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222 lines
9.2 KiB
Bash
222 lines
9.2 KiB
Bash
# Copyright 1999-2025 Gentoo Authors
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# Distributed under the terms of the GNU General Public License v2
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EAPI=8
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DISTUTILS_EXT=1
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DISTUTILS_USE_PEP517=meson-python
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PYTHON_COMPAT=( python3_{11..14} )
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PYTHON_REQ_USE="threads(+)"
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VIRTUALX_REQUIRED="manual"
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inherit distutils-r1 optfeature pypi toolchain-funcs virtualx
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DESCRIPTION="Powerful data structures for data analysis and statistics"
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HOMEPAGE="
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https://pandas.pydata.org/
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https://github.com/pandas-dev/pandas/
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https://pypi.org/project/pandas/
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"
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LICENSE="BSD"
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SLOT="0"
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KEYWORDS="~amd64 ~arm64 ~riscv ~x86"
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IUSE="big-endian full-support minimal test X"
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RESTRICT="!test? ( test )"
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RECOMMENDED_DEPEND="
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>=dev-python/bottleneck-1.3.4[${PYTHON_USEDEP}]
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>=dev-python/numexpr-2.8.0[${PYTHON_USEDEP}]
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"
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# TODO: add pandas-gbq to the tree
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# TODO: Re-add dev-python/statsmodel[python3_11] dep once it supports python3_11
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# https://github.com/statsmodels/statsmodels/issues/8287
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OPTIONAL_DEPEND="
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>=dev-python/beautifulsoup4-4.14.2[${PYTHON_USEDEP}]
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dev-python/blosc[${PYTHON_USEDEP}]
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>=dev-python/html5lib-1.1[${PYTHON_USEDEP}]
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>=dev-python/jinja2-3.1.2[${PYTHON_USEDEP}]
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>=dev-python/lxml-4.8.0[${PYTHON_USEDEP}]
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>=dev-python/matplotlib-3.6.1[${PYTHON_USEDEP}]
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>=dev-python/openpyxl-3.0.7[${PYTHON_USEDEP}]
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>=dev-python/sqlalchemy-1.4.36[${PYTHON_USEDEP}]
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>=dev-python/tabulate-0.8.10[${PYTHON_USEDEP}]
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>=dev-python/xarray-2022.3.0[${PYTHON_USEDEP}]
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>=dev-python/xlrd-2.0.1[${PYTHON_USEDEP}]
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>=dev-python/xlsxwriter-3.0.3[${PYTHON_USEDEP}]
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>=dev-python/xlwt-1.3.0[${PYTHON_USEDEP}]
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!arm? ( !hppa? ( !ppc? ( !x86? (
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>=dev-python/scipy-1.8.1[${PYTHON_USEDEP}]
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dev-python/statsmodels[${PYTHON_USEDEP}]
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) ) ) )
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!big-endian? (
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>=dev-python/tables-3.7.0[${PYTHON_USEDEP}]
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)
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X? (
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|| (
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>=dev-python/pyqt5-5.15.6[${PYTHON_USEDEP}]
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>=dev-python/qtpy-2.2.0[${PYTHON_USEDEP}]
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x11-misc/xclip
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x11-misc/xsel
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)
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)
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"
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DEPEND="
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>=dev-python/numpy-1.23.2:=[${PYTHON_USEDEP}]
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"
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COMMON_DEPEND="
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${DEPEND}
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>=dev-python/python-dateutil-2.8.2[${PYTHON_USEDEP}]
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>=dev-python/pytz-2020.1[${PYTHON_USEDEP}]
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"
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BDEPEND="
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${COMMON_DEPEND}
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>=dev-build/meson-1.2.1
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>=dev-python/cython-3.0.5[${PYTHON_USEDEP}]
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>=dev-python/versioneer-0.28[${PYTHON_USEDEP}]
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test? (
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${VIRTUALX_DEPEND}
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${RECOMMENDED_DEPEND}
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${OPTIONAL_DEPEND}
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dev-libs/apache-arrow[brotli,parquet,snappy]
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>=dev-python/beautifulsoup4-4.14.2[${PYTHON_USEDEP}]
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>=dev-python/hypothesis-6.46.1[${PYTHON_USEDEP}]
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>=dev-python/openpyxl-3.0.10[${PYTHON_USEDEP}]
