Repository: pandas-dev/pandas
Pull request #57359 (2024-02-11 11:24:03)

CI/DOC: Enforce ES01 in CI
Enforce ES01 in CI so that it can be fixed and enforced in chunks like other docstring errors.

The added functions come from the result of running `scripts/validate_docstrings.py --format=actions --errors=ES01`

Part of our ongoing work to continue enforcing numpydoc validations: https://numpydoc.readthedocs.io/en/latest/validation.html#built-in-validation-checks

- [x]  xref https://github.com/pandas-dev/pandas/pull/56971
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).
- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.
- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.


jordan-d-murphy: pre-commit.ci autofix



Patch:
diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 35383ca526..20ced8a513 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -141,6 +141,1049 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         pandas.core.groupby.SeriesGroupBy.plot # There should be no backslash in the final line, please keep this comment in the last ignored function
     RET=$(($RET + $?)) ; echo $MSG "DONE"
 
+    MSG='Partially validate docstrings (ES01)' ;  echo $MSG
+    $BASE_DIR/scripts/validate_docstrings.py --format=actions --errors=ES01 --ignore_functions \
+        pandas.Categorical.__array__\
+        pandas.Categorical.as_ordered\
+        pandas.Categorical.as_unordered\
+        pandas.Categorical.dtype\
+        pandas.Categorical.ordered\
+        pandas.Categorical.remove_unused_categories\
+        pandas.Categorical.rename_categories\
+        pandas.CategoricalDtype\
+        pandas.CategoricalDtype.categories\
+        pandas.CategoricalDtype.ordered\
+        pandas.CategoricalIndex.as_ordered\
+        pandas.CategoricalIndex.as_unordered\
+        pandas.CategoricalIndex.equals\
+        pandas.CategoricalIndex.ordered\
+        pandas.CategoricalIndex.remove_unused_categories\
+        pandas.CategoricalIndex.rename_categories\
+        pandas.DataFrame.T\
+        pandas.DataFrame.__dataframe__\
+        pandas.DataFrame.__iter__\
+        pandas.DataFrame.agg\
+        pandas.DataFrame.aggregate\
+        pandas.DataFrame.astype\
+        pandas.DataFrame.at_time\
+        pandas.DataFrame.bfill\
+        pandas.DataFrame.columns\
+        pandas.DataFrame.compare\
+        pandas.DataFrame.convert_dtypes\
+        pandas.DataFrame.corr\
+        pandas.DataFrame.droplevel\
+        pandas.DataFrame.expanding\
+        pandas.DataFrame.explode\
+        pandas.DataFrame.ffill\
+        pandas.DataFrame.fillna\
+        pandas.DataFrame.first_valid_index\
+        pandas.DataFrame.isin\
+        pandas.DataFrame.iterrows\
+        pandas.DataFrame.itertuples\
+        pandas.DataFrame.last_valid_index\
+        pandas.DataFrame.mask\
+        pandas.DataFrame.mean\
+        pandas.DataFrame.median\
+        pandas.DataFrame.pipe\
+        pandas.DataFrame.pop\
+        pandas.DataFrame.prod\
+        pandas.DataFrame.product\
+        pandas.DataFrame.quantile\
+        pandas.DataFrame.query\
+        pandas.DataFrame.rename_axis\
+        pandas.DataFrame.reorder_levels\
+        pandas.DataFrame.rolling\
+        pandas.DataFrame.round\
+        pandas.DataFrame.select_dtypes\
+        pandas.DataFrame.set_flags\
+        pandas.DataFrame.shape\
+        pandas.DataFrame.sort_values\
+        pandas.DataFrame.sparse\
+        pandas.DataFrame.sparse.density\
+        pandas.DataFrame.sparse.from_spmatrix\
+        pandas.DataFrame.sparse.to_coo\
+        pandas.DataFrame.sparse.to_dense\
+        pandas.DataFrame.to_csv\
+        pandas.DataFrame.to_feather\
+        pandas.DataFrame.to_html\
+        pandas.DataFrame.to_markdown\
+        pandas.DataFrame.to_pickle\
+        pandas.DataFrame.to_string\
+        pandas.DataFrame.to_timestamp\
+        pandas.DataFrame.to_xarray\
+        pandas.DataFrame.transform\
+        pandas.DataFrame.tz_convert\
+        pandas.DataFrame.value_counts\
+        pandas.DataFrame.where\
+        pandas.DatetimeIndex.ceil\
+        pandas.DatetimeIndex.day\
+        pandas.DatetimeIndex.day_name\
+        pandas.DatetimeIndex.day_of_year\
+        pandas.DatetimeIndex.dayofyear\
+        pandas.DatetimeIndex.floor\
+        pandas.DatetimeIndex.freqstr\
+        pandas.DatetimeIndex.hour\
+        pandas.DatetimeIndex.indexer_at_time\
+        pandas.DatetimeIndex.indexer_between_time\
+        pandas.DatetimeIndex.is_month_end\
+        pandas.DatetimeIndex.is_month_start\
+        pandas.DatetimeIndex.is_quarter_end\
+        pandas.DatetimeIndex.is_quarter_start\
+        pandas.DatetimeIndex.is_year_end\
+        pandas.DatetimeIndex.is_year_start\
+        pandas.DatetimeIndex.mean\
+        pandas.DatetimeIndex.microsecond\
+        pandas.DatetimeIndex.minute\
