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here is the log from the commit of package python-pandas for openSUSE:Factory
checked in at 2022-12-25 15:14:34
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Comparing /work/SRC/openSUSE:Factory/python-pandas (Old)
and /work/SRC/openSUSE:Factory/.python-pandas.new.1563 (New)
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Package is "python-pandas"
Sun Dec 25 15:14:34 2022 rev:46 rq:1045178 version:1.5.2
Changes:
--------
--- /work/SRC/openSUSE:Factory/python-pandas/python-pandas.changes
2022-10-27 13:53:24.280332554 +0200
+++ /work/SRC/openSUSE:Factory/.python-pandas.new.1563/python-pandas.changes
2022-12-25 15:14:47.625352982 +0100
@@ -1,0 +2,31 @@
+Fri Dec 23 16:22:18 UTC 2022 - Ben Greiner <c...@bnavigator.de>
+
+- Update to version 1.5.2
+ ## Fixed regressions
+ * Fixed regression in MultiIndex.join() for extension array
+ dtypes (GH49277)
+ * Fixed regression in Series.replace() raising RecursionError
+ with numeric dtype and when specifying value=None (GH45725)
+ * Fixed regression in arithmetic operations for DataFrame with
+ MultiIndex columns with different dtypes (GH49769)
+ * Fixed regression in DataFrame.plot() preventing Colormap
+ instance from being passed using the colormap argument if
+ Matplotlib 3.6+ is used (GH49374)
+ * Fixed regression in date_range() returning an invalid set of
+ periods for CustomBusinessDay frequency and start date with
+ timezone (GH49441)
+ * Fixed performance regression in groupby operations (GH49676)
+ * Fixed regression in Timedelta constructor returning object of
+ wrong type when subclassing Timedelta (GH49579)
+ ## Bug fixes
+ * Bug in the Copy-on-Write implementation losing track of views
+ in certain chained indexing cases (GH48996)
+ * Fixed memory leak in Styler.to_excel() (GH49751)
+ ## Other
+ * Reverted color as an alias for c and size as an alias for s in
+ function DataFrame.plot.scatter() (GH49732)
+- Add pandas-pr49886-fix-numpy-deprecations.patch
+ * gh#pandas-dev/pandas#49887
+- Move to PEP518 build
+
+-------------------------------------------------------------------
Old:
----
pandas-1.5.1.tar.gz
New:
----
pandas-1.5.2.tar.gz
pandas-pr49886-fix-numpy-deprecations.patch
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Other differences:
------------------
++++++ python-pandas.spec ++++++
--- /var/tmp/diff_new_pack.UfQxYG/_old 2022-12-25 15:14:48.173356082 +0100
+++ /var/tmp/diff_new_pack.UfQxYG/_new 2022-12-25 15:14:48.177356106 +0100
@@ -39,64 +39,83 @@
%define psuffix %{nil}
%bcond_with test
%endif
-%{?!python_module:%define python_module() python3-%{**}}
-%define skip_python2 1
+
Name: python-pandas%{psuffix}
-Version: 1.5.1
+Version: 1.5.2
Release: 0
Summary: Python data structures for data analysis, time series, and
statistics
License: BSD-3-Clause
Group: Development/Libraries/Python
URL: https://pandas.pydata.org/
Source0:
https://files.pythonhosted.org/packages/source/p/pandas/pandas-%{version}.tar.gz
+# SourceRepository: https://github.com/pandas-dev/pandas
+# PATCH-FIX-UPSTREAM pandas-pr49886-fix-numpy-deprecations.patch
gh#pandas-dev/pandas#49886, gh#pandas-dev/pandas#49887
