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python-pandas/python-pandas.spec
Matej Cepl aab0b4e004 Accepting request 920383 from home:bnavigator:branches:devel:languages:python:numeric 
- Update to version 1.3.3
  * Fixed regression in DataFrame constructor failing to broadcast
    for defined Index and len one list of Timestamp (GH42810)
  * Fixed regression in GroupBy.agg() incorrectly raising in some
    cases (GH42390)
  * Fixed regression in GroupBy.apply() where nan values were
    dropped even with dropna=False (GH43205)
  * Fixed regression in GroupBy.quantile() which was failing with
    pandas.NA (GH42849)
  * Fixed regression in merge() where on columns with
    ExtensionDtype or bool data types were cast to object in right
    and outer merge (GH40073)
  * Fixed regression in RangeIndex.where() and RangeIndex.putmask()
    raising AssertionError when result did not represent a
    RangeIndex (GH43240)
  * Fixed regression in read_parquet() where the fastparquet engine
    would not work properly with fastparquet 0.7.0 (GH43075)
  * Fixed regression in DataFrame.loc.__setitem__() raising
    ValueError when setting array as cell value (GH43422)
  * Fixed regression in is_list_like() where objects with __iter__
    set to None would be identified as iterable (GH43373)
  * Fixed regression in DataFrame.__getitem__() raising error for
    slice of DatetimeIndex when index is non monotonic (GH43223)
  * Fixed regression in Resampler.aggregate() when used after
    column selection would raise if func is a list of aggregation
    functions (GH42905)
  * Fixed regression in DataFrame.corr() where Kendall correlation
    would produce incorrect results for columns with repeated
    values (GH43401)
  * Fixed regression in DataFrame.groupby() where aggregation on
    columns with object types dropped results on those columns
    (GH42395, GH43108)
  * Fixed regression in Series.fillna() raising TypeError when
    filling float Series with list-like fill value having a dtype
    which couldn’t cast lostlessly (like float32 filled with
    float64) (GH43424)
  * Fixed regression in read_csv() raising AttributeError when the
    file handle is an tempfile.SpooledTemporaryFile object
    (GH43439)
  * Fixed performance regression in core.window.ewm.
    ExponentialMovingWindow.mean() (GH42333)
  * Performance improvement for DataFrame.__setitem__() when the
    key or value is not a DataFrame, or key is not list-like
    (GH43274)
  * Fixed bug in DataFrameGroupBy.agg() and DataFrameGroupBy.
    transform() with engine="numba" where index data was not being
    correctly passed into func (GH43133)
- Release 1.3.2
  * Performance regression in DataFrame.isin() and Series.isin()
    for nullable data types (GH42714)
  * Regression in updating values of Series using boolean index,
    created by using DataFrame.pop() (GH42530)
  * Regression in DataFrame.from_records() with empty records
    (GH42456)
  * Fixed regression in DataFrame.shift() where TypeError occurred
    when shifting DataFrame created by concatenation of slices and
    fills with values (GH42719)
  * Regression in DataFrame.agg() when the func argument returned
    lists and axis=1 (GH42727)
  * Regression in DataFrame.drop() does nothing if MultiIndex has
    duplicates and indexer is a tuple or list of tuples (GH42771)
  * Fixed regression where read_csv() raised a ValueError when
    parameters names and prefix were both set to None (GH42387)
  * Fixed regression in comparisons between Timestamp object and
    datetime64 objects outside the implementation bounds for
    nanosecond datetime64 (GH42794)
  * Fixed regression in Styler.highlight_min() and Styler.