+        pandas.DatetimeIndex.month\
+        pandas.DatetimeIndex.month_name\
+        pandas.DatetimeIndex.nanosecond\
+        pandas.DatetimeIndex.quarter\
+        pandas.DatetimeIndex.round\
+        pandas.DatetimeIndex.second\
+        pandas.DatetimeIndex.snap\
+        pandas.DatetimeIndex.to_frame\
+        pandas.DatetimeIndex.to_pydatetime\
+        pandas.DatetimeIndex.tz\
+        pandas.DatetimeIndex.tz_convert\
+        pandas.DatetimeIndex.year\
+        pandas.DatetimeTZDtype.tz\
+        pandas.DatetimeTZDtype.unit\
+        pandas.Flags\
+        pandas.HDFStore.get\
+        pandas.HDFStore.info\
+        pandas.HDFStore.keys\
+        pandas.HDFStore.put\
+        pandas.Index.T\
+        pandas.Index.all\
+        pandas.Index.any\
+        pandas.Index.append\
+        pandas.Index.argsort\
+        pandas.Index.array\
+        pandas.Index.delete\
+        pandas.Index.drop\
+        pandas.Index.drop_duplicates\
+        pandas.Index.dropna\
+        pandas.Index.dtype\
+        pandas.Index.fillna\
+        pandas.Index.get_loc\
+        pandas.Index.has_duplicates\
+        pandas.Index.identical\
+        pandas.Index.inferred_type\
+        pandas.Index.is_monotonic_decreasing\
+        pandas.Index.is_monotonic_increasing\
+        pandas.Index.is_unique\
+        pandas.Index.item\
+        pandas.Index.join\
+        pandas.Index.map\
+        pandas.Index.max\
+        pandas.Index.memory_usage\
+        pandas.Index.min\
+        pandas.Index.name\
+        pandas.Index.nbytes\
+        pandas.Index.ndim\
+        pandas.Index.putmask\
+        pandas.Index.ravel\
+        pandas.Index.reindex\
+        pandas.Index.shape\
+        pandas.Index.size\
+        pandas.Index.slice_locs\
+        pandas.Index.symmetric_difference\
+        pandas.Index.to_frame\
+        pandas.Index.to_numpy\
+        pandas.IndexSlice\
+        pandas.Interval\
+        pandas.Interval.is_empty\
+        pandas.Interval.left\
+        pandas.Interval.length\
+        pandas.Interval.mid\
+        pandas.Interval.right\
+        pandas.IntervalDtype.subtype\
+        pandas.IntervalIndex\
+        pandas.IntervalIndex.from_arrays\
+        pandas.IntervalIndex.from_breaks\
+        pandas.IntervalIndex.from_tuples\
+        pandas.IntervalIndex.get_loc\
+        pandas.IntervalIndex.is_empty\
+        pandas.IntervalIndex.set_closed\
+        pandas.IntervalIndex.to_tuples\
+        pandas.MultiIndex\
+        pandas.MultiIndex.append\
+        pandas.MultiIndex.drop\
+        pandas.MultiIndex.dtypes\
+        pandas.MultiIndex.from_arrays\
+        pandas.MultiIndex.from_frame\
+        pandas.MultiIndex.from_product\
+        pandas.MultiIndex.from_tuples\
+        pandas.MultiIndex.get_loc_level\
+        pandas.MultiIndex.get_locs\
+        pandas.MultiIndex.levshape\
+        pandas.MultiIndex.names\
+        pandas.MultiIndex.nlevels\
+        pandas.MultiIndex.reorder_levels\
+        pandas.MultiIndex.set_codes\
+        pandas.MultiIndex.set_levels\
+        pandas.MultiIndex.to_flat_index\
+        pandas.MultiIndex.truncate\
+        pandas.NaT\
+        pandas.Period\
+        pandas.Period.asfreq\
+        pandas.Period.day\
+        pandas.Period.days_in_month\
+        pandas.Period.daysinmonth\
+        pandas.Period.end_time\
+        pandas.Period.freqstr\
+        pandas.Period.hour\
+        pandas.Period.is_leap_year\
+        pandas.Period.minute\
+        pandas.Period.month\
+        pandas.Period.now\
+        pandas.Period.quarter\
+        pandas.Period.second\
+        pandas.Period.start_time\
+        pandas.Period.week\
+        pandas.Period.weekofyear\
+        pandas.Period.year\
+        pandas.PeriodDtype.freq\
+        pandas.PeriodIndex.day\
+        pandas.PeriodIndex.day_of_week\
+        pandas.PeriodIndex.day_of_year\
+        pandas.PeriodIndex.dayofweek\
+        pandas.PeriodIndex.dayofyear\
+        pandas.PeriodIndex.days_in_month\
+        pandas.PeriodIndex.daysinmonth\
+        pandas.PeriodIndex.end_time\
+        pandas.PeriodIndex.freqstr\
+        pandas.PeriodIndex.from_fields\
+        pandas.PeriodIndex.from_ordinals\
+        pandas.PeriodIndex.hour\
+        pandas.PeriodIndex.is_leap_year\
+        pandas.PeriodIndex.minute\
+        pandas.PeriodIndex.month\
+        pandas.PeriodIndex.quarter\
+        pandas.PeriodIndex.second\
+        pandas.PeriodIndex.start_time\
+        pandas.PeriodIndex.to_timestamp\
+        pandas.PeriodIndex.week\
+        pandas.PeriodIndex.weekday\
+        pandas.PeriodIndex.weekofyear\
+        pandas.PeriodIndex.year\
+        pandas.RangeIndex.from_range\
+        pandas.RangeIndex.start\
+        pandas.RangeIndex.step\
+        pandas.RangeIndex.stop\
+        pandas.Series.T\
+        pandas.Series.agg\
+        pandas.Series.aggregate\