+Patch1: pandas-pr49886-fix-numpy-deprecations.patch
BuildRequires: %{python_module Cython >= 0.29.32}
-BuildRequires: %{python_module Jinja2 >= 3.0.0}
BuildRequires: %{python_module devel >= 3.8}
BuildRequires: %{python_module numpy-devel >= 1.20.3}
-BuildRequires: %{python_module python-dateutil >= 2.8.1}
-BuildRequires: %{python_module pytz >= 2020.1}
+BuildRequires: %{python_module pip}
BuildRequires: %{python_module setuptools >= 51.0.0}
+BuildRequires: %{python_module wheel}
BuildRequires: fdupes
BuildRequires: gcc-c++
BuildRequires: python-rpm-macros
Requires: python-numpy >= 1.20.3
Requires: python-python-dateutil >= 2.8.1
Requires: python-pytz >= 2020.1
+# SECTION Optional dependencies
+#
https://pandas.pydata.org/docs/getting_started/install.html#optional-dependencies
Recommends: python-Bottleneck >= 1.3.2
Recommends: python-numexpr >= 2.7.3
+# Visualization
+Suggests: python-matplotlib >= 3.3.2
Suggests: python-Jinja2 >= 3.0.0
-Suggests: python-PyMySQL >= 1.0.2
-Suggests: python-SQLAlchemy >= 1.4.16
+Suggests: python-tabulate >= 0.8.9
+# Computation
+Suggests: python-scipy >= 1.7.1
+Suggests: python-numba >= 0.53.1
+Suggests: python-xarray >= 0.19.0
+# Excel files
+Suggests: python-xlrd >= 2.0.1
+Suggests: python-xlwt >= 1.3.0
Suggests: python-XlsxWriter >= 1.2.2
+Suggests: python-openpyxl >= 3.0.7
+Suggests: python-pyxlb >= 1.0.8
+# HTML
Suggests: python-beautifulsoup4 >= 4.9.3
-Suggests: python-blosc >= 1.21.0
-Suggests: python-fastparquet >= 0.4.0
-Suggests: python-fsspec >= 0.7.4
-Suggests: python-gcsfs >= 0.6.0
Suggests: python-html5lib >= 1.1
Suggests: python-lxml >= 4.6.3
-Suggests: python-matplotlib >= 3.3.2
-Suggests: python-numba >= 0.53.1
-Suggests: python-openpyxl >= 3.0.7
-Suggests: python-pandas-gbq >= 0.15.0
+# SQL databases
+Suggests: python-PyMySQL >= 1.0.2
+Suggests: python-SQLAlchemy >= 1.4.16
Suggests: python-psycopg2 >= 2.8.6
+# Other data sources
+Suggests: python-tables >= 3.6.1
+Suggests: python-blosc >= 1.21.0
+Suggests: python-zlib
+Suggests: python-fastparquet >= 0.4.0
Suggests: python-pyarrow >= 1.0.1
Suggests: python-pyreadstat >= 1.1.2
+# Access data in the cloud
+Suggests: python-fsspec >= 2021.7.0
+Suggests: python-gcsfs >= 2021.7.0
+Suggests: python-pandas-gbq >= 0.15.0
+Suggests: python-s3fs >= 2021.08.0
+# Clipboard
Suggests: python-qt5
-Suggests: python-s3fs >= 0.4.0
-Suggests: python-scipy >= 1.7.1
-Suggests: python-tables >= 3.6.1
-Suggests: python-tabulate >= 0.8.9
-Suggests: python-xarray >= 0.19.0
-Suggests: python-xlrd >= 2.0.1
-Suggests: python-xlwt >= 1.3.0
-Suggests: python-zlib
+Suggests: python-QtPy
Suggests: xclip
Suggests: xsel
+# Compression
+Suggests: python-Brotli >= 0.7.0
+Suggests: python-python-snappy >= 0.6.0
+Suggests: python-zstandard >= 0.15.2
+# /SECTION
Obsoletes: python-pandas-doc < %{version}
Provides: python-pandas-doc = %{version}
%if %{with test}
BuildRequires: %{python_module Bottleneck >= 1.3.2}
+BuildRequires: %{python_module Jinja2 >= 3}
BuildRequires: %{python_module SQLAlchemy >= 1.4.16}
BuildRequires: %{python_module XlsxWriter >= 1.4.3}
BuildRequires: %{python_module beautifulsoup4 >= 4.9.3}
@@ -125,18 +144,18 @@
block for doing data analysis in Python.