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>=dev-python/pyarrow-10.0.1[parquet,${PYTHON_USEDEP}]
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>=dev-python/pymysql-1.0.2[${PYTHON_USEDEP}]
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>=dev-python/xlsxwriter-3.0.3[${PYTHON_USEDEP}]
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x11-misc/xclip
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x11-misc/xsel
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)
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"
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RDEPEND="
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${COMMON_DEPEND}
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dev-python/tzdata[${PYTHON_USEDEP}]
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!minimal? ( ${RECOMMENDED_DEPEND} )
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full-support? ( ${OPTIONAL_DEPEND} )
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"
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EPYTEST_PLUGINS=()
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EPYTEST_XDIST=1
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distutils_enable_tests pytest
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PATCHES=(
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# https://github.com/pandas-dev/pandas/pull/61331/commits/12b1d00622ffc8b99986da2f4478cc2df4da213a
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# (partially applied to 2.3.1, sigh)
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"${FILESDIR}/${PN}-2.3.1-xarray-test.patch"
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)
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src_test() {
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virtx distutils-r1_src_test
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}
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python_test() {
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# Note; deselects relative to pandas/
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local EPYTEST_DESELECT=(
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# test for rounding errors, fails if we have better precision
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# e.g. on amd64 with FMA or on arm64
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# https://github.com/pandas-dev/pandas/issues/38921
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tests/window/test_rolling.py::test_rolling_var_numerical_issues
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# TODO: missing data not covered by --no-strict-data-files?
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tests/io/xml/test_xml.py::test_empty_stylesheet
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tests/io/xml/test_xml.py::test_wrong_file_path
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# deprecation warning
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'tests/computation/test_eval.py::TestEval::test_scalar_unary[numexpr-pandas]'
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# requires -Werror
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tests/tslibs/test_to_offset.py::test_to_offset_lowercase_frequency_deprecated
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tests/tslibs/test_to_offset.py::test_to_offset_uppercase_frequency_deprecated
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tests/copy_view/test_array.py::test_dataframe_multiple_numpy_dtypes
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# probably pytz, doesn't happen on main (where zoneinfo is used)
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'tests/arrays/test_array.py::test_array_inference[data7-expected7]'
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# random warning regressions?!
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tests/test_expressions.py::TestExpressions::test_bool_ops_warn_on_arithmetic
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'tests/series/test_arithmetic.py::TestSeriesArithmetic::test_add_list_to_masked_array_boolean[numexpr]'
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'tests/frame/test_arithmetic.py::TestFrameArithmetic::test_binop_other[numexpr-add-True-bool]'
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'tests/frame/test_arithmetic.py::TestFrameArithmetic::test_binop_other[numexpr-mul-True-bool]'
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)
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if ! tc-has-64bit-time_t; then
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EPYTEST_DESELECT+=(
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# Needs 64-bit time_t (TODO: split into 32-bit arch only section)
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tests/tseries/offsets/test_year.py::test_add_out_of_pydatetime_range
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'tests/tseries/offsets/test_common.py::test_apply_out_of_range[tzlocal()-BusinessDay]'
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'tests/tseries/offsets/test_common.py::test_apply_out_of_range[tzlocal()-BusinessHour]'
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'tests/tseries/offsets/test_common.py::test_apply_out_of_range[tzlocal()-BusinessMonthEnd]'
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'tests/tseries/offsets/test_common.py::test_apply_out_of_range[tzlocal()-BusinessMonthBegin]'
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'tests/tseries/offsets/test_common.py::test_apply_out_of_range[tzlocal()-BQuarterEnd]'
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'tests/tseries/offsets/test_common.py::test_apply_out_of_range[tzlocal()-BQuarterBegin]'
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'tests/tseries/offsets/test_common.py::test_apply_out_of_range[tzlocal()-CustomBusinessDay]'
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'tests/tseries/offsets/test_common.py::test_apply_out_of_range[tzlocal()-CustomBusinessHour]'
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'tests/tseries/offsets/test_common.py::test_apply_out_of_range[tzlocal()-CustomBusinessMonthEnd]'
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'tests/tseries/offsets/test_common.py::test_apply_out_of_range[tzlocal()-CustomBusinessMonthBegin]'
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'tests/tseries/offsets/test_common.py::test_apply_out_of_range[tzlocal()-MonthEnd]'
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'tests/tseries/offsets/test_common.py::test_apply_out_of_range[tzlocal()-MonthBegin]'