+        pandas.Series.array\
+        pandas.Series.astype\
+        pandas.Series.at_time\
+        pandas.Series.bfill\
+        pandas.Series.case_when\
+        pandas.Series.cat\
+        pandas.Series.cat.as_ordered\
+        pandas.Series.cat.as_unordered\
+        pandas.Series.cat.codes\
+        pandas.Series.cat.ordered\
+        pandas.Series.cat.remove_unused_categories\
+        pandas.Series.cat.rename_categories\
+        pandas.Series.compare\
+        pandas.Series.convert_dtypes\
+        pandas.Series.count\
+        pandas.Series.drop_duplicates\
+        pandas.Series.droplevel\
+        pandas.Series.dt.ceil\
+        pandas.Series.dt.components\
+        pandas.Series.dt.day\
+        pandas.Series.dt.day_name\
+        pandas.Series.dt.day_of_year\
+        pandas.Series.dt.dayofyear\
+        pandas.Series.dt.days\
+        pandas.Series.dt.days_in_month\
+        pandas.Series.dt.daysinmonth\
+        pandas.Series.dt.end_time\
+        pandas.Series.dt.floor\
+        pandas.Series.dt.hour\
+        pandas.Series.dt.is_month_end\
+        pandas.Series.dt.is_month_start\
+        pandas.Series.dt.is_quarter_end\
+        pandas.Series.dt.is_quarter_start\
+        pandas.Series.dt.is_year_end\
+        pandas.Series.dt.is_year_start\
+        pandas.Series.dt.isocalendar\
+        pandas.Series.dt.microsecond\
+        pandas.Series.dt.microseconds\
+        pandas.Series.dt.minute\
+        pandas.Series.dt.month\
+        pandas.Series.dt.month_name\
+        pandas.Series.dt.nanosecond\
+        pandas.Series.dt.nanoseconds\
+        pandas.Series.dt.quarter\
+        pandas.Series.dt.round\
+        pandas.Series.dt.second\
+        pandas.Series.dt.seconds\
+        pandas.Series.dt.start_time\
+        pandas.Series.dt.tz\
+        pandas.Series.dt.tz_convert\
+        pandas.Series.dt.year\
+        pandas.Series.dtype\
+        pandas.Series.dtypes\
+        pandas.Series.expanding\
+        pandas.Series.explode\
+        pandas.Series.ffill\
+        pandas.Series.fillna\
+        pandas.Series.first_valid_index\
+        pandas.Series.hist\
+        pandas.Series.is_monotonic_decreasing\
+        pandas.Series.is_monotonic_increasing\
+        pandas.Series.is_unique\
+        pandas.Series.item\
+        pandas.Series.keys\
+        pandas.Series.last_valid_index\
+        pandas.Series.list.__getitem__\
+        pandas.Series.list.flatten\
+        pandas.Series.list.len\
+        pandas.Series.mask\
+        pandas.Series.mean\
+        pandas.Series.median\
+        pandas.Series.nbytes\
+        pandas.Series.ndim\
+        pandas.Series.nlargest\
+        pandas.Series.nsmallest\
+        pandas.Series.pipe\
+        pandas.Series.pop\
+        pandas.Series.prod\
+        pandas.Series.product\
+        pandas.Series.quantile\
+        pandas.Series.rename_axis\
+        pandas.Series.rolling\
+        pandas.Series.round\
+        pandas.Series.set_flags\
+        pandas.Series.shape\
+        pandas.Series.size\
+        pandas.Series.sparse\
+        pandas.Series.sparse.density\
+        pandas.Series.sparse.from_coo\
+        pandas.Series.sparse.npoints\
+        pandas.Series.sparse.sp_values\
+        pandas.Series.str.fullmatch\
+        pandas.Series.str.match\
+        pandas.Series.str.pad\
+        pandas.Series.str.repeat\
+        pandas.Series.str.slice\
+        pandas.Series.str.slice_replace\
+        pandas.Series.struct.dtypes\
+        pandas.Series.struct.explode\
+        pandas.Series.struct.field\
+        pandas.Series.to_csv\
+        pandas.Series.to_dict\
+        pandas.Series.to_frame\
+        pandas.Series.to_markdown\
+        pandas.Series.to_numpy\
+        pandas.Series.to_period\
+        pandas.Series.to_pickle\
+        pandas.Series.to_string\
+        pandas.Series.to_timestamp\
+        pandas.Series.to_xarray\
+        pandas.Series.transform\
+        pandas.Series.tz_convert\
+        pandas.Series.unstack\
+        pandas.Series.where\
+        pandas.Timedelta.as_unit\
+        pandas.Timedelta.ceil\
+        pandas.Timedelta.components\
+        pandas.Timedelta.days\
+        pandas.Timedelta.floor\
+        pandas.Timedelta.nanoseconds\
+        pandas.Timedelta.round\
+        pandas.Timedelta.to_timedelta64\
+        pandas.Timedelta.total_seconds\
+        pandas.Timedelta.view\
+        pandas.TimedeltaIndex.as_unit\
+        pandas.TimedeltaIndex.ceil\
+        pandas.TimedeltaIndex.days\
+        pandas.TimedeltaIndex.floor\
+        pandas.TimedeltaIndex.mean\
+        pandas.TimedeltaIndex.microseconds\
+        pandas.TimedeltaIndex.nanoseconds\
+        pandas.TimedeltaIndex.round\
+        pandas.TimedeltaIndex.seconds\
+        pandas.TimedeltaIndex.to_frame\
+        pandas.TimedeltaIndex.to_pytimedelta\
+        pandas.Timestamp.as_unit\
+        pandas.Timestamp.asm8\
