..utils import check_scalar as check_scalar
-from ..utils._readonly_array_wrapper import ReadonlyArrayWrapper as ReadonlyArrayWrapper
 from ._loss import (
-    CyAbsoluteError as CyAbsoluteError,
-    CyHalfBinomialLoss as CyHalfBinomialLoss,
-    CyHalfGammaLoss as CyHalfGammaLoss,
-    CyHalfMultinomialLoss as CyHalfMultinomialLoss,
-    CyHalfPoissonLoss as CyHalfPoissonLoss,
-    CyHalfSquaredError,
-    CyHalfTweedieLoss as CyHalfTweedieLoss,
-    CyHalfTweedieLossIdentity as CyHalfTweedieLossIdentity,
     CyLossFunction,
-    CyPinballLoss as CyPinballLoss,
 )
 from .link import (
     BaseLink,
-    IdentityLink,
     Interval,
-    LogitLink as LogitLink,
-    LogLink as LogLink,
-    MultinomialLogit as MultinomialLogit,
 )
 
 # Goals:

stubs/sklearn/_loss/setup.pyi

@@ -1,7 +1 @@
-import numpy
-from numpy.distutils.core import setup
-from numpy.distutils.misc_util import Configuration
-
-from .._build_utils import gen_from_templates
-
 def configuration(parent_package: str = "", top_path=None): ...

stubs/sklearn/_min_dependencies.pyi

@@ -1,5 +1,3 @@
-from collections import defaultdict as defaultdict
-
 SCIPY_MIN_VERSION: str = ...
 JOBLIB_MIN_VERSION: str = ...
 THREADPOOLCTL_MIN_VERSION: str = ...

stubs/sklearn/cluster/_affinity_propagation.pyi

@@ -1,18 +1,11 @@
-from numbers import Integral as Integral, Real as Real
 from typing import Any, ClassVar, Literal
 from typing_extensions import Self
 
 from numpy import ndarray
 from numpy.random import RandomState
 
-from .._config import config_context as config_context
 from .._typing import ArrayLike, Float, Int, MatrixLike
 from ..base import BaseEstimator, ClusterMixin
-from ..exceptions import ConvergenceWarning as ConvergenceWarning
-from ..metrics import euclidean_distances as euclidean_distances, pairwise_distances_argmin as pairwise_distances_argmin
-from ..utils import as_float_array as as_float_array, check_random_state as check_random_state
-from ..utils._param_validation import Interval as Interval, StrOptions as StrOptions
-from ..utils.validation import check_is_fitted as check_is_fitted
 
 ###############################################################################
 # Public API

stubs/sklearn/cluster/_agglomerative.pyi

@@ -1,23 +1,11 @@
-from heapq import heapify as heapify, heappop as heappop, heappush as heappush, heappushpop as heappushpop
-from numbers import Integral as Integral, Real as Real
 from typing import Any, Callable, ClassVar, Literal
 from typing_extensions import Self
 
 from joblib import Memory
 from numpy import ndarray
-from scipy import sparse as sparse
-from scipy.cluster import hierarchy as hierarchy
-from scipy.sparse.csgraph import connected_components as connected_components
 
 from .._typing import ArrayLike, Float, Int, MatrixLike
 from ..base import BaseEstimator, ClassNamePrefixFeaturesOutMixin, ClusterMixin
-from ..metrics import DistanceMetric as DistanceMetric
-from ..metrics._dist_metrics import METRIC_MAPPING as METRIC_MAPPING
-from ..metrics.pairwise import paired_distances as paired_distances
-from ..utils import check_array as check_array
-from ..utils._fast_dict import IntFloatDict as IntFloatDict
-from ..utils._param_validation import HasMethods as HasMethods, Hidden as Hidden, Interval as Interval, StrOptions as StrOptions
-from ..utils.validation import check_memory as check_memory
 from ._feature_agglomeration import AgglomerationTransform
 
 ###############################################################################

stubs/sklearn/cluster/_bicluster.pyi

@@ -1,25 +1,12 @@
 from abc import ABCMeta, abstractmethod
-from numbers import Integral as Integral
 from typing import Any, ClassVar, Literal
 from typing_extensions import Self
 
 from numpy import ndarray
 from numpy.random import RandomState
-from scipy.linalg import norm as norm
-from scipy.sparse import dia_matrix as dia_matrix, issparse as issparse
-from scipy.sparse.linalg import eigsh as eigsh, svds as svds
 
 from .._typing import ArrayLike, Int, MatrixLike
 from ..base import BaseEstimator, BiclusterMixin
-from ..utils import check_random_state as check_random_state, check_scalar as check_scalar
-from ..utils._param_validation import Interval as Interval, StrOptions as StrOptions
-from ..utils.extmath import (
-    make_nonnegative as make_nonnegative,
-    randomized_svd as randomized_svd,
-    safe_sparse_dot as safe_sparse_dot,
-)
-from ..utils.validation import assert_all_finite as assert_all_finite
-from . import KMeans as KMeans, MiniBatchKMeans as MiniBatchKMeans
 
