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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
set -uo pipefail
if [[ -v 1 ]]; then
CHECK=$1
else
# script will fail if it uses an unset variable (i.e. $1 is not provided)
CHECK=""
fi
[[ -z "$CHECK" || "$CHECK" == "code" || "$CHECK" == "doctests" || "$CHECK" == "docstrings" || "$CHECK" == "single-docs" || "$CHECK" == "notebooks" ]] || \
{ echo "Unknown command $1. Usage: $0 [code|doctests|docstrings|single-docs|notebooks]"; exit 9999; }
BASE_DIR="$(dirname $0)/.."
RET=0
### CODE ###
if [[ -z "$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' ; echo $MSG
$BASE_DIR/scripts/validate_docstrings.py \
--format=actions \
-i ES01 `# For now it is ok if docstrings are missing the extended summary` \
-i "pandas.Series.dt PR01" `# Accessors are implemented as classes, but we do not document the Parameters section` \
-i "pandas.DataFrame.at_time PR01" \
-i "pandas.DataFrame.max RT03" \
-i "pandas.DataFrame.mean RT03,SA01" \
-i "pandas.DataFrame.median RT03,SA01" \
-i "pandas.DataFrame.min RT03" \
-i "pandas.DataFrame.plot PR02,SA01" \
-i "pandas.DataFrame.prod RT03" \
-i "pandas.DataFrame.product RT03" \
-i "pandas.DataFrame.sem PR01,RT03,SA01" \
-i "pandas.DataFrame.skew RT03,SA01" \
-i "pandas.DataFrame.sparse PR01" \
-i "pandas.DataFrame.std PR01,RT03,SA01" \
-i "pandas.DataFrame.sum RT03" \
-i "pandas.DataFrame.swaplevel SA01" \
-i "pandas.DataFrame.to_markdown SA01" \
-i "pandas.DataFrame.var PR01,RT03,SA01" \
-i "pandas.Grouper PR02" \
-i "pandas.Index PR07" \
-i "pandas.Index.append PR07,RT03,SA01" \
-i "pandas.Index.difference PR07,RT03,SA01" \
-i "pandas.Index.get_indexer PR07,SA01" \
-i "pandas.Index.get_indexer_for PR01,SA01" \
-i "pandas.Index.get_indexer_non_unique PR07,SA01" \
-i "pandas.Index.get_loc PR07,RT03,SA01" \
-i "pandas.Index.names GL08" \
-i "pandas.Index.putmask PR01,RT03" \
-i "pandas.Index.ravel PR01,RT03" \
-i "pandas.Index.str PR01,SA01" \
-i "pandas.Index.view GL08" \
-i "pandas.Int16Dtype SA01" \
-i "pandas.Int32Dtype SA01" \
-i "pandas.Int64Dtype SA01" \
-i "pandas.Int8Dtype SA01" \
-i "pandas.Interval PR02" \
-i "pandas.Interval.closed SA01" \
-i "pandas.Interval.left SA01" \
-i "pandas.Interval.mid SA01" \
-i "pandas.Interval.right SA01" \
-i "pandas.IntervalDtype PR01,SA01" \
-i "pandas.IntervalDtype.subtype SA01" \
-i "pandas.IntervalIndex.closed SA01" \
-i "pandas.IntervalIndex.contains RT03" \
-i "pandas.IntervalIndex.get_indexer PR07,SA01" \
-i "pandas.IntervalIndex.get_loc PR07,RT03,SA01" \
-i "pandas.IntervalIndex.is_non_overlapping_monotonic SA01" \
-i "pandas.IntervalIndex.left GL08" \
-i "pandas.IntervalIndex.length GL08" \
-i "pandas.IntervalIndex.mid GL08" \
-i "pandas.IntervalIndex.right GL08" \
-i "pandas.IntervalIndex.set_closed RT03,SA01" \
-i "pandas.IntervalIndex.to_tuples RT03,SA01" \
-i "pandas.MultiIndex PR01" \
-i "pandas.MultiIndex.append PR07,SA01" \
-i "pandas.MultiIndex.copy PR07,RT03,SA01" \
-i "pandas.MultiIndex.drop PR07,RT03,SA01" \
-i "pandas.MultiIndex.dtypes SA01" \
-i "pandas.MultiIndex.get_indexer PR07,SA01" \
-i "pandas.MultiIndex.get_level_values SA01" \
-i "pandas.MultiIndex.get_loc PR07" \
-i "pandas.MultiIndex.get_loc_level PR07" \
-i "pandas.MultiIndex.levels SA01" \
-i "pandas.MultiIndex.levshape SA01" \
-i "pandas.MultiIndex.names SA01" \