+        pandas.Timestamp.astimezone\
+        pandas.Timestamp.ceil\
+        pandas.Timestamp.combine\
+        pandas.Timestamp.ctime\
+        pandas.Timestamp.date\
+        pandas.Timestamp.day_name\
+        pandas.Timestamp.day_of_week\
+        pandas.Timestamp.day_of_year\
+        pandas.Timestamp.dayofweek\
+        pandas.Timestamp.dayofyear\
+        pandas.Timestamp.days_in_month\
+        pandas.Timestamp.daysinmonth\
+        pandas.Timestamp.dst\
+        pandas.Timestamp.floor\
+        pandas.Timestamp.fromordinal\
+        pandas.Timestamp.fromtimestamp\
+        pandas.Timestamp.is_leap_year\
+        pandas.Timestamp.is_month_end\
+        pandas.Timestamp.is_month_start\
+        pandas.Timestamp.is_quarter_end\
+        pandas.Timestamp.is_quarter_start\
+        pandas.Timestamp.is_year_end\
+        pandas.Timestamp.is_year_start\
+        pandas.Timestamp.isocalendar\
+        pandas.Timestamp.month_name\
+        pandas.Timestamp.normalize\
+        pandas.Timestamp.now\
+        pandas.Timestamp.quarter\
+        pandas.Timestamp.replace\
+        pandas.Timestamp.round\
+        pandas.Timestamp.strftime\
+        pandas.Timestamp.strptime\
+        pandas.Timestamp.time\
+        pandas.Timestamp.timestamp\
+        pandas.Timestamp.timetuple\
+        pandas.Timestamp.timetz\
+        pandas.Timestamp.to_datetime64\
+        pandas.Timestamp.to_period\
+        pandas.Timestamp.toordinal\
+        pandas.Timestamp.tz\
+        pandas.Timestamp.tz_convert\
+        pandas.Timestamp.tzname\
+        pandas.Timestamp.unit\
+        pandas.Timestamp.utcfromtimestamp\
+        pandas.Timestamp.utcnow\
+        pandas.Timestamp.utcoffset\
+        pandas.Timestamp.utctimetuple\
+        pandas.Timestamp.week\
+        pandas.Timestamp.weekofyear\
+        pandas.api.extensions.ExtensionArray._concat_same_type\
+        pandas.api.extensions.ExtensionArray._from_factorized\
+        pandas.api.extensions.ExtensionArray._from_sequence\
+        pandas.api.extensions.ExtensionArray._from_sequence_of_strings\
+        pandas.api.extensions.ExtensionArray._pad_or_backfill\
+        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.dropna\
+        pandas.api.extensions.ExtensionArray.dtype\
+        pandas.api.extensions.ExtensionArray.duplicated\
+        pandas.api.extensions.ExtensionArray.factorize\
+        pandas.api.extensions.ExtensionArray.fillna\
+        pandas.api.extensions.ExtensionArray.insert\
+        pandas.api.extensions.ExtensionArray.interpolate\
+        pandas.api.extensions.ExtensionArray.isna\
+        pandas.api.extensions.ExtensionArray.nbytes\
+        pandas.api.extensions.ExtensionArray.ndim\
+        pandas.api.extensions.ExtensionArray.ravel\
+        pandas.api.extensions.ExtensionArray.shape\
+        pandas.api.extensions.ExtensionArray.take\
+        pandas.api.extensions.ExtensionArray.unique\
+        pandas.api.extensions.ExtensionArray.view\
+        pandas.api.extensions.ExtensionDtype\
+        pandas.api.extensions.register_dataframe_accessor\
+        pandas.api.extensions.register_index_accessor\
+        pandas.api.extensions.register_series_accessor\
+        pandas.api.indexers.BaseIndexer\
+        pandas.api.indexers.FixedForwardWindowIndexer\
+        pandas.api.indexers.VariableOffsetWindowIndexer\
+        pandas.api.interchange.from_dataframe\
+        pandas.api.types.infer_dtype\
+        pandas.api.types.is_any_real_numeric_dtype\
+        pandas.api.types.is_bool\
+        pandas.api.types.is_bool_dtype\
+        pandas.api.types.is_categorical_dtype\
+        pandas.api.types.is_complex\
+        pandas.api.types.is_complex_dtype\
+        pandas.api.types.is_datetime64_any_dtype\
+        pandas.api.types.is_datetime64_dtype\
+        pandas.api.types.is_datetime64_ns_dtype\
+        pandas.api.types.is_datetime64tz_dtype\
+        pandas.api.types.is_dict_like\
+        pandas.api.types.is_float\
+        pandas.api.types.is_float_dtype\
+        pandas.api.types.is_integer\
+        pandas.api.types.is_interval_dtype\
+        pandas.api.types.is_named_tuple\
+        pandas.api.types.is_numeric_dtype\
+        pandas.api.types.is_object_dtype\
+        pandas.api.types.is_period_dtype\
+        pandas.api.types.is_re\
+        pandas.api.types.is_re_compilable\
+        pandas.api.types.is_scalar\
+        pandas.api.types.is_timedelta64_dtype\
+        pandas.api.types.pandas_dtype\
+        pandas.array\
+        pandas.arrays.IntervalArray\
+        pandas.arrays.IntervalArray.from_arrays\
+        pandas.arrays.IntervalArray.from_breaks\
+        pandas.arrays.IntervalArray.from_tuples\
+        pandas.arrays.IntervalArray.is_empty\
+        pandas.arrays.IntervalArray.left\
+        pandas.arrays.IntervalArray.length\
+        pandas.arrays.IntervalArray.mid\
