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code_checks.sh
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#!/bin/bash
#
# Run checks related to code quality.
#
# This script is intended for both the CI and to check locally that code standards are
# respected. We run doctests here (currently some files only), and we
# validate formatting error in docstrings.
#
# Usage:
# $ ./ci/code_checks.sh # run all checks
# $ ./ci/code_checks.sh code # checks on imported code
# $ ./ci/code_checks.sh doctests # run doctests
# $ ./ci/code_checks.sh docstrings # validate docstring errors
# $ ./ci/code_checks.sh single-docs # check single-page docs build warning-free
# $ ./ci/code_checks.sh notebooks # check execution of documentation notebooks
[[ -z "$1" || "$1" == "code" || "$1" == "doctests" || "$1" == "docstrings" || "$1" == "single-docs" || "$1" == "notebooks" ]] || \
{ echo "Unknown command $1. Usage: $0 [code|doctests|docstrings|single-docs|notebooks]"; exit 9999; }
BASE_DIR="$(dirname $0)/.."
RET=0
CHECK=$1
function invgrep {
# grep with inverse exist status and formatting for azure-pipelines
#
# This function works exactly as grep, but with opposite exit status:
# - 0 (success) when no patterns are found
# - 1 (fail) when the patterns are found
#
# This is useful for the CI, as we want to fail if one of the patterns
# that we want to avoid is found by grep.
grep -n "$@" | sed "s/^/$INVGREP_PREPEND/" | sed "s/$/$INVGREP_APPEND/" ; EXIT_STATUS=${PIPESTATUS[0]}
return $((! $EXIT_STATUS))
}
if [[ "$GITHUB_ACTIONS" == "true" ]]; then
INVGREP_PREPEND="##[error]"
fi
### CODE ###
if [[ -z "$CHECK" || "$CHECK" == "code" ]]; then
MSG='Check import. No warnings, and blocklist some optional dependencies' ; echo $MSG
python -W error -c "
import sys
import pandas
blocklist = {'bs4', 'gcsfs', 'html5lib', 'http', 'ipython', 'jinja2', 'hypothesis',
'lxml', 'matplotlib', 'openpyxl', 'py', 'pytest', 's3fs', 'scipy',
'tables', 'urllib.request', 'xlrd', 'xlsxwriter'}
# GH#28227 for some of these check for top-level modules, while others are
# more specific (e.g. urllib.request)
import_mods = set(m.split('.')[0] for m in sys.modules) | set(sys.modules)
mods = blocklist & import_mods
if mods:
sys.stderr.write('err: pandas should not import: {}\n'.format(', '.join(mods)))
sys.exit(len(mods))
"
RET=$(($RET + $?)) ; echo $MSG "DONE"
fi
### DOCTESTS ###
if [[ -z "$CHECK" || "$CHECK" == "doctests" ]]; then
MSG='Python and Cython Doctests' ; echo $MSG
python -c 'import pandas as pd; pd.test(run_doctests=True)'
RET=$(($RET + $?)) ; echo $MSG "DONE"
fi
### DOCSTRINGS ###
if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
MSG='Validate docstrings (EX02, EX04, GL01, GL02, GL03, GL04, GL05, GL06, GL07, GL09, GL10, PR03, PR04, PR05, PR06, PR08, PR09, PR10, RT01, RT02, RT04, RT05, SA02, SA03, SA04, SS01, SS02, SS03, SS04, SS05, SS06)' ; echo $MSG
$BASE_DIR/scripts/validate_docstrings.py --format=actions --errors=EX02,EX04,GL01,GL02,GL03,GL04,GL05,GL06,GL07,GL09,GL10,PR03,PR04,PR05,PR06,PR08,PR09,PR10,RT01,RT02,RT04,RT05,SA02,SA03,SA04,SS01,SS02,SS03,SS04,SS05,SS06
RET=$(($RET + $?)) ; echo $MSG "DONE"
MSG='Partially validate docstrings (EX01)' ; echo $MSG
$BASE_DIR/scripts/validate_docstrings.py --format=actions --errors=EX01 --ignore_functions \
pandas.Series.backfill \
pandas.Series.pad \
pandas.Series.hist \
pandas.errors.AccessorRegistrationWarning \
pandas.errors.AttributeConflictWarning \
pandas.errors.DataError \
pandas.errors.IncompatibilityWarning \
pandas.errors.InvalidComparison \
pandas.errors.IntCastingNaNError \
