Updated script that can be controled by Nodejs web app

lib/python3.13/site-packages/pandas/tests/groupby/test_api.py

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+"""
+Tests of the groupby API, including internal consistency and with other pandas objects.
+
+Tests in this file should only check the existence, names, and arguments of groupby
+methods. It should not test the results of any groupby operation.
+"""
+
+import inspect
+
+import pytest
+
+from pandas import (
+    DataFrame,
+    Series,
+)
+from pandas.core.groupby.base import (
+    groupby_other_methods,
+    reduction_kernels,
+    transformation_kernels,
+)
+from pandas.core.groupby.generic import (
+    DataFrameGroupBy,
+    SeriesGroupBy,
+)
+
+
+def test_tab_completion(multiindex_dataframe_random_data):
+    grp = multiindex_dataframe_random_data.groupby(level="second")
+    results = {v for v in dir(grp) if not v.startswith("_")}
+    expected = {
+        "A",
+        "B",
+        "C",
+        "agg",
+        "aggregate",
+        "apply",
+        "boxplot",
+        "filter",
+        "first",
+        "get_group",
+        "groups",
+        "hist",
+        "indices",
+        "last",
+        "max",
+        "mean",
+        "median",
+        "min",
+        "ngroups",
+        "nth",
+        "ohlc",
+        "plot",
+        "prod",
+        "size",
+        "std",
+        "sum",
+        "transform",
+        "var",
+        "sem",
+        "count",
+        "nunique",
+        "head",
+        "describe",
+        "cummax",
+        "quantile",
+        "rank",
+        "cumprod",
+        "tail",
+        "resample",
+        "cummin",
+        "fillna",
+        "cumsum",
+        "cumcount",
+        "ngroup",
+        "all",
+        "shift",
+        "skew",
+        "take",
+        "pct_change",
+        "any",
+        "corr",
+        "corrwith",
+        "cov",
+        "dtypes",
+        "ndim",
+        "diff",
+        "idxmax",
+        "idxmin",
+        "ffill",
+        "bfill",
+        "rolling",
+        "expanding",
+        "pipe",
+        "sample",
+        "ewm",
+        "value_counts",
+    }
+    assert results == expected
+
+
+def test_all_methods_categorized(multiindex_dataframe_random_data):
+    grp = multiindex_dataframe_random_data.groupby(
+        multiindex_dataframe_random_data.iloc[:, 0]
+    )
+    names = {_ for _ in dir(grp) if not _.startswith("_")} - set(
+        multiindex_dataframe_random_data.columns
+    )
+    new_names = set(names)
+    new_names -= reduction_kernels
+    new_names -= transformation_kernels
+    new_names -= groupby_other_methods
+
+    assert not reduction_kernels & transformation_kernels
+    assert not reduction_kernels & groupby_other_methods
+    assert not transformation_kernels & groupby_other_methods
+
+    # new public method?
+    if new_names:
+        msg = f"""
+There are uncategorized methods defined on the Grouper class:
+{new_names}.
+
+Was a new method recently added?
+
+Every public method On Grouper must appear in exactly one the
+following three lists defined in pandas.core.groupby.base:
+- `reduction_kernels`
+- `transformation_kernels`
+- `groupby_other_methods`
+see the comments in pandas/core/groupby/base.py for guidance on
+how to fix this test.
+        """
+        raise AssertionError(msg)
+
+    # removed a public method?
+    all_categorized = reduction_kernels | transformation_kernels | groupby_other_methods
+    if names != all_categorized:
+        msg = f"""
+Some methods which are supposed to be on the Grouper class
+are missing:
+{all_categorized - names}.
+
+They're still defined in one of the lists that live in pandas/core/groupby/base.py.
+If you removed a method, you should update them
+"""
+        raise AssertionError(msg)
+
+
+def test_frame_consistency(groupby_func):
+    # GH#48028
+    if groupby_func in ("first", "last"):
+        msg = "first and last are entirely different between frame and groupby"
+        pytest.skip(reason=msg)
+
+    if groupby_func in ("cumcount", "ngroup"):
+        assert not hasattr(DataFrame, groupby_func)
+        return
+
+    frame_method = getattr(DataFrame, groupby_func)
+    gb_method = getattr(DataFrameGroupBy, groupby_func)
+    result = set(inspect.signature(gb_method).parameters)
+    if groupby_func == "size":
+        # "size" is a method on GroupBy but property on DataFrame:
+        expected = {"self"}
+    else:
+        expected = set(inspect.signature(frame_method).parameters)
+
+    # Exclude certain arguments from result and expected depending on the operation
+    # Some of these may be purposeful inconsistencies between the APIs
+    exclude_expected, exclude_result = set(), set()
+    if groupby_func in ("any", "all"):
+        exclude_expected = {"kwargs", "bool_only", "axis"}
+    elif groupby_func in ("count",):
+        exclude_expected = {"numeric_only", "axis"}
+    elif groupby_func in ("nunique",):
+        exclude_expected = {"axis"}
+    elif groupby_func in ("max", "min"):
+        exclude_expected = {"axis", "kwargs", "skipna"}
+        exclude_result = {"min_count", "engine", "engine_kwargs"}
+    elif groupby_func in ("mean", "std", "sum", "var"):
+        exclude_expected = {"axis", "kwargs", "skipna"}
+        exclude_result = {"engine", "engine_kwargs"}
+    elif groupby_func in ("median", "prod", "sem"):
+        exclude_expected = {"axis", "kwargs", "skipna"}
+    elif groupby_func in ("backfill", "bfill", "ffill", "pad"):
+        exclude_expected = {"downcast", "inplace", "axis", "limit_area"}
+    elif groupby_func in ("cummax", "cummin"):
+        exclude_expected = {"skipna", "args"}
+        exclude_result = {"numeric_only"}
+    elif groupby_func in ("cumprod", "cumsum"):
+        exclude_expected = {"skipna"}
+    elif groupby_func in ("pct_change",):
+        exclude_expected = {"kwargs"}
+        exclude_result = {"axis"}
+    elif groupby_func in ("rank",):
+        exclude_expected = {"numeric_only"}
+    elif groupby_func in ("quantile",):
+        exclude_expected = {"method", "axis"}
+
+    # Ensure excluded arguments are actually in the signatures
+    assert result & exclude_result == exclude_result
+    assert expected & exclude_expected == exclude_expected
+
+    result -= exclude_result
+    expected -= exclude_expected
+    assert result == expected
+
+
+def test_series_consistency(request, groupby_func):
+    # GH#48028
+    if groupby_func in ("first", "last"):
+        pytest.skip("first and last are entirely different between Series and groupby")
+
+    if groupby_func in ("cumcount", "corrwith", "ngroup"):
+        assert not hasattr(Series, groupby_func)
+        return
+
+    series_method = getattr(Series, groupby_func)
+    gb_method = getattr(SeriesGroupBy, groupby_func)
+    result = set(inspect.signature(gb_method).parameters)
+    if groupby_func == "size":
+        # "size" is a method on GroupBy but property on Series
+        expected = {"self"}
+    else:
+        expected = set(inspect.signature(series_method).parameters)
+
+    # Exclude certain arguments from result and expected depending on the operation
+    # Some of these may be purposeful inconsistencies between the APIs
+    exclude_expected, exclude_result = set(), set()
+    if groupby_func in ("any", "all"):
+        exclude_expected = {"kwargs", "bool_only", "axis"}
+    elif groupby_func in ("diff",):
+        exclude_result = {"axis"}
+    elif groupby_func in ("max", "min"):
+        exclude_expected = {"axis", "kwargs", "skipna"}
+        exclude_result = {"min_count", "engine", "engine_kwargs"}
+    elif groupby_func in ("mean", "std", "sum", "var"):
+        exclude_expected = {"axis", "kwargs", "skipna"}
+        exclude_result = {"engine", "engine_kwargs"}
+    elif groupby_func in ("median", "prod", "sem"):
+        exclude_expected = {"axis", "kwargs", "skipna"}
+    elif groupby_func in ("backfill", "bfill", "ffill", "pad"):
+        exclude_expected = {"downcast", "inplace", "axis", "limit_area"}
+    elif groupby_func in ("cummax", "cummin"):
+        exclude_expected = {"skipna", "args"}
+        exclude_result = {"numeric_only"}
+    elif groupby_func in ("cumprod", "cumsum"):
+        exclude_expected = {"skipna"}
+    elif groupby_func in ("pct_change",):
+        exclude_expected = {"kwargs"}
+        exclude_result = {"axis"}
+    elif groupby_func in ("rank",):
+        exclude_expected = {"numeric_only"}
+    elif groupby_func in ("idxmin", "idxmax"):
+        exclude_expected = {"args", "kwargs"}
+    elif groupby_func in ("quantile",):
+        exclude_result = {"numeric_only"}
+
+    # Ensure excluded arguments are actually in the signatures
+    assert result & exclude_result == exclude_result
+    assert expected & exclude_expected == exclude_expected
+
+    result -= exclude_result
+    expected -= exclude_expected
+    assert result == expected