    highlight_max() where pandas.NA was not successfully ignored
    (GH42650)
  * Fixed regression in concat() where copy=False was not honored
    in axis=1 Series concatenation (GH42501)
  * Regression in Series.nlargest() and Series.nsmallest() with
    nullable integer or float dtype (GH42816)
  * Fixed regression in Series.quantile() with Int64Dtype (GH42626)
  * Fixed regression in Series.groupby() and DataFrame.groupby()
    where supplying the by argument with a Series named with a
    tuple would incorrectly raise (GH42731)
  * Bug in read_excel() modifies the dtypes dictionary when reading
    a file with duplicate columns (GH42462)
  * 1D slices over extension types turn into N-dimensional slices
    over ExtensionArrays (GH42430)
  * Fixed bug in Series.rolling() and DataFrame.rolling() not
    calculating window bounds correctly for the first row when
    center=True and window is an offset that covers all the rows
    (GH42753)
  * Styler.hide_columns() now hides the index name header row as
    well as column headers (GH42101)
  * Styler.set_sticky() has amended CSS to control the column/index
    names and ensure the correct sticky positions (GH42537)
  * Bug in de-serializing datetime indexes in PYTHONOPTIMIZED mode
    (GH42866)

OBS-URL: https://build.opensuse.org/request/show/920383
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-pandas?expand=0&rev=64
2021-09-23 11:26:45 +00:00

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#
# spec file
#
# Copyright (c) 2021 SUSE LLC
#
# All modifications and additions to the file contributed by third parties
# remain the property of their copyright owners, unless otherwise agreed
# upon. The license for this file, and modifications and additions to the
# file, is the same license as for the pristine package itself (unless the
# license for the pristine package is not an Open Source License, in which
# case the license is the MIT License). An "Open Source License" is a
# license that conforms to the Open Source Definition (Version 1.9)
# published by the Open Source Initiative.
# Please submit bugfixes or comments via https://bugs.opensuse.org/
#
%{?!python_module:%define python_module() python3-%{**}}
%define skip_python2 1
%define skip_python36 1
%global flavor @BUILD_FLAVOR@%{nil}
%if "%{flavor}" == "test"
%define psuffix -test
%bcond_without test
%else
%define psuffix %{nil}
%bcond_with test
%endif
Name: python-pandas%{psuffix}
Version: 1.3.3
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
BuildRequires: %{python_module Cython >= 0.29.21}
BuildRequires: %{python_module Jinja2}
BuildRequires: %{python_module devel >= 3.7.1}
BuildRequires: %{python_module numpy >= 1.17.3}
BuildRequires: %{python_module numpy-devel >= 1.16.5}
BuildRequires: %{python_module python-dateutil >= 2.7.3}
BuildRequires: %{python_module pytz >= 2017.3}
BuildRequires: %{python_module setuptools >= 51.0.0}
BuildRequires: fdupes
BuildRequires: gcc-c++
BuildRequires: python-rpm-macros
Requires: python-numpy >= 1.17.3
Requires: python-python-dateutil >= 2.7.3
Requires: python-pytz >= 2017.3
Recommends: python-Bottleneck >= 1.2.1
Recommends: python-numexpr >= 2.6.8
Suggests: python-Jinja2 >= 2.10
Suggests: python-PyMySQL >= 0.8.1
Suggests: python-SQLAlchemy >= 1.3.0
Suggests: python-XlsxWriter >= 1.0.2
Suggests: python-beautifulsoup4 >= 4.6.0
Suggests: python-blosc >= 1.17.0
Suggests: python-fastparquet >= 0.4.0
Suggests: python-fsspec >= 0.7.4
Suggests: python-gcsfs >= 0.6.0
Suggests: python-html5lib >= 1.0.1
Suggests: python-lxml >= 4.3.0
Suggests: python-matplotlib >= 2.2.3
Suggests: python-openpyxl >= 3.0.0
Suggests: python-pandas-gbq >= 0.12.0
Suggests: python-psycopg2 >= 2.7
Suggests: python-pyarrow >= 0.17.0
Suggests: python-pyreadstat
Suggests: python-qt5
Suggests: python-s3fs >= 0.4.0
Suggests: python-scipy >= 1.12.0
Suggests: python-tables >= 3.5.1
Suggests: python-tabulate >= 0.8.7
Suggests: python-xarray >= 0.12.0
Suggests: python-xlrd >= 1.2.0
Suggests: python-xlsb >= 1.0.6
Suggests: python-zlib
Suggests: xclip
Suggests: xsel
Obsoletes: python-pandas-doc < %{version}
Provides: python-pandas-doc = %{version}
%if %{with test}
BuildRequires: %{python_module Bottleneck >= 1.2.1}
BuildRequires: %{python_module SQLAlchemy >= 1.3.0}
BuildRequires: %{python_module XlsxWriter >= 1.0.2}
BuildRequires: %{python_module beautifulsoup4 >= 4.6.0}
BuildRequires: %{python_module hypothesis}
BuildRequires: %{python_module lxml >= 4.3.0}
BuildRequires: %{python_module numexpr >= 2.7.0}
BuildRequires: %{python_module openpyxl >= 3.0.0}
BuildRequires: %{python_module pandas = %{version}}
BuildRequires: %{python_module pytest >= 6.0}
BuildRequires: %{python_module pytest-mock}
BuildRequires: %{python_module pytest-xdist}
BuildRequires: %{python_module xlrd >= 1.2.0}
BuildRequires: xclip
BuildRequires: xvfb-run
%endif
%python_subpackages
%description
Pandas is a Python package providing data structures designed for
working with structured (tabular, multidimensional, potentially
heterogeneous) and time series data. It is a high-level building
block for doing data analysis in Python.