pandas.errors.LossySetitemError \
pandas.errors.MergeError \
pandas.errors.NoBufferPresent \
pandas.errors.NullFrequencyError \
pandas.errors.NumbaUtilError \
pandas.errors.OptionError \
pandas.errors.OutOfBoundsDatetime \
pandas.errors.OutOfBoundsTimedelta \
pandas.errors.ParserError \
pandas.errors.PerformanceWarning \
pandas.errors.PyperclipException \
pandas.errors.PyperclipWindowsException \
pandas.errors.UnsortedIndexError \
pandas.errors.UnsupportedFunctionCall \
pandas.test \
pandas.NaT \
pandas.read_clipboard \
pandas.ExcelFile \
pandas.ExcelFile.parse \
pandas.io.formats.style.Styler.to_html \
pandas.HDFStore.groups \
pandas.HDFStore.walk \
pandas.read_feather \
pandas.DataFrame.to_feather \
pandas.read_parquet \
pandas.read_orc \
pandas.read_sas \
pandas.read_spss \
pandas.read_sql_query \
pandas.read_gbq \
pandas.io.stata.StataReader.data_label \
pandas.io.stata.StataReader.value_labels \
pandas.io.stata.StataReader.variable_labels \
pandas.io.stata.StataWriter.write_file \
pandas.core.resample.Resampler.__iter__ \
pandas.core.resample.Resampler.groups \
pandas.core.resample.Resampler.indices \
pandas.core.resample.Resampler.get_group \
pandas.core.resample.Resampler.ffill \
pandas.core.resample.Resampler.asfreq \
pandas.core.resample.Resampler.count \
pandas.core.resample.Resampler.nunique \
pandas.core.resample.Resampler.max \
pandas.core.resample.Resampler.mean \
pandas.core.resample.Resampler.median \
pandas.core.resample.Resampler.min \
pandas.core.resample.Resampler.ohlc \
pandas.core.resample.Resampler.prod \
pandas.core.resample.Resampler.size \
pandas.core.resample.Resampler.sem \
pandas.core.resample.Resampler.std \
pandas.core.resample.Resampler.sum \
pandas.core.resample.Resampler.var \
pandas.core.resample.Resampler.quantile \
pandas.describe_option \
pandas.reset_option \
pandas.get_option \
pandas.set_option \
pandas.plotting.deregister_matplotlib_converters \
pandas.plotting.plot_params \
pandas.plotting.register_matplotlib_converters \
pandas.plotting.table \
pandas.util.hash_array \
pandas.util.hash_pandas_object \
pandas_object \
pandas.api.interchange.from_dataframe \
pandas.Index.asof_locs \
pandas.Index.get_slice_bound \
pandas.RangeIndex \
pandas.RangeIndex.start \
pandas.RangeIndex.stop \
pandas.RangeIndex.step \
pandas.RangeIndex.from_range \
pandas.CategoricalIndex.codes \
pandas.CategoricalIndex.categories \
pandas.CategoricalIndex.ordered \
pandas.CategoricalIndex.reorder_categories \
pandas.CategoricalIndex.set_categories \
pandas.CategoricalIndex.as_ordered \
pandas.CategoricalIndex.as_unordered \
pandas.CategoricalIndex.equals \
pandas.IntervalIndex.values \
pandas.IntervalIndex.to_tuples \
pandas.MultiIndex.dtypes \
pandas.MultiIndex.drop \
pandas.DatetimeIndex.snap \
pandas.DatetimeIndex.as_unit \
pandas.DatetimeIndex.to_pydatetime \
pandas.DatetimeIndex.to_series \
pandas.DatetimeIndex.mean \
pandas.DatetimeIndex.std \
pandas.TimedeltaIndex \
pandas.core.window.rolling.Rolling.max \
pandas.core.window.rolling.Rolling.cov \
pandas.core.window.rolling.Rolling.skew \
pandas.core.window.rolling.Rolling.apply \
pandas.core.window.rolling.Window.mean \
pandas.core.window.rolling.Window.sum \
pandas.core.window.rolling.Window.var \
pandas.core.window.rolling.Window.std \
pandas.core.window.expanding.Expanding.count \
pandas.core.window.expanding.Expanding.sum \
pandas.core.window.expanding.Expanding.mean \
pandas.core.window.expanding.Expanding.median \
pandas.core.window.expanding.Expanding.min \
pandas.core.window.expanding.Expanding.max \