+        pandas.arrays.IntervalArray.right\
+        pandas.arrays.IntervalArray.set_closed\
+        pandas.arrays.IntervalArray.to_tuples\
+        pandas.arrays.SparseArray\
+        pandas.bdate_range\
+        pandas.core.groupby.DataFrameGroupBy.__iter__\
+        pandas.core.groupby.DataFrameGroupBy.agg\
+        pandas.core.groupby.DataFrameGroupBy.aggregate\
+        pandas.core.groupby.DataFrameGroupBy.all\
+        pandas.core.groupby.DataFrameGroupBy.any\
+        pandas.core.groupby.DataFrameGroupBy.bfill\
+        pandas.core.groupby.DataFrameGroupBy.boxplot\
+        pandas.core.groupby.DataFrameGroupBy.corr\
+        pandas.core.groupby.DataFrameGroupBy.count\
+        pandas.core.groupby.DataFrameGroupBy.cummax\
+        pandas.core.groupby.DataFrameGroupBy.cummin\
+        pandas.core.groupby.DataFrameGroupBy.cumprod\
+        pandas.core.groupby.DataFrameGroupBy.cumsum\
+        pandas.core.groupby.DataFrameGroupBy.ffill\
+        pandas.core.groupby.DataFrameGroupBy.get_group\
+        pandas.core.groupby.DataFrameGroupBy.groups\
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+        pandas.core.groupby.DataFrameGroupBy.min\
+        pandas.core.groupby.DataFrameGroupBy.nunique\
+        pandas.core.groupby.DataFrameGroupBy.pct_change\
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+        pandas.core.groupby.DataFrameGroupBy.quantile\
+        pandas.core.groupby.DataFrameGroupBy.rank\
+        pandas.core.groupby.DataFrameGroupBy.rolling\
+        pandas.core.groupby.DataFrameGroupBy.size\
+        pandas.core.groupby.DataFrameGroupBy.sum\
+        pandas.core.groupby.SeriesGroupBy.__iter__\
+        pandas.core.groupby.SeriesGroupBy.agg\
+        pandas.core.groupby.SeriesGroupBy.aggregate\
+        pandas.core.groupby.SeriesGroupBy.all\
+        pandas.core.groupby.SeriesGroupBy.any\
+        pandas.core.groupby.SeriesGroupBy.bfill\
+        pandas.core.groupby.SeriesGroupBy.count\
+        pandas.core.groupby.SeriesGroupBy.cummax\
+        pandas.core.groupby.SeriesGroupBy.cummin\
+        pandas.core.groupby.SeriesGroupBy.cumprod\
+        pandas.core.groupby.SeriesGroupBy.cumsum\
+        pandas.core.groupby.SeriesGroupBy.ffill\
+        pandas.core.groupby.SeriesGroupBy.get_group\
+        pandas.core.groupby.SeriesGroupBy.groups\
+        pandas.core.groupby.SeriesGroupBy.hist\
+        pandas.core.groupby.SeriesGroupBy.indices\
+        pandas.core.groupby.SeriesGroupBy.is_monotonic_decreasing\
+        pandas.core.groupby.SeriesGroupBy.is_monotonic_increasing\
+        pandas.core.groupby.SeriesGroupBy.max\
+        pandas.core.groupby.SeriesGroupBy.mean\
+        pandas.core.groupby.SeriesGroupBy.min\
+        pandas.core.groupby.SeriesGroupBy.nlargest\
+        pandas.core.groupby.SeriesGroupBy.nsmallest\
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+        pandas.core.groupby.SeriesGroupBy.rank\
+        pandas.core.groupby.SeriesGroupBy.rolling\
+        pandas.core.groupby.SeriesGroupBy.size\
+        pandas.core.groupby.SeriesGroupBy.sum\
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+        pandas.core.resample.Resampler.get_group\
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+        pandas.core.resample.Resampler.std\
+        pandas.core.resample.Resampler.sum\
+        pandas.core.resample.Resampler.var\
+        pandas.core.window.ewm.ExponentialMovingWindow.corr\
+        pandas.core.window.ewm.ExponentialMovingWindow.cov\
+        pandas.core.window.ewm.ExponentialMovingWindow.mean\
+        pandas.core.window.ewm.ExponentialMovingWindow.std\
+        pandas.core.window.ewm.ExponentialMovingWindow.sum\
+        pandas.core.window.ewm.ExponentialMovingWindow.var\
+        pandas.core.window.expanding.Expanding.aggregate\
+        pandas.core.window.expanding.Expanding.apply\
+        pandas.core.window.expanding.Expanding.corr\
+        pandas.core.window.expanding.Expanding.count\
+        pandas.core.window.expanding.Expanding.cov\
+        pandas.core.window.expanding.Expanding.kurt\
+        pandas.core.window.expanding.Expanding.max\
+        pandas.core.window.expanding.Expanding.mean\
+        pandas.core.window.expanding.Expanding.median\
+        pandas.core.window.expanding.Expanding.min\
+        pandas.core.window.expanding.Expanding.quantile\
+        pandas.core.window.expanding.Expanding.sem\
+        pandas.core.window.expanding.Expanding.skew\
+        pandas.core.window.expanding.Expanding.std\
+        pandas.core.window.expanding.Expanding.sum\
+        pandas.core.window.expanding.Expanding.var\
+        pandas.core.window.rolling.Rolling.aggregate\
+        pandas.core.window.rolling.Rolling.apply\
+        pandas.core.window.rolling.Rolling.corr\
+        pandas.core.window.rolling.Rolling.count\
+        pandas.core.window.rolling.Rolling.cov\