%prep
-%setup -q -n pandas-%{version}
+%autosetup -p1 -n pandas-%{version}
sed -i 's/--strict-data-files//' pyproject.toml
%build
%if !%{with test}
export CFLAGS="%{optflags} -fno-strict-aliasing"
-%python_build
+%pyproject_wheel
%endif
%install
%if !%{with test}
-%python_install
+%pyproject_install
%{python_expand sed -i -e 's|"python", "-c",|"%{__$python}", "-c",|'
%{buildroot}%{$python_sitearch}/pandas/tests/io/test_compression.py
%fdupes %{buildroot}%{$python_sitearch}
}
@@ -163,6 +182,8 @@
SKIP_TESTS="(test_misc and test_memory_usage and series and empty and index)"
# pytest-xdist worker crash
SKIP_TESTS+=" or test_pivot_number_of_levels_larger_than_int32"
+# https://github.com/pandas-dev/pandas/pull/49777 -- removed in pandas 1.6+
+SKIP_TESTS+=" or test_constructor_signed_int_overflow_deprecation"
# --skip-* arguments: Upstream's custom way to skip marked tests. These do not
use pytest.mark.
SKIP_ARGS="--skip-network"
@@ -225,7 +246,7 @@
%license LICENSE
%doc README.md RELEASE.md
%{python_sitearch}/pandas/
-%{python_sitearch}/pandas-%{version}*-info
+%{python_sitearch}/pandas-%{version}.dist-info
%endif
%changelog
++++++ pandas-1.5.1.tar.gz -> pandas-1.5.2.tar.gz ++++++
++++ 2002 lines of diff (skipped)
++++++ pandas-pr49886-fix-numpy-deprecations.patch ++++++
>From a0e1b0c28dfccd9a3f9e9e2794ef109e950d1a08 Mon Sep 17 00:00:00 2001
From: Patrick Hoefler <61934744+ph...@users.noreply.github.com>
Date: Thu, 24 Nov 2022 11:58:42 +0000
Subject: [PATCH] Backport PR #49886: CI: Remove deprecated numpy dtype aliases
---
asv_bench/benchmarks/sparse.py | 4 ++--
pandas/core/arrays/sparse/array.py | 4 ++--
pandas/core/interchange/column.py | 2 +-
pandas/tests/arrays/sparse/test_indexing.py | 4 ++--
pandas/tests/arrays/sparse/test_reductions.py | 2 +-
pandas/tests/arrays/sparse/test_unary.py | 4 ++--
pandas/tests/io/excel/test_writers.py | 9 ++++-----
7 files changed, 14 insertions(+), 15 deletions(-)
Index: pandas-1.5.2/pandas/core/arrays/sparse/array.py
===================================================================
--- pandas-1.5.2.orig/pandas/core/arrays/sparse/array.py
+++ pandas-1.5.2/pandas/core/arrays/sparse/array.py
@@ -728,7 +728,7 @@ class SparseArray(OpsMixin, PandasObject
dtype = SparseDtype(bool, self._null_fill_value)
if self._null_fill_value:
return type(self)._simple_new(isna(self.sp_values), self.sp_index,
dtype)
- mask = np.full(len(self), False, dtype=np.bool8)
+ mask = np.full(len(self), False, dtype=np.bool_)
mask[self.sp_index.indices] = isna(self.sp_values)
return type(self)(mask, fill_value=False, dtype=dtype)
@@ -1043,7 +1043,7 @@ class SparseArray(OpsMixin, PandasObject
if not key.fill_value:
return self.take(key.sp_index.indices)
n = len(self)
- mask = np.full(n, True, dtype=np.bool8)
+ mask = np.full(n, True, dtype=np.bool_)
mask[key.sp_index.indices] = False
return self.take(np.arange(n)[mask])
else:
Index: pandas-1.5.2/pandas/core/interchange/column.py
===================================================================
--- pandas-1.5.2.orig/pandas/core/interchange/column.py
+++ pandas-1.5.2/pandas/core/interchange/column.py
@@ -315,7 +315,7 @@ class PandasColumn(Column):
valid = invalid == 0
invalid = not valid
- mask = np.zeros(shape=(len(buf),), dtype=np.bool8)