pandas.core.window.expanding.Expanding.corr \
pandas.core.window.expanding.Expanding.cov \
pandas.core.window.expanding.Expanding.skew \
pandas.core.window.expanding.Expanding.apply \
pandas.core.window.expanding.Expanding.quantile \
pandas.core.window.ewm.ExponentialMovingWindow.mean \
pandas.core.window.ewm.ExponentialMovingWindow.sum \
pandas.core.window.ewm.ExponentialMovingWindow.std \
pandas.core.window.ewm.ExponentialMovingWindow.var \
pandas.core.window.ewm.ExponentialMovingWindow.corr \
pandas.core.window.ewm.ExponentialMovingWindow.cov \
pandas.api.indexers.BaseIndexer \
pandas.api.indexers.VariableOffsetWindowIndexer \
pandas.io.formats.style.Styler \
pandas.io.formats.style.Styler.from_custom_template \
pandas.io.formats.style.Styler.set_caption \
pandas.io.formats.style.Styler.set_sticky \
pandas.io.formats.style.Styler.set_uuid \
pandas.io.formats.style.Styler.clear \
pandas.io.formats.style.Styler.highlight_null \
pandas.io.formats.style.Styler.highlight_max \
pandas.io.formats.style.Styler.highlight_min \
pandas.io.formats.style.Styler.bar \
pandas.io.formats.style.Styler.to_string \
pandas.api.extensions.ExtensionDtype \
pandas.api.extensions.ExtensionArray \
pandas.arrays.PandasArray \
pandas.api.extensions.ExtensionArray._accumulate \
pandas.api.extensions.ExtensionArray._concat_same_type \
pandas.api.extensions.ExtensionArray._formatter \
pandas.api.extensions.ExtensionArray._from_factorized \
pandas.api.extensions.ExtensionArray._from_sequence \
pandas.api.extensions.ExtensionArray._from_sequence_of_strings \
pandas.api.extensions.ExtensionArray._hash_pandas_object \
pandas.api.extensions.ExtensionArray._reduce \
pandas.api.extensions.ExtensionArray._values_for_argsort \
pandas.api.extensions.ExtensionArray._values_for_factorize \
pandas.api.extensions.ExtensionArray.argsort \
pandas.api.extensions.ExtensionArray.astype \
pandas.api.extensions.ExtensionArray.copy \
pandas.api.extensions.ExtensionArray.view \
pandas.api.extensions.ExtensionArray.dropna \
pandas.api.extensions.ExtensionArray.equals \
pandas.api.extensions.ExtensionArray.factorize \
pandas.api.extensions.ExtensionArray.fillna \
pandas.api.extensions.ExtensionArray.insert \
pandas.api.extensions.ExtensionArray.interpolate \
pandas.api.extensions.ExtensionArray.isin \
pandas.api.extensions.ExtensionArray.isna \
pandas.api.extensions.ExtensionArray.ravel \
pandas.api.extensions.ExtensionArray.searchsorted \
pandas.api.extensions.ExtensionArray.shift \
pandas.api.extensions.ExtensionArray.unique \
pandas.api.extensions.ExtensionArray.dtype \
pandas.api.extensions.ExtensionArray.nbytes \
pandas.api.extensions.ExtensionArray.ndim \
pandas.api.extensions.ExtensionArray.shape \
pandas.api.extensions.ExtensionArray.tolist \
pandas.DataFrame.columns \
pandas.DataFrame.backfill \
pandas.DataFrame.ffill \
pandas.DataFrame.pad \
pandas.DataFrame.swapaxes \
pandas.DataFrame.attrs \
pandas.DataFrame.plot \
pandas.DataFrame.to_gbq \
pandas.DataFrame.style \
pandas.DataFrame.__dataframe__
RET=$(($RET + $?)) ; echo $MSG "DONE"
fi
### DOCUMENTATION NOTEBOOKS ###
if [[ -z "$CHECK" || "$CHECK" == "notebooks" ]]; then
MSG='Notebooks' ; echo $MSG
jupyter nbconvert --execute $(find doc/source -name '*.ipynb') --to notebook
RET=$(($RET + $?)) ; echo $MSG "DONE"
fi
### SINGLE-PAGE DOCS ###
if [[ -z "$CHECK" || "$CHECK" == "single-docs" ]]; then
python doc/make.py --warnings-are-errors --single pandas.Series.value_counts
python doc/make.py --warnings-are-errors --single pandas.Series.str.split
python doc/make.py clean
fi
exit $RET