+        pandas.core.window.rolling.Rolling.kurt\
+        pandas.core.window.rolling.Rolling.max\
+        pandas.core.window.rolling.Rolling.mean\
+        pandas.core.window.rolling.Rolling.median\
+        pandas.core.window.rolling.Rolling.min\
+        pandas.core.window.rolling.Rolling.quantile\
+        pandas.core.window.rolling.Rolling.sem\
+        pandas.core.window.rolling.Rolling.skew\
+        pandas.core.window.rolling.Rolling.std\
+        pandas.core.window.rolling.Rolling.sum\
+        pandas.core.window.rolling.Rolling.var\
+        pandas.core.window.rolling.Window.mean\
+        pandas.core.window.rolling.Window.std\
+        pandas.core.window.rolling.Window.sum\
+        pandas.core.window.rolling.Window.var\
+        pandas.errors.AbstractMethodError\
+        pandas.errors.CategoricalConversionWarning\
+        pandas.errors.ClosedFileError\
+        pandas.errors.DuplicateLabelError\
+        pandas.errors.EmptyDataError\
+        pandas.errors.IntCastingNaNError\
+        pandas.errors.InvalidIndexError\
+        pandas.errors.InvalidVersion\
+        pandas.errors.NumbaUtilError\
+        pandas.errors.OutOfBoundsDatetime\
+        pandas.errors.PerformanceWarning\
+        pandas.errors.PossibleDataLossError\
+        pandas.errors.ValueLabelTypeMismatch\
+        pandas.infer_freq\
+        pandas.interval_range\
+        pandas.io.formats.style.Styler\
+        pandas.io.formats.style.Styler.format\
+        pandas.io.formats.style.Styler.highlight_max\
+        pandas.io.formats.style.Styler.highlight_min\
+        pandas.io.formats.style.Styler.highlight_null\
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+        pandas.io.formats.style.Styler.set_caption\
+        pandas.io.formats.style.Styler.set_properties\
+        pandas.io.formats.style.Styler.set_sticky\
+        pandas.io.formats.style.Styler.set_td_classes\
+        pandas.io.formats.style.Styler.set_uuid\
+        pandas.io.json.build_table_schema\
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+        pandas.io.stata.StataReader.variable_labels\
+        pandas.io.stata.StataWriter.write_file\
+        pandas.json_normalize\
+        pandas.plotting.autocorrelation_plot\
+        pandas.plotting.lag_plot\
+        pandas.plotting.parallel_coordinates\
+        pandas.plotting.scatter_matrix\
+        pandas.plotting.table\
+        pandas.read_feather\
+        pandas.read_html\
+        pandas.read_json\
+        pandas.read_orc\
+        pandas.read_sas\
+        pandas.read_spss\
+        pandas.read_stata\
+        pandas.set_eng_float_format\
+        pandas.testing.assert_extension_array_equal\
+        pandas.testing.assert_index_equal\
+        pandas.testing.assert_series_equal\
+        pandas.timedelta_range\
+        pandas.tseries.api.guess_datetime_format\
+        pandas.tseries.frequencies.to_offset\
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+        pandas.tseries.offsets.BQuarterEnd.name\
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+        pandas.tseries.offsets.Minute.is_month_start\
+        pandas.tseries.offsets.Minute.is_quarter_end\
+        pandas.tseries.offsets.Minute.is_quarter_start\
+        pandas.tseries.offsets.Minute.is_year_end\
+        pandas.tseries.offsets.Minute.is_year_start\
+        pandas.tseries.offsets.Minute.kwds\
+        pandas.tseries.offsets.Minute.name\
+        pandas.tseries.offsets.Minute.nanos\
+        pandas.tseries.offsets.MonthBegin.copy\
+        pandas.tseries.offsets.MonthBegin.freqstr\
+        pandas.tseries.offsets.MonthBegin.is_month_end\
+        pandas.tseries.offsets.MonthBegin.is_month_start\
+        pandas.tseries.offsets.MonthBegin.is_quarter_end\
+        pandas.tseries.offsets.MonthBegin.is_quarter_start\
+        pandas.tseries.offsets.MonthBegin.is_year_end\
+        pandas.tseries.offsets.MonthBegin.is_year_start\
+        pandas.tseries.offsets.MonthBegin.kwds\
+        pandas.tseries.offsets.MonthBegin.name\
+        pandas.tseries.offsets.MonthEnd.copy\
+        pandas.tseries.offsets.MonthEnd.freqstr\
+        pandas.tseries.offsets.MonthEnd.is_month_end\
+        pandas.tseries.offsets.MonthEnd.is_month_start\
+        pandas.tseries.offsets.MonthEnd.is_quarter_end\
+        pandas.tseries.offsets.MonthEnd.is_quarter_start\
+        pandas.tseries.offsets.MonthEnd.is_year_end\
+        pandas.tseries.offsets.MonthEnd.is_year_start\
+        pandas.tseries.offsets.MonthEnd.kwds\
+        pandas.tseries.offsets.MonthEnd.name\
+        pandas.tseries.offsets.Nano\
+        pandas.tseries.offsets.Nano.copy\
+        pandas.tseries.offsets.Nano.freqstr\
+        pandas.tseries.offsets.Nano.is_month_end\
+        pandas.tseries.offsets.Nano.is_month_start\
+        pandas.tseries.offsets.Nano.is_quarter_end\
+        pandas.tseries.offsets.Nano.is_quarter_start\