%prep
%if !%{with test}
%setup -q -n pandas-%{version}
%else
%setup -c -n pandas-%{version} -T
cd ..
# unpack only the files we need for testing
tar xf %{SOURCE0} \
pandas-%{version}/pyproject.toml \
pandas-%{version}/pandas/io/formats/templates/html.tpl
sed -i 's/--strict-data-files//' pandas-%{version}/pyproject.toml
%endif
%build
%if !%{with test}
export CFLAGS="%{optflags} -fno-strict-aliasing"
%python_build
%endif
%install
%if !%{with test}
%python_install
%{python_expand sed -i -e 's|"python", "-c",|"%{__$python}", "-c",|' %{buildroot}%{$python_sitearch}/pandas/tests/io/test_compression.py
# don't install devel files
rm -r %{buildroot}%{$python_sitearch}/pandas/_libs/src
rm -r %{buildroot}%{$python_sitearch}/pandas/_libs/tslibs/src
%fdupes %{buildroot}%{$python_sitearch}
}
%endif
%check
%if %{with test}
export LANG=en_US.UTF-8
export LC_ALL=en_US.UTF-8
export PYTHONDONTWRITEBYTECODE=1
# Workaround for pytest-xdist flaky collection order
# https://github.com/pytest-dev/pytest/issues/920
# https://github.com/pytest-dev/pytest/issues/1075
export PYTHONHASHSEED=1
# tries to compile stuff in system sitearch
SKIP_TESTS+=" or test_oo_optimizable"
# dtypes not as expected
# https://github.com/pandas-dev/pandas/issues/39096
# https://github.com/pandas-dev/pandas/issues/36579
SKIP_TESTS+=" or (test_misc and test_memory_usage and series and empty and index)"
# no network -- https://github.com/pandas-dev/pandas/pull/42354
SKIP_TESTS+=" or test_wrong_url"
%ifarch %{ix86}
# overflows on i586
SKIP_TESTS+=" or test_encode_non_c_locale"
# fails on i586 (was gcc10-skip-one-test.patch)
SKIP_TESTS+=" or test_merge_on_ints_floats_warning"
%endif
if [ $(getconf LONG_BIT) -eq 32 ]; then
# https://github.com/pandas-dev/pandas/issues/31856
SKIP_TESTS+=" or test_maybe_promote_int_with_int"
# rounding error
SKIP_TESTS+=" or (test_rolling_quantile_interpolation_options and data1 and linear and 0.1)"
fi
%ifnarch x86_64
# run the slow tests only on x86_64
%define test_fast --skip-slow --skip-db
%endif
%{python_expand $python -c 'import pandas; print(pandas.__path__); print(pandas.show_versions())'
# -n 4: The test collection consumes a lot of memory per worker. Sync with constraints file
# -c pyproject.toml: get the marker declarations
# cache: can't just say no cacheprovider, because one test checks for the --lf option of pytest-cache
# --skip-* arguments: Upstreams custom way to skip marked tests. These do not use pytest.mark.
# clipboard marker: not set up properly in build service
# need to specify test path directly instead of --pyargs pandas in order
# to find all conftest.py files https://github.com/pytest-dev/pytest/issues/1596
xvfb-run pytest-%{$python_bin_suffix} -v -n 4 \
-c pyproject.toml \
-o cache_dir=$PWD/.pytest_cache --cache-clear \
--skip-network %{?test_fast} \
-m "not clipboard" \
-k "not (${SKIP_TESTS:4})" \
%{$python_sitearch}/pandas
}
%endif
%if !%{with test}
%files %{python_files}
%license LICENSE
%doc README.md RELEASE.md
%{python_sitearch}/pandas/
%{python_sitearch}/pandas-%{version}*-info
%endif
%changelog
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