-i "pandas.MultiIndex.nlevels SA01" \
-i "pandas.MultiIndex.remove_unused_levels RT03,SA01" \
-i "pandas.MultiIndex.reorder_levels RT03,SA01" \
-i "pandas.MultiIndex.set_codes SA01" \
-i "pandas.MultiIndex.set_levels RT03,SA01" \
-i "pandas.MultiIndex.sortlevel PR07,SA01" \
-i "pandas.MultiIndex.to_frame RT03" \
-i "pandas.MultiIndex.truncate SA01" \
-i "pandas.NA SA01" \
-i "pandas.NaT SA01" \
-i "pandas.NamedAgg SA01" \
-i "pandas.Period SA01" \
-i "pandas.Period.asfreq SA01" \
-i "pandas.Period.freq GL08" \
-i "pandas.Period.freqstr SA01" \
-i "pandas.Period.is_leap_year SA01" \
-i "pandas.Period.month SA01" \
-i "pandas.Period.now SA01" \
-i "pandas.Period.ordinal GL08" \
-i "pandas.Period.quarter SA01" \
-i "pandas.Period.strftime PR01,SA01" \
-i "pandas.Period.to_timestamp SA01" \
-i "pandas.Period.year SA01" \
-i "pandas.PeriodDtype SA01" \
-i "pandas.PeriodDtype.freq SA01" \
-i "pandas.PeriodIndex.day SA01" \
-i "pandas.PeriodIndex.day_of_week SA01" \
-i "pandas.PeriodIndex.day_of_year SA01" \
-i "pandas.PeriodIndex.dayofweek SA01" \
-i "pandas.PeriodIndex.dayofyear SA01" \
-i "pandas.PeriodIndex.days_in_month SA01" \
-i "pandas.PeriodIndex.daysinmonth SA01" \
-i "pandas.PeriodIndex.from_fields PR07,SA01" \
-i "pandas.PeriodIndex.from_ordinals SA01" \
-i "pandas.PeriodIndex.hour SA01" \
-i "pandas.PeriodIndex.is_leap_year SA01" \
-i "pandas.PeriodIndex.minute SA01" \
-i "pandas.PeriodIndex.month SA01" \
-i "pandas.PeriodIndex.quarter SA01" \
-i "pandas.PeriodIndex.qyear GL08" \
-i "pandas.PeriodIndex.second SA01" \
-i "pandas.PeriodIndex.to_timestamp RT03,SA01" \
-i "pandas.PeriodIndex.week SA01" \
-i "pandas.PeriodIndex.weekday SA01" \
-i "pandas.PeriodIndex.weekofyear SA01" \
-i "pandas.PeriodIndex.year SA01" \
-i "pandas.RangeIndex PR07" \
-i "pandas.RangeIndex.from_range PR01,SA01" \
-i "pandas.RangeIndex.start SA01" \
-i "pandas.RangeIndex.step SA01" \
-i "pandas.RangeIndex.stop SA01" \
-i "pandas.Series SA01" \
-i "pandas.Series.__iter__ RT03,SA01" \
-i "pandas.Series.add PR07" \
-i "pandas.Series.at_time PR01" \
-i "pandas.Series.backfill PR01,SA01" \
-i "pandas.Series.case_when RT03" \
-i "pandas.Series.cat PR07,SA01" \
-i "pandas.Series.cat.add_categories PR01,PR02" \
-i "pandas.Series.cat.as_ordered PR01" \
-i "pandas.Series.cat.as_unordered PR01" \
-i "pandas.Series.cat.codes SA01" \
-i "pandas.Series.cat.remove_categories PR01,PR02" \
-i "pandas.Series.cat.remove_unused_categories PR01" \
-i "pandas.Series.cat.rename_categories PR01,PR02" \
-i "pandas.Series.cat.reorder_categories PR01,PR02" \
-i "pandas.Series.cat.set_categories PR01,PR02" \
-i "pandas.Series.div PR07" \
-i "pandas.Series.dt.as_unit PR01,PR02" \
-i "pandas.Series.dt.ceil PR01,PR02" \
-i "pandas.Series.dt.components SA01" \
-i "pandas.Series.dt.day_name PR01,PR02" \
-i "pandas.Series.dt.days SA01" \
-i "pandas.Series.dt.days_in_month SA01" \
-i "pandas.Series.dt.daysinmonth SA01" \
-i "pandas.Series.dt.floor PR01,PR02" \
-i "pandas.Series.dt.freq GL08" \
-i "pandas.Series.dt.microseconds SA01" \
-i "pandas.Series.dt.month_name PR01,PR02" \
-i "pandas.Series.dt.nanoseconds SA01" \
-i "pandas.Series.dt.normalize PR01" \
-i "pandas.Series.dt.qyear GL08" \
-i "pandas.Series.dt.round PR01,PR02" \
-i "pandas.Series.dt.seconds SA01" \
-i "pandas.Series.dt.strftime PR01,PR02" \