+ mask = np.zeros(shape=(len(buf),), dtype=np.bool_)
for i, obj in enumerate(buf):
mask[i] = valid if isinstance(obj, str) else invalid
Index: pandas-1.5.2/pandas/tests/arrays/sparse/test_indexing.py
===================================================================
--- pandas-1.5.2.orig/pandas/tests/arrays/sparse/test_indexing.py
+++ pandas-1.5.2/pandas/tests/arrays/sparse/test_indexing.py
@@ -85,7 +85,7 @@ class TestGetitem:
def test_getitem_bool_sparse_array(self):
# GH 23122
- spar_bool = SparseArray([False, True] * 5, dtype=np.bool8,
fill_value=True)
+ spar_bool = SparseArray([False, True] * 5, dtype=np.bool_,
fill_value=True)
exp = SparseArray([np.nan, 2, np.nan, 5, 6])
tm.assert_sp_array_equal(arr[spar_bool], exp)
@@ -95,7 +95,7 @@ class TestGetitem:
tm.assert_sp_array_equal(res, exp)
spar_bool = SparseArray(
- [False, True, np.nan] * 3, dtype=np.bool8, fill_value=np.nan
+ [False, True, np.nan] * 3, dtype=np.bool_, fill_value=np.nan
)
res = arr[spar_bool]
exp = SparseArray([np.nan, 3, 5])
Index: pandas-1.5.2/pandas/tests/arrays/sparse/test_reductions.py
===================================================================
--- pandas-1.5.2.orig/pandas/tests/arrays/sparse/test_reductions.py
+++ pandas-1.5.2/pandas/tests/arrays/sparse/test_reductions.py
@@ -142,7 +142,7 @@ class TestReductions:
assert result == expected
def test_bool_sum_min_count(self):
- spar_bool = SparseArray([False, True] * 5, dtype=np.bool8,
fill_value=True)
+ spar_bool = SparseArray([False, True] * 5, dtype=np.bool_,
fill_value=True)
res = spar_bool.sum(min_count=1)
assert res == 5
res = spar_bool.sum(min_count=11)
Index: pandas-1.5.2/pandas/tests/arrays/sparse/test_unary.py
===================================================================
--- pandas-1.5.2.orig/pandas/tests/arrays/sparse/test_unary.py
+++ pandas-1.5.2/pandas/tests/arrays/sparse/test_unary.py
@@ -59,9 +59,9 @@ class TestUnaryMethods:
tm.assert_sp_array_equal(exp, res)
def test_invert_operator(self):
- arr = SparseArray([False, True, False, True], fill_value=False,
dtype=np.bool8)
+ arr = SparseArray([False, True, False, True], fill_value=False,
dtype=np.bool_)
exp = SparseArray(
- np.invert([False, True, False, True]), fill_value=True,
dtype=np.bool8
+ np.invert([False, True, False, True]), fill_value=True,
dtype=np.bool_
)
res = ~arr
tm.assert_sp_array_equal(exp, res)
Index: pandas-1.5.2/pandas/tests/io/excel/test_writers.py
===================================================================
--- pandas-1.5.2.orig/pandas/tests/io/excel/test_writers.py
+++ pandas-1.5.2/pandas/tests/io/excel/test_writers.py
@@ -496,15 +496,14 @@ class TestExcelWriter:
tm.assert_frame_equal(df, recons)
- @pytest.mark.parametrize("np_type", [np.bool8, np.bool_])
- def test_bool_types(self, np_type, path):
- # Test np.bool8 and np.bool_ values read come back as float.
- df = DataFrame([1, 0, True, False], dtype=np_type)
+ def test_bool_types(self, path):
+ # Test np.bool_ values read come back as float.
+ df = DataFrame([1, 0, True, False], dtype=np.bool_)
df.to_excel(path, "test1")
with ExcelFile(path) as reader:
recons = pd.read_excel(reader, sheet_name="test1",
index_col=0).astype(
- np_type
+ np.bool_
)
tm.assert_frame_equal(df, recons)
