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Fix all stub-body-multiple-statements (PYI048) #362

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Merged
merged 4 commits into from
May 5, 2025
Merged

Fix all stub-body-multiple-statements (PYI048) #362

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bb914e7
stub-body-multiple-statements (PYI048)
Avasam May 3, 2025
3e8a227
Merge branch 'main' into Fix-all-stub-body-multiple-statements-(PYI048)
debonte May 5, 2025
0ebea6c
Merge branch 'main' into Fix-all-stub-body-multiple-statements-(PYI048)
Avasam May 5, 2025
d315513
Merge branch 'main' into Fix-all-stub-body-multiple-statements-(PYI048)
debonte May 5, 2025
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2 changes: 1 addition & 1 deletion pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -33,6 +33,7 @@ extend-select = [
"PYI", # flake8-pyi
"UP", # pyupgrade
"W", # pycodestyle Warning
"PIE790", # unnecessary-placeholder
]
ignore = [
###
Expand All @@ -55,7 +56,6 @@ ignore = [
"F401",

# TODO: Investigate and fix or configure
"PYI048",
"PYI051", # Request for autofix: https://github.com/astral-sh/ruff/issues/14185
]
[tool.ruff.lint.per-file-ignores]
Expand Down
4 changes: 0 additions & 4 deletions stubs/sklearn/cluster/_k_means_elkan.pyi
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Expand Up @@ -41,7 +41,6 @@ def init_bounds_dense(
n_threads : int
The number of threads to be used by openmp.
"""
...

def init_bounds_sparse(
X: spmatrix,
Expand Down Expand Up @@ -83,7 +82,6 @@ def init_bounds_sparse(
n_threads : int
The number of threads to be used by openmp.
"""
...

def elkan_iter_chunked_dense(
X: np.ndarray,
Expand Down Expand Up @@ -141,7 +139,6 @@ def elkan_iter_chunked_dense(
the algorithm. This is useful especially when calling predict on a
fitted model.
"""
...

def elkan_iter_chunked_sparse(
X: spmatrix,
Expand Down Expand Up @@ -199,4 +196,3 @@ def elkan_iter_chunked_sparse(
the algorithm. This is useful especially when calling predict on a
fitted model.
"""
...
2 changes: 0 additions & 2 deletions stubs/sklearn/cluster/_k_means_lloyd.pyi
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Expand Up @@ -44,7 +44,6 @@ def lloyd_iter_chunked_dense(
the algorithm. This is useful especially when calling predict on a
fitted model.
"""
...

def lloyd_iter_chunked_sparse(
X: np.ndarray,
Expand Down Expand Up @@ -90,4 +89,3 @@ def lloyd_iter_chunked_sparse(
the algorithm. This is useful especially when calling predict on a
fitted model.
"""
...
1 change: 0 additions & 1 deletion stubs/sklearn/decomposition/_online_lda_fast.pyi
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Expand Up @@ -5,6 +5,5 @@ def mean_change(arr_1: np.ndarray, arr_2: np.ndarray) -> float:

Equivalent to np.abs(arr_1 - arr2).mean().
"""
...

def psi(x: float) -> float: ...
2 changes: 0 additions & 2 deletions stubs/sklearn/ensemble/_gradient_boosting.pyi
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Expand Up @@ -5,11 +5,9 @@ def predict_stages(estimators: np.ndarray, X, scale: float, out: np.ndarray) ->
Each estimator is scaled by ``scale`` before its prediction
is added to ``out``.
"""
...

def predict_stage(estimators: np.ndarray, stage: int, X, scale: float, out: np.ndarray) -> None:
"""Add predictions of ``estimators[stage]`` to ``out``.
Each estimator in the stage is scaled by ``scale`` before
its prediction is added to ``out``.
"""
...
2 changes: 0 additions & 2 deletions stubs/sklearn/ensemble/_hist_gradient_boosting/histogram.pyi
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Expand Up @@ -58,7 +58,6 @@ class HistogramBuilder:
histograms : ndarray of HISTOGRAM_DTYPE, shape (n_features, n_bins)
The computed histograms of the current node.
"""
...

def compute_histograms_subtraction(
self,
Expand All @@ -85,4 +84,3 @@ class HistogramBuilder:
histograms : ndarray of HISTOGRAM_DTYPE, shape(n_features, n_bins)
The computed histograms of the current node.
"""
...
2 changes: 0 additions & 2 deletions stubs/sklearn/ensemble/_hist_gradient_boosting/splitting.pyi
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Expand Up @@ -159,7 +159,6 @@ class Splitter:
right_child_position : int
The position of the right child in ``sample_indices``.
"""
...

def find_node_split(
self,
Expand Down Expand Up @@ -208,4 +207,3 @@ class Splitter:
best_split_info : SplitInfo
The info about the best possible split among all features.
"""
...
1 change: 0 additions & 1 deletion stubs/sklearn/feature_extraction/_hashing_fast.pyi
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Expand Up @@ -8,4 +8,3 @@ def transform(
indices, indptr, values : lists
For constructing a scipy.sparse.csr_matrix.
"""
...
4 changes: 0 additions & 4 deletions stubs/sklearn/metrics/_pairwise_distances_reduction/_dispatcher.pyi
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Expand Up @@ -20,7 +20,6 @@ def sqeuclidean_row_norms(X: np.ndarray | csr_matrix, num_threads: int) -> np.nd
sqeuclidean_row_norms : ndarray of shape (n_samples,)
Arrays containing the squared euclidean norm of each row of X.
"""
...

class BaseDistancesReductionDispatcher:
"""Abstract base dispatcher for pairwise distance computation & reduction.
Expand Down Expand Up @@ -53,7 +52,6 @@ class BaseDistancesReductionDispatcher:
-------
True if the dispatcher can be used, else False.
"""
...

@classmethod
@abstractmethod
Expand Down Expand Up @@ -170,7 +168,6 @@ class ArgKmin(BaseDistancesReductionDispatcher):
for the concrete implementation are therefore freed when this classmethod
returns.
"""
...

class RadiusNeighbors(BaseDistancesReductionDispatcher):
"""Compute radius-based neighbors for two sets of vectors.
Expand Down Expand Up @@ -286,4 +283,3 @@ class RadiusNeighbors(BaseDistancesReductionDispatcher):
for the concrete implementation are therefore freed when this classmethod
returns.
"""
...
1 change: 0 additions & 1 deletion stubs/sklearn/utils/arrayfuncs.pyi
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Expand Up @@ -5,6 +5,5 @@ def min_pos(X: np.ndarray) -> float:
Returns the maximum representable value of the input dtype if none of the
values are positive.
"""
...

def cholesky_delete(L: np.ndarray, go_out: int) -> None: ...
7 changes: 0 additions & 7 deletions stubs/sklearn/utils/sparsefuncs_fast.pyi
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Expand Up @@ -3,7 +3,6 @@ from scipy.sparse import csc_matrix, csr_matrix

def csr_row_norms(X: np.ndarray) -> np.ndarray:
"""Squared L2 norm of each row in CSR matrix X."""
...

def csr_mean_variance_axis0(
X: csr_matrix, weights: np.ndarray | None = None, return_sum_weights: bool = False
Expand All @@ -29,7 +28,6 @@ def csr_mean_variance_axis0(
sum_weights : ndarray of shape (n_features,), dtype=floating
Returned if return_sum_weights is True.
"""
...

def csc_mean_variance_axis0(
X: csc_matrix, weights: np.ndarray | None = None, return_sum_weights: bool = False
Expand All @@ -55,7 +53,6 @@ def csc_mean_variance_axis0(
sum_weights : ndarray of shape (n_features,), dtype=floating
Returned if return_sum_weights is True.
"""
...

def incr_mean_variance_axis0(
X: csr_matrix | csc_matrix, last_mean: np.ndarray, last_var: np.ndarray, last_n: np.ndarray, weights: np.ndarray | None = None
Expand Down Expand Up @@ -86,15 +83,12 @@ def incr_mean_variance_axis0(
updated_n : int array with shape (n_features,)
Updated number of samples seen
"""
...

def inplace_csr_row_normalize_l1(X: np.ndarray) -> None:
"""Inplace row normalize using the l1 norm"""
...

def inplace_csr_row_normalize_l2(X: np.ndarray) -> None:
"""Inplace row normalize using the l2 norm"""
...

def assign_rows_csr(
X: csr_matrix,
Expand All @@ -112,4 +106,3 @@ def assign_rows_csr(
out_rows : array, dtype=np.intp, shape=n_rows
out : array, shape=(arbitrary, n_features)
"""
...