+        pandas.tseries.offsets.Nano.is_year_end\
+        pandas.tseries.offsets.Nano.is_year_start\
+        pandas.tseries.offsets.Nano.kwds\
+        pandas.tseries.offsets.Nano.name\
+        pandas.tseries.offsets.Nano.nanos\
+        pandas.tseries.offsets.QuarterBegin.copy\
+        pandas.tseries.offsets.QuarterBegin.freqstr\
+        pandas.tseries.offsets.QuarterBegin.is_month_end\
+        pandas.tseries.offsets.QuarterBegin.is_month_start\
+        pandas.tseries.offsets.QuarterBegin.is_quarter_end\
+        pandas.tseries.offsets.QuarterBegin.is_quarter_start\
+        pandas.tseries.offsets.QuarterBegin.is_year_end\
+        pandas.tseries.offsets.QuarterBegin.is_year_start\
+        pandas.tseries.offsets.QuarterBegin.kwds\
+        pandas.tseries.offsets.QuarterBegin.name\
+        pandas.tseries.offsets.QuarterEnd.copy\
+        pandas.tseries.offsets.QuarterEnd.freqstr\
+        pandas.tseries.offsets.QuarterEnd.is_month_end\
+        pandas.tseries.offsets.QuarterEnd.is_month_start\
+        pandas.tseries.offsets.QuarterEnd.is_quarter_end\
+        pandas.tseries.offsets.QuarterEnd.is_quarter_start\
+        pandas.tseries.offsets.QuarterEnd.is_year_end\
+        pandas.tseries.offsets.QuarterEnd.is_year_start\
+        pandas.tseries.offsets.QuarterEnd.kwds\
+        pandas.tseries.offsets.QuarterEnd.name\
+        pandas.tseries.offsets.Second\
+        pandas.tseries.offsets.Second.copy\
+        pandas.tseries.offsets.Second.freqstr\
+        pandas.tseries.offsets.Second.is_month_end\
+        pandas.tseries.offsets.Second.is_month_start\
+        pandas.tseries.offsets.Second.is_quarter_end\
+        pandas.tseries.offsets.Second.is_quarter_start\
+        pandas.tseries.offsets.Second.is_year_end\
+        pandas.tseries.offsets.Second.is_year_start\
+        pandas.tseries.offsets.Second.kwds\
+        pandas.tseries.offsets.Second.name\
+        pandas.tseries.offsets.Second.nanos\
+        pandas.tseries.offsets.SemiMonthBegin\
+        pandas.tseries.offsets.SemiMonthBegin.copy\
+        pandas.tseries.offsets.SemiMonthBegin.freqstr\
+        pandas.tseries.offsets.SemiMonthBegin.is_month_end\
+        pandas.tseries.offsets.SemiMonthBegin.is_month_start\
+        pandas.tseries.offsets.SemiMonthBegin.is_quarter_end\
+        pandas.tseries.offsets.SemiMonthBegin.is_quarter_start\
+        pandas.tseries.offsets.SemiMonthBegin.is_year_end\
+        pandas.tseries.offsets.SemiMonthBegin.is_year_start\
+        pandas.tseries.offsets.SemiMonthBegin.kwds\
+        pandas.tseries.offsets.SemiMonthBegin.name\
+        pandas.tseries.offsets.SemiMonthEnd\
+        pandas.tseries.offsets.SemiMonthEnd.copy\
+        pandas.tseries.offsets.SemiMonthEnd.freqstr\
+        pandas.tseries.offsets.SemiMonthEnd.is_month_end\
+        pandas.tseries.offsets.SemiMonthEnd.is_month_start\
+        pandas.tseries.offsets.SemiMonthEnd.is_quarter_end\
+        pandas.tseries.offsets.SemiMonthEnd.is_quarter_start\
+        pandas.tseries.offsets.SemiMonthEnd.is_year_end\
+        pandas.tseries.offsets.SemiMonthEnd.is_year_start\
+        pandas.tseries.offsets.SemiMonthEnd.kwds\
+        pandas.tseries.offsets.SemiMonthEnd.name\
+        pandas.tseries.offsets.Tick.copy\
+        pandas.tseries.offsets.Tick.freqstr\
+        pandas.tseries.offsets.Tick.is_month_end\
+        pandas.tseries.offsets.Tick.is_month_start\
+        pandas.tseries.offsets.Tick.is_quarter_end\
+        pandas.tseries.offsets.Tick.is_quarter_start\
+        pandas.tseries.offsets.Tick.is_year_end\
+        pandas.tseries.offsets.Tick.is_year_start\
+        pandas.tseries.offsets.Tick.kwds\
+        pandas.tseries.offsets.Tick.name\
+        pandas.tseries.offsets.Tick.nanos\
+        pandas.tseries.offsets.Week\
+        pandas.tseries.offsets.Week.copy\
+        pandas.tseries.offsets.Week.freqstr\
+        pandas.tseries.offsets.Week.is_month_end\
+        pandas.tseries.offsets.Week.is_month_start\
+        pandas.tseries.offsets.Week.is_quarter_end\
+        pandas.tseries.offsets.Week.is_quarter_start\
+        pandas.tseries.offsets.Week.is_year_end\
+        pandas.tseries.offsets.Week.is_year_start\
+        pandas.tseries.offsets.Week.kwds\
+        pandas.tseries.offsets.Week.name\
+        pandas.tseries.offsets.WeekOfMonth\
+        pandas.tseries.offsets.WeekOfMonth.copy\
+        pandas.tseries.offsets.WeekOfMonth.freqstr\
+        pandas.tseries.offsets.WeekOfMonth.is_month_end\
+        pandas.tseries.offsets.WeekOfMonth.is_month_start\
+        pandas.tseries.offsets.WeekOfMonth.is_quarter_end\
+        pandas.tseries.offsets.WeekOfMonth.is_quarter_start\
+        pandas.tseries.offsets.WeekOfMonth.is_year_end\
+        pandas.tseries.offsets.WeekOfMonth.is_year_start\
+        pandas.tseries.offsets.WeekOfMonth.kwds\
