Accepting request 1045082 from home:bnavigator:branches:devel:languages:python:numeric

- 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

OBS-URL: https://build.opensuse.org/request/show/1045082
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-pandas?expand=0&rev=78
This commit is contained in:
Matej Cepl 2022-12-24 10:44:42 +00:00 committed by Git OBS Bridge
parent 17f26b04da
commit 04666fb180
5 changed files with 211 additions and 34 deletions

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@ -1,3 +0,0 @@
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size 5199286

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pandas-1.5.2.tar.gz Normal file
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From a0e1b0c28dfccd9a3f9e9e2794ef109e950d1a08 Mon Sep 17 00:00:00 2001
From: Patrick Hoefler <61934744+phofl@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)

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@ -1,3 +1,34 @@
-------------------------------------------------------------------
Fri Dec 23 16:22:18 UTC 2022 - Ben Greiner <code@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
-------------------------------------------------------------------
Sat Oct 22 16:10:11 UTC 2022 - Arun Persaud <arun@gmx.de>

View File

@ -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
Suggests: python-Jinja2 >= 3.0.0
Suggests: python-PyMySQL >= 1.0.2
Suggests: python-SQLAlchemy >= 1.4.16
Suggests: python-XlsxWriter >= 1.2.2
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
# Visualization
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
Suggests: python-psycopg2 >= 2.8.6
Suggests: python-pyarrow >= 1.0.1
Suggests: python-pyreadstat >= 1.1.2
Suggests: python-qt5
Suggests: python-s3fs >= 0.4.0
Suggests: python-scipy >= 1.7.1
Suggests: python-tables >= 3.6.1
Suggests: python-Jinja2 >= 3.0.0
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-html5lib >= 1.1
Suggests: python-lxml >= 4.6.3
# 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-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 @@ heterogeneous) and time series data. It is a high-level building
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}%{$python_sitearch}
}
@ -163,6 +182,8 @@ export PYTHONHASHSEED=1
SKIP_TESTS="(test_misc and test_memory_usage and series and empty and index)"
# pytest-xdist worker crash
SKIP_TESTS+=" or test_pivot_number_of_levels_larger_than_int32"
# https://github.com/pandas-dev/pandas/pull/49777 -- removed in pandas 1.6+
SKIP_TESTS+=" or test_constructor_signed_int_overflow_deprecation"
# --skip-* arguments: Upstream's custom way to skip marked tests. These do not use pytest.mark.
SKIP_ARGS="--skip-network"
@ -225,7 +246,7 @@ xvfb-run pytest-%{$python_bin_suffix} -v -n %{jobs} --dist=loadfile \
%license LICENSE
%doc README.md RELEASE.md
%{python_sitearch}/pandas/
%{python_sitearch}/pandas-%{version}*-info
%{python_sitearch}/pandas-%{version}.dist-info
%endif
%changelog