 __all__ = ["SpectralCoclustering", "SpectralBiclustering"]
 

stubs/sklearn/cluster/_birch.pyi

@@ -1,22 +1,11 @@
-from math import sqrt as sqrt
-from numbers import Integral as Integral, Real as Real
 from typing import Any, ClassVar
 from typing_extensions import Self
 
 from numpy import ndarray
-from scipy import sparse as sparse
 from scipy.sparse import spmatrix
 
-from .._config import config_context as config_context
 from .._typing import ArrayLike, Float, Int, MatrixLike
 from ..base import BaseEstimator, ClassNamePrefixFeaturesOutMixin, ClusterMixin, TransformerMixin
-from ..exceptions import ConvergenceWarning as ConvergenceWarning
-from ..metrics import pairwise_distances_argmin as pairwise_distances_argmin
-from ..metrics.pairwise import euclidean_distances as euclidean_distances
-from ..utils._param_validation import Interval as Interval
-from ..utils.extmath import row_norms as row_norms
-from ..utils.validation import check_is_fitted as check_is_fitted
-from . import AgglomerativeClustering as AgglomerativeClustering
 
 # Authors: Manoj Kumar <manojkumarsivaraj334@gmail.com>
 #          Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>

stubs/sklearn/cluster/_bisect_k_means.pyi

@@ -6,9 +6,6 @@ from numpy import ndarray
 from numpy.random import RandomState
 
 from .._typing import ArrayLike, Float, Int, MatrixLike
-from ..utils._param_validation import StrOptions as StrOptions
-from ..utils.extmath import row_norms as row_norms
-from ..utils.validation import check_is_fitted as check_is_fitted, check_random_state as check_random_state
 from ._kmeans import _BaseKMeans
 
 # Author: Michal Krawczyk <mkrwczyk.1@gmail.com>

stubs/sklearn/cluster/_dbscan.pyi

@@ -1,15 +1,10 @@
-from numbers import Integral as Integral, Real as Real
 from typing import Any, Callable, ClassVar, Literal
 from typing_extensions import Self
 
 from numpy import ndarray
-from scipy import sparse as sparse
 
 from .._typing import ArrayLike, Float, Int, MatrixLike
 from ..base import BaseEstimator, ClusterMixin
-from ..neighbors import NearestNeighbors as NearestNeighbors
-from ..utils._param_validation import Interval as Interval, StrOptions as StrOptions
-from ._dbscan_inner import dbscan_inner as dbscan_inner
 
 # Author: Robert Layton <robertlayton@gmail.com>
 #         Joel Nothman <joel.nothman@gmail.com>

stubs/sklearn/cluster/_feature_agglomeration.pyi

@@ -1,9 +1,7 @@
 from numpy import ndarray
-from scipy.sparse import issparse as issparse
 
 from .._typing import ArrayLike, MatrixLike
 from ..base import TransformerMixin
-from ..utils.validation import check_is_fitted as check_is_fitted
 
 # Author: V. Michel, A. Gramfort
 # License: BSD 3 clause

stubs/sklearn/cluster/_kmeans.pyi

@@ -1,5 +1,4 @@
-from abc import ABC, abstractmethod as abstractmethod
-from numbers import Integral as Integral, Real as Real
+from abc import ABC
 from typing import Any, Callable, ClassVar, Literal
 from typing_extensions import Self
 
@@ -8,31 +7,6 @@ from numpy.random import RandomState
 
 from .._typing import ArrayLike, Float, Int, MatrixLike
 from ..base import BaseEstimator, ClassNamePrefixFeaturesOutMixin, ClusterMixin, TransformerMixin
-from ..exceptions import ConvergenceWarning as ConvergenceWarning
-from ..metrics.pairwise import euclidean_distances as euclidean_distances
-from ..utils import check_array as check_array, check_random_state as check_random_state
-from ..utils._param_validation import (
-    Hidden as Hidden,
-    Interval as Interval,
-    StrOptions as StrOptions,
-    validate_params as validate_params,
-)
-from ..utils._readonly_array_wrapper import ReadonlyArrayWrapper as ReadonlyArrayWrapper
-from ..utils.extmath import row_norms as row_norms, stable_cumsum as stable_cumsum
-from ..utils.sparsefuncs import mean_variance_axis as mean_variance_axis
-from ..utils.sparsefuncs_fast import assign_rows_csr as assign_rows_csr
-from ..utils.validation import check_is_fitted as check_is_fitted
-from ._k_means_common import CHUNK_SIZE as CHUNK_SIZE
-from ._k_means_elkan import (
-    elkan_iter_chunked_dense as elkan_iter_chunked_dense,
-    elkan_iter_chunked_sparse as elkan_iter_chunked_sparse,
-    init_bounds_dense as init_bounds_dense,
-    init_bounds_sparse as init_bounds_sparse,
-)
-from ._k_means_lloyd import (
-    lloyd_iter_chunked_dense as lloyd_iter_chunked_dense,
-    lloyd_iter_chunked_sparse as lloyd_iter_chunked_sparse,
-)
 
 ###############################################################################
 # Initialization heuristic