Updated script that can be controled by Nodejs web app

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

@@ -0,0 +1,80 @@
+import pytest
+
+from pandas import (
+    DataFrame,
+    Series,
+    option_context,
+)
+import pandas._testing as tm
+
+pytestmark = pytest.mark.single_cpu
+
+pytest.importorskip("numba")
+
+
+@pytest.mark.filterwarnings("ignore")
+# Filter warnings when parallel=True and the function can't be parallelized by Numba
+class TestEngine:
+    def test_cython_vs_numba_frame(
+        self, sort, nogil, parallel, nopython, numba_supported_reductions
+    ):
+        func, kwargs = numba_supported_reductions
+        df = DataFrame({"a": [3, 2, 3, 2], "b": range(4), "c": range(1, 5)})
+        engine_kwargs = {"nogil": nogil, "parallel": parallel, "nopython": nopython}
+        gb = df.groupby("a", sort=sort)
+        result = getattr(gb, func)(
+            engine="numba", engine_kwargs=engine_kwargs, **kwargs
+        )
+        expected = getattr(gb, func)(**kwargs)
+        tm.assert_frame_equal(result, expected)
+
+    def test_cython_vs_numba_getitem(
+        self, sort, nogil, parallel, nopython, numba_supported_reductions
+    ):
+        func, kwargs = numba_supported_reductions
+        df = DataFrame({"a": [3, 2, 3, 2], "b": range(4), "c": range(1, 5)})
+        engine_kwargs = {"nogil": nogil, "parallel": parallel, "nopython": nopython}
+        gb = df.groupby("a", sort=sort)["c"]
+        result = getattr(gb, func)(
+            engine="numba", engine_kwargs=engine_kwargs, **kwargs
+        )
+        expected = getattr(gb, func)(**kwargs)
+        tm.assert_series_equal(result, expected)
+
+    def test_cython_vs_numba_series(
+        self, sort, nogil, parallel, nopython, numba_supported_reductions
+    ):
+        func, kwargs = numba_supported_reductions
+        ser = Series(range(3), index=[1, 2, 1], name="foo")
+        engine_kwargs = {"nogil": nogil, "parallel": parallel, "nopython": nopython}
+        gb = ser.groupby(level=0, sort=sort)
+        result = getattr(gb, func)(
+            engine="numba", engine_kwargs=engine_kwargs, **kwargs
+        )
+        expected = getattr(gb, func)(**kwargs)
+        tm.assert_series_equal(result, expected)
+
+    def test_as_index_false_unsupported(self, numba_supported_reductions):
+        func, kwargs = numba_supported_reductions
+        df = DataFrame({"a": [3, 2, 3, 2], "b": range(4), "c": range(1, 5)})
+        gb = df.groupby("a", as_index=False)
+        with pytest.raises(NotImplementedError, match="as_index=False"):
+            getattr(gb, func)(engine="numba", **kwargs)
+
+    def test_axis_1_unsupported(self, numba_supported_reductions):
+        func, kwargs = numba_supported_reductions
+        df = DataFrame({"a": [3, 2, 3, 2], "b": range(4), "c": range(1, 5)})
+        gb = df.groupby("a", axis=1)
+        with pytest.raises(NotImplementedError, match="axis=1"):
+            getattr(gb, func)(engine="numba", **kwargs)
+
+    def test_no_engine_doesnt_raise(self):
+        # GH55520
+        df = DataFrame({"a": [3, 2, 3, 2], "b": range(4), "c": range(1, 5)})
+        gb = df.groupby("a")
+        # Make sure behavior of functions w/out engine argument don't raise
+        # when the global use_numba option is set
+        with option_context("compute.use_numba", True):
+            res = gb.agg({"b": "first"})
+        expected = gb.agg({"b": "first"})
+        tm.assert_frame_equal(res, expected)