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'tests/tseries/offsets/test_common.py::test_apply_out_of_range[tzlocal()-SemiMonthBegin]'
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'tests/tseries/offsets/test_common.py::test_apply_out_of_range[tzlocal()-SemiMonthEnd]'
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'tests/tseries/offsets/test_common.py::test_apply_out_of_range[tzlocal()-QuarterEnd]'
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'tests/tseries/offsets/test_common.py::test_apply_out_of_range[tzlocal()-LastWeekOfMonth]'
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'tests/tseries/offsets/test_common.py::test_apply_out_of_range[tzlocal()-WeekOfMonth]'
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'tests/tseries/offsets/test_common.py::test_apply_out_of_range[tzlocal()-Week]'
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)
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fi
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if ! has_version "dev-python/scipy[${PYTHON_USEDEP}]"; then
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EPYTEST_DESELECT+=(
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tests/plotting/test_misc.py::test_savefig
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)
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fi
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case ${EPYTHON} in
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python3.14)
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EPYTEST_DESELECT+=(
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'tests/computation/test_eval.py::TestEval::test_simple_cmp_ops[float-float-numexpr-pandas-in]'
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'tests/computation/test_eval.py::TestEval::test_simple_cmp_ops[float-float-numexpr-pandas-not in]'
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'tests/computation/test_eval.py::TestEval::test_simple_cmp_ops[float-float-python-pandas-in]'
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'tests/computation/test_eval.py::TestEval::test_simple_cmp_ops[float-float-python-pandas-not in]'
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'tests/computation/test_eval.py::TestEval::test_compound_invert_op[float-float-numexpr-pandas-in]'
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'tests/computation/test_eval.py::TestEval::test_compound_invert_op[float-float-numexpr-pandas-not in]'
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'tests/computation/test_eval.py::TestEval::test_compound_invert_op[float-float-python-pandas-in]'
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'tests/computation/test_eval.py::TestEval::test_compound_invert_op[float-float-python-pandas-not in]'
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'tests/computation/test_eval.py::TestOperations::test_simple_arith_ops[numexpr-pandas]'
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'tests/computation/test_eval.py::TestOperations::test_simple_arith_ops[python-pandas]'
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)
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;;
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esac
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local -x LC_ALL=C.UTF-8
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cd "${BUILD_DIR}/install$(python_get_sitedir)" || die
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"${EPYTHON}" -c "import pandas; pandas.show_versions()" || die
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# nonfatal from virtx
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# --no-strict-data-files is necessary since upstream prevents data
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# files from even being included in GitHub archives, sigh
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# https://github.com/pandas-dev/pandas/issues/54907
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nonfatal epytest pandas/tests \
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--no-strict-data-files -o xfail_strict=false \
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-m "not single_cpu and not slow and not network and not db" ||
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die "Tests failed with ${EPYTHON}"
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rm test_stata.dta || die
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}
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pkg_postinst() {
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optfeature "accelerating certain types of NaN evaluations, using specialized cython routines to achieve large speedups." dev-python/bottleneck
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optfeature "accelerating certain numerical operations, using multiple cores as well as smart chunking and caching to achieve large speedups" ">=dev-python/numexpr-2.1"
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optfeature "needed for pandas.io.html.read_html" dev-python/beautifulsoup4 dev-python/html5lib dev-python/lxml
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optfeature "for msgpack compression using blosc" dev-python/blosc
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optfeature "Template engine for conditional HTML formatting" dev-python/jinja2
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optfeature "Plotting support" dev-python/matplotlib
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optfeature "Needed for Excel I/O" ">=dev-python/openpyxl-3.0.10" dev-python/xlsxwriter dev-python/xlrd dev-python/xlwt
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optfeature "necessary for HDF5-based storage" ">=dev-python/tables-3.7.0"
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optfeature "R I/O support" dev-python/rpy2
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optfeature "Needed for parts of pandas.stats" dev-python/statsmodels
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optfeature "SQL database support" ">=dev-python/sqlalchemy-1.4.36"
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optfeature "miscellaneous statistical functions" dev-python/scipy
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optfeature "necessary to use pandas.io.clipboard.read_clipboard support" dev-python/pyqt5 dev-python/qtpy x11-misc/xclip x11-misc/xsel
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}
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