+        pandas.tseries.offsets.WeekOfMonth.name\
+        pandas.tseries.offsets.YearBegin.copy\
+        pandas.tseries.offsets.YearBegin.freqstr\
+        pandas.tseries.offsets.YearBegin.is_month_end\
+        pandas.tseries.offsets.YearBegin.is_month_start\
+        pandas.tseries.offsets.YearBegin.is_quarter_end\
+        pandas.tseries.offsets.YearBegin.is_quarter_start\
+        pandas.tseries.offsets.YearBegin.is_year_end\
+        pandas.tseries.offsets.YearBegin.is_year_start\
+        pandas.tseries.offsets.YearBegin.kwds\
+        pandas.tseries.offsets.YearBegin.name\
+        pandas.tseries.offsets.YearEnd.copy\
+        pandas.tseries.offsets.YearEnd.freqstr\
+        pandas.tseries.offsets.YearEnd.is_month_end\
+        pandas.tseries.offsets.YearEnd.is_month_start\
+        pandas.tseries.offsets.YearEnd.is_quarter_end\
+        pandas.tseries.offsets.YearEnd.is_quarter_start\
+        pandas.tseries.offsets.YearEnd.is_year_end\
+        pandas.tseries.offsets.YearEnd.is_year_start\
+        pandas.tseries.offsets.YearEnd.kwds\
+        pandas.tseries.offsets.YearEnd.name\
+        pandas.util.hash_array\
+        pandas.util.hash_pandas_object # There should be no backslash in the final line, please keep this comment in the last ignored function
+    RET=$(($RET + $?)) ; echo $MSG "DONE"
+
     MSG='Partially validate docstrings (PR01)' ;  echo $MSG
     $BASE_DIR/scripts/validate_docstrings.py --format=actions --errors=PR01 --ignore_functions \
         pandas.Categorical\
diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index 35769d9c5f..54cd598939 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -213,7 +213,7 @@ Strings
 
 Interval
 ^^^^^^^^
--
+- Bug in :func:`interval_range` where start and end numeric types were always cast to 64 bit (:issue:`57268`)
 -
 
 Indexing
diff --git a/pandas/core/indexes/interval.py b/pandas/core/indexes/interval.py
index 46d1ee49c2..7695193a15 100644
--- a/pandas/core/indexes/interval.py
+++ b/pandas/core/indexes/interval.py
@@ -1101,9 +1101,23 @@ def interval_range(
     breaks: np.ndarray | TimedeltaIndex | DatetimeIndex
 
     if is_number(endpoint):
+        dtype: np.dtype = np.dtype("int64")
         if com.all_not_none(start, end, freq):
+            if (
+                isinstance(start, (float, np.float16))
+                or isinstance(end, (float, np.float16))
+                or isinstance(freq, (float, np.float16))
+            ):
+                dtype = np.dtype("float64")
+            elif (
+                isinstance(start, (np.integer, np.floating))
+                and isinstance(end, (np.integer, np.floating))
+                and start.dtype == end.dtype
+            ):
+                dtype = start.dtype
             # 0.1 ensures we capture end
             breaks = np.arange(start, end + (freq * 0.1), freq)
+            breaks = maybe_downcast_numeric(breaks, dtype)
         else:
             # compute the period/start/end if unspecified (at most one)
             if periods is None:
@@ -1122,7 +1136,7 @@ def interval_range(
             # expected "ndarray[Any, Any]"  [
             breaks = maybe_downcast_numeric(
                 breaks,  # type: ignore[arg-type]
-                np.dtype("int64"),
+                dtype,
             )
     else:
         # delegate to the appropriate range function
@@ -1131,4 +1145,9 @@ def interval_range(
         else:
             breaks = timedelta_range(start=start, end=end, periods=periods, freq=freq)
 
-    return IntervalIndex.from_breaks(breaks, name=name, closed=closed)
+    return IntervalIndex.from_breaks(
+        breaks,
+        name=name,
+        closed=closed,
+        dtype=IntervalDtype(subtype=breaks.dtype, closed=closed),
+    )


Test patch:
diff --git a/pandas/tests/indexes/interval/test_interval_range.py b/pandas/tests/indexes/interval/test_interval_range.py
index e8de59f84b..7aea481b49 100644
--- a/pandas/tests/indexes/interval/test_interval_range.py
+++ b/pandas/tests/indexes/interval/test_interval_range.py
@@ -220,6 +220,20 @@ class TestIntervalRange:
         expected = "int64" if is_integer(start + end) else "float64"
         assert result == expected
 
+    @pytest.mark.parametrize(
+        "start, end, expected",
+        [
+            (np.int8(1), np.int8(10), np.dtype("int8")),
+            (np.int8(1), np.float16(10), np.dtype("float64")),
+            (np.float32(1), np.float32(10), np.dtype("float32")),
+            (1, 10, np.dtype("int64")),
+            (1, 10.0, np.dtype("float64")),
+        ],
+    )
+    def test_interval_dtype(self, start, end, expected):
+        result = interval_range(start=start, end=end).dtype.subtype
+        assert result == expected
+
     def test_interval_range_fractional_period(self):
         # float value for periods
         expected = interval_range(start=0, periods=10)