-i "pandas.Series.dt.to_period PR01,PR02" \
-i "pandas.Series.dt.total_seconds PR01" \
-i "pandas.Series.dt.tz_convert PR01,PR02" \
-i "pandas.Series.dt.tz_localize PR01,PR02" \
-i "pandas.Series.dt.unit GL08" \
-i "pandas.Series.dtype SA01" \
-i "pandas.Series.eq PR07,SA01" \
-i "pandas.Series.floordiv PR07" \
-i "pandas.Series.ge PR07,SA01" \
-i "pandas.Series.gt PR07,SA01" \
-i "pandas.Series.hasnans SA01" \
-i "pandas.Series.is_monotonic_decreasing SA01" \
-i "pandas.Series.is_monotonic_increasing SA01" \
-i "pandas.Series.is_unique SA01" \
-i "pandas.Series.kurt RT03,SA01" \
-i "pandas.Series.kurtosis RT03,SA01" \
-i "pandas.Series.le PR07,SA01" \
-i "pandas.Series.list.__getitem__ SA01" \
-i "pandas.Series.list.flatten SA01" \
-i "pandas.Series.list.len SA01" \
-i "pandas.Series.lt PR07,SA01" \
-i "pandas.Series.max RT03" \
-i "pandas.Series.mean RT03,SA01" \
-i "pandas.Series.median RT03,SA01" \
-i "pandas.Series.min RT03" \
-i "pandas.Series.mod PR07" \
-i "pandas.Series.mode SA01" \
-i "pandas.Series.mul PR07" \
-i "pandas.Series.ne PR07,SA01" \
-i "pandas.Series.pad PR01,SA01" \
-i "pandas.Series.plot PR02,SA01" \
-i "pandas.Series.pop RT03,SA01" \
-i "pandas.Series.pow PR07" \
-i "pandas.Series.prod RT03" \
-i "pandas.Series.product RT03" \
-i "pandas.Series.radd PR07" \
-i "pandas.Series.rdiv PR07" \
-i "pandas.Series.reorder_levels RT03,SA01" \
-i "pandas.Series.rfloordiv PR07" \
-i "pandas.Series.rmod PR07" \
-i "pandas.Series.rmul PR07" \
-i "pandas.Series.rpow PR07" \
-i "pandas.Series.rsub PR07" \
-i "pandas.Series.rtruediv PR07" \
-i "pandas.Series.sem PR01,RT03,SA01" \
-i "pandas.Series.shape SA01" \
-i "pandas.Series.skew RT03,SA01" \
-i "pandas.Series.sparse PR01,SA01" \
-i "pandas.Series.sparse.density SA01" \
-i "pandas.Series.sparse.fill_value SA01" \
-i "pandas.Series.sparse.from_coo PR07,SA01" \
-i "pandas.Series.sparse.npoints SA01" \
-i "pandas.Series.sparse.sp_values SA01" \
-i "pandas.Series.sparse.to_coo PR07,RT03,SA01" \
-i "pandas.Series.std PR01,RT03,SA01" \
-i "pandas.Series.str PR01,SA01" \
-i "pandas.Series.str.capitalize RT03" \
-i "pandas.Series.str.casefold RT03" \
-i "pandas.Series.str.center RT03,SA01" \
-i "pandas.Series.str.decode PR07,RT03,SA01" \
-i "pandas.Series.str.encode PR07,RT03,SA01" \
-i "pandas.Series.str.find RT03" \
-i "pandas.Series.str.fullmatch RT03" \
-i "pandas.Series.str.get RT03,SA01" \
-i "pandas.Series.str.index RT03" \
-i "pandas.Series.str.ljust RT03,SA01" \
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-i "pandas.io.stata.StataReader.variable_labels RT03,SA01" \
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-i "pandas.merge_ordered PR07" \
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-i "pandas.period_range RT03,SA01" \
-i "pandas.pivot PR07" \
-i "pandas.pivot_table PR07" \
-i "pandas.plotting.andrews_curves RT03,SA01" \
-i "pandas.plotting.autocorrelation_plot RT03,SA01" \
-i "pandas.plotting.lag_plot RT03,SA01" \
-i "pandas.plotting.parallel_coordinates PR07,RT03,SA01" \
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-i "pandas.plotting.scatter_matrix PR07,SA01" \
-i "pandas.plotting.table PR07,RT03,SA01" \
-i "pandas.qcut PR07,SA01" \
-i "pandas.read_feather SA01" \
-i "pandas.read_orc SA01" \
-i "pandas.read_sas SA01" \
-i "pandas.read_spss SA01" \
