Merge remote-tracking branch 'upstream/main' into feat/pep770-sbom

Author: fangchenli

.clang-format

@@ -4,11 +4,11 @@ on:
   push:
     branches:
       - main
-      - 2.3.x
+      - 3.0.x
   pull_request:
     branches:
       - main
-      - 2.3.x
+      - 3.0.x
 
 env:
   ENV_FILE: environment.yml

.github/workflows/code-checks.yml

@@ -4,13 +4,13 @@ on:
   push:
     branches:
       - main
-      - 2.3.x
+      - 3.0.x
     tags:
       - '*'
   pull_request:
     branches:
       - main
-      - 2.3.x
+      - 3.0.x
   workflow_dispatch:
     inputs:
       version:

.github/workflows/docbuild-and-upload.yml

@@ -4,11 +4,11 @@ on:
   push:
     branches:
       - main
-      - 2.3.x
+      - 3.0.x
   pull_request:
     branches:
       - main
-      - 2.3.x
+      - 3.0.x
     types: [ labeled, opened, synchronize, reopened ]
 
 permissions:

.github/workflows/package-checks.yml

@@ -4,11 +4,11 @@ on:
   push:
     branches:
       - main
-      - 2.3.x
+      - 3.0.x
   pull_request:
     branches:
       - main
-      - 2.3.x
+      - 3.0.x
     paths-ignore:
       - "doc/**"
       - "web/**"
@@ -167,7 +167,9 @@ jobs:
       id: build
       uses: ./.github/actions/build_pandas
       with:
-        # xref https://github.com/cython/cython/issues/6870
+        # python3.14t/cpython/pyatomic_gcc.h:63:10:
+        #   error: ‘__atomic_fetch_add_8’
+        #   writing 8 bytes into a region of size 0 overflows the destination [-Werror=stringop-overflow=]
         werror: ${{ matrix.name != 'Freethreading' }}
 
     - name: Test (not single_cpu)
@@ -241,14 +243,12 @@ jobs:
           fi
       - name: Build environment and Run Tests
         # https://github.com/numpy/numpy/issues/24703#issuecomment-1722379388
-        # Note: Pinned to Cython 3.0.10 to avoid numerical instability in 32-bit environments
-        # https://github.com/pandas-dev/pandas/pull/61423
         run: |
           /opt/python/cp313-cp313/bin/python -m venv ~/virtualenvs/pandas-dev
           . ~/virtualenvs/pandas-dev/bin/activate
           python -m pip install --no-cache-dir -U pip wheel setuptools meson[ninja]==1.2.1 meson-python==0.13.1
           python -m pip install numpy -Csetup-args="-Dallow-noblas=true"
-          python -m pip install --no-cache-dir versioneer[toml] cython==3.0.10 python-dateutil pytest>=8.3.4 pytest-xdist>=3.6.1 hypothesis>=6.116.0
+          python -m pip install --no-cache-dir versioneer[toml] cython python-dateutil pytest>=8.3.4 pytest-xdist>=3.6.1 hypothesis>=6.116.0
           python -m pip install --no-cache-dir --no-build-isolation -e . -Csetup-args="--werror"
           python -m pip list --no-cache-dir
           PANDAS_CI=1 python -m pytest -m 'not slow and not network and not clipboard and not single_cpu' pandas --junitxml=test-data.xml

.github/workflows/unit-tests.yml

@@ -19,7 +19,7 @@ ci:
     skip: [pyright, mypy]
 repos:
 -   repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.14.7
+    rev: v0.14.10
     hooks:
     -   id: ruff
         args: [--exit-non-zero-on-fix]
@@ -92,14 +92,14 @@ repos:
     - id: sphinx-lint
       args: ["--enable", "all", "--disable", "line-too-long"]
 -   repo: https://github.com/pre-commit/mirrors-clang-format
-    rev: v21.1.6
+    rev: v21.1.8
     hooks:
     - id: clang-format
       files: ^pandas/_libs/src|^pandas/_libs/include
-      args: [-i]
+      args: ['-i', '--style', '{IndentPPDirectives: AfterHash}']
       types_or: [c, c++]
 -   repo: https://github.com/trim21/pre-commit-mirror-meson
-    rev: v1.9.1
+    rev: v1.10.0
     hooks:
     - id: meson-fmt
       args: ['--inplace']

.pre-commit-config.yaml

@@ -3,7 +3,7 @@ BSD 3-Clause License
 Copyright (c) 2008-2011, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development Team
 All rights reserved.
 
-Copyright (c) 2011-2025, Open source contributors.
+Copyright (c) 2011-2026, Open source contributors.
 
 Redistribution and use in source and binary forms, with or without
 modification, are permitted provided that the following conditions are met:

LICENSE

@@ -29,7 +29,7 @@ def setup(self):
         self.datetimes_with_nat = self.datetimes.copy()
         self.datetimes_with_nat.iloc[-1] = pd.NaT
 
-        self.values_some_nan = list(np.tile(self.categories + [np.nan], N))
+        self.values_some_nan = list(np.tile([*self.categories, np.nan], N))
         self.values_all_nan = [np.nan] * len(self.values)
         self.values_all_int8 = np.ones(N, "int8")
         self.categorical = pd.Categorical(self.values, self.categories)

asv_bench/benchmarks/categoricals.py

@@ -39,11 +39,11 @@ def list_of_lists(arr):
 
 
 def list_of_tuples_with_none(arr):
-    return [(i, -i) for i in arr][:-1] + [None]
+    return [*[(i, -i) for i in arr][:-1], None]
 
 
 def list_of_lists_with_none(arr):
-    return [[i, -i] for i in arr][:-1] + [None]
+    return [*[[i, -i] for i in arr][:-1], None]
 
 
 class SeriesConstructors:

asv_bench/benchmarks/ctors.py

@@ -44,8 +44,8 @@ class Unique:
     param_names = ["dtype"]
 
     def setup(self, dtype):
-        self.ser = pd.Series(([1, pd.NA, 2] + list(range(100_000))) * 3, dtype=dtype)
-        self.ser_unique = pd.Series(list(range(300_000)) + [pd.NA], dtype=dtype)
+        self.ser = pd.Series(([1, pd.NA, 2, *range(100000)]) * 3, dtype=dtype)
+        self.ser_unique = pd.Series([*range(300000), pd.NA], dtype=dtype)
 
     def time_unique_with_duplicates(self, exponent):
         pd.unique(self.ser)
@@ -62,7 +62,7 @@ class NumericSeriesIndexing:
     param_names = ["dtype", "N"]
 
     def setup(self, dtype, N):
-        vals = np.array(list(range(55)) + [54] + list(range(55, N - 1)), dtype=dtype)
+        vals = np.array([*range(55), 54, *range(55, N - 1)], dtype=dtype)
         indices = pd.Index(vals)
         self.data = pd.Series(np.arange(N), index=indices)
 
@@ -79,7 +79,7 @@ class NumericSeriesIndexingShuffled:
     param_names = ["dtype", "N"]
 
     def setup(self, dtype, N):
-        vals = np.array(list(range(55)) + [54] + list(range(55, N - 1)), dtype=dtype)
+        vals = np.array([*range(55), 54, *range(55, N - 1)], dtype=dtype)
         np.random.shuffle(vals)
         indices = pd.Index(vals)
         self.data = pd.Series(np.arange(N), index=indices)