Updated script that can be controled by Nodejs web app

lib/python3.13/site-packages/pandas/tests/indexes/period/methods/test_astype.py

@@ -0,0 +1,151 @@
+import numpy as np
+import pytest
+
+from pandas import (
+    CategoricalIndex,
+    DatetimeIndex,
+    Index,
+    NaT,
+    Period,
+    PeriodIndex,
+    period_range,
+)
+import pandas._testing as tm
+
+
+class TestPeriodIndexAsType:
+    @pytest.mark.parametrize("dtype", [float, "timedelta64", "timedelta64[ns]"])
+    def test_astype_raises(self, dtype):
+        # GH#13149, GH#13209
+        idx = PeriodIndex(["2016-05-16", "NaT", NaT, np.nan], freq="D")
+        msg = "Cannot cast PeriodIndex to dtype"
+        with pytest.raises(TypeError, match=msg):
+            idx.astype(dtype)
+
+    def test_astype_conversion(self):
+        # GH#13149, GH#13209
+        idx = PeriodIndex(["2016-05-16", "NaT", NaT, np.nan], freq="D", name="idx")
+
+        result = idx.astype(object)
+        expected = Index(
+            [Period("2016-05-16", freq="D")] + [Period(NaT, freq="D")] * 3,
+            dtype="object",
+            name="idx",
+        )
+        tm.assert_index_equal(result, expected)
+
+        result = idx.astype(np.int64)
+        expected = Index(
+            [16937] + [-9223372036854775808] * 3, dtype=np.int64, name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+
+        result = idx.astype(str)
+        expected = Index([str(x) for x in idx], name="idx", dtype=object)
+        tm.assert_index_equal(result, expected)
+
+        idx = period_range("1990", "2009", freq="Y", name="idx")
+        result = idx.astype("i8")
+        tm.assert_index_equal(result, Index(idx.asi8, name="idx"))
+        tm.assert_numpy_array_equal(result.values, idx.asi8)
+
+    def test_astype_uint(self):
+        arr = period_range("2000", periods=2, name="idx")
+
+        with pytest.raises(TypeError, match=r"Do obj.astype\('int64'\)"):
+            arr.astype("uint64")
+        with pytest.raises(TypeError, match=r"Do obj.astype\('int64'\)"):
+            arr.astype("uint32")
+
+    def test_astype_object(self):
+        idx = PeriodIndex([], freq="M")
+
+        exp = np.array([], dtype=object)
+        tm.assert_numpy_array_equal(idx.astype(object).values, exp)
+        tm.assert_numpy_array_equal(idx._mpl_repr(), exp)
+
+        idx = PeriodIndex(["2011-01", NaT], freq="M")
+
+        exp = np.array([Period("2011-01", freq="M"), NaT], dtype=object)
+        tm.assert_numpy_array_equal(idx.astype(object).values, exp)
+        tm.assert_numpy_array_equal(idx._mpl_repr(), exp)
+
+        exp = np.array([Period("2011-01-01", freq="D"), NaT], dtype=object)
+        idx = PeriodIndex(["2011-01-01", NaT], freq="D")
+        tm.assert_numpy_array_equal(idx.astype(object).values, exp)
+        tm.assert_numpy_array_equal(idx._mpl_repr(), exp)
+
+    # TODO: de-duplicate this version (from test_ops) with the one above
+    # (from test_period)
+    def test_astype_object2(self):
+        idx = period_range(start="2013-01-01", periods=4, freq="M", name="idx")
+        expected_list = [
+            Period("2013-01-31", freq="M"),
+            Period("2013-02-28", freq="M"),
+            Period("2013-03-31", freq="M"),
+            Period("2013-04-30", freq="M"),
+        ]
+        expected = Index(expected_list, dtype=object, name="idx")
+        result = idx.astype(object)
+        assert isinstance(result, Index)
+        assert result.dtype == object
+        tm.assert_index_equal(result, expected)
+        assert result.name == expected.name
+        assert idx.tolist() == expected_list
+
+        idx = PeriodIndex(
+            ["2013-01-01", "2013-01-02", "NaT", "2013-01-04"], freq="D", name="idx"
+        )
+        expected_list = [
+            Period("2013-01-01", freq="D"),
+            Period("2013-01-02", freq="D"),
+            Period("NaT", freq="D"),
+            Period("2013-01-04", freq="D"),
+        ]
+        expected = Index(expected_list, dtype=object, name="idx")
+        result = idx.astype(object)
+        assert isinstance(result, Index)
+        assert result.dtype == object
+