-i "pandas.reset_option SA01" \
-i "pandas.set_eng_float_format RT03,SA01" \
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-i "pandas.show_versions SA01" \
-i "pandas.test SA01" \
-i "pandas.testing.assert_extension_array_equal SA01" \
-i "pandas.testing.assert_index_equal PR07,SA01" \
-i "pandas.testing.assert_series_equal PR07,SA01" \
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-i "pandas.tseries.offsets.BMonthEnd PR02" \
-i "pandas.tseries.offsets.BQuarterBegin PR02" \
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-i "pandas.tseries.offsets.BYearEnd.copy SA01" \
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-i "pandas.tseries.offsets.BusinessDay.n GL08" \
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-i "pandas.tseries.offsets.BusinessHour.kwds SA01" \
-i "pandas.tseries.offsets.BusinessHour.n GL08" \
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-i "pandas.tseries.offsets.BusinessMonthBegin.copy SA01" \
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-i "pandas.tseries.offsets.BusinessMonthBegin.is_on_offset GL08" \
-i "pandas.tseries.offsets.BusinessMonthBegin.kwds SA01" \
-i "pandas.tseries.offsets.BusinessMonthBegin.n GL08" \
-i "pandas.tseries.offsets.BusinessMonthBegin.name SA01" \
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-i "pandas.tseries.offsets.BusinessMonthEnd.copy SA01" \
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-i "pandas.tseries.offsets.BusinessMonthEnd.n GL08" \
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-i "pandas.tseries.offsets.CustomBusinessDay.copy SA01" \
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-i "pandas.tseries.offsets.CustomBusinessDay.n GL08" \
-i "pandas.tseries.offsets.CustomBusinessDay.name SA01" \
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-i "pandas.tseries.offsets.CustomBusinessHour.is_on_offset GL08" \
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-i "pandas.tseries.offsets.CustomBusinessHour.n GL08" \
-i "pandas.tseries.offsets.CustomBusinessHour.name SA01" \
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-i "pandas.tseries.offsets.CustomBusinessMonthBegin PR02" \
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-i "pandas.tseries.offsets.CustomBusinessMonthEnd.name SA01" \
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-i "pandas.tseries.offsets.DateOffset.n GL08" \
-i "pandas.tseries.offsets.DateOffset.name SA01" \
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-i "pandas.tseries.offsets.FY5253 PR02" \
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-i "pandas.tseries.offsets.SemiMonthBegin.copy SA01" \
-i "pandas.tseries.offsets.SemiMonthBegin.day_of_month GL08" \
-i "pandas.tseries.offsets.SemiMonthBegin.freqstr SA01" \
-i "pandas.tseries.offsets.SemiMonthBegin.is_on_offset GL08" \
-i "pandas.tseries.offsets.SemiMonthBegin.kwds SA01" \
-i "pandas.tseries.offsets.SemiMonthBegin.n GL08" \
-i "pandas.tseries.offsets.SemiMonthBegin.name SA01" \
-i "pandas.tseries.offsets.SemiMonthBegin.nanos GL08" \
-i "pandas.tseries.offsets.SemiMonthBegin.normalize GL08" \
-i "pandas.tseries.offsets.SemiMonthBegin.rule_code GL08" \
-i "pandas.tseries.offsets.SemiMonthEnd PR02,SA01" \
-i "pandas.tseries.offsets.SemiMonthEnd.copy SA01" \
-i "pandas.tseries.offsets.SemiMonthEnd.day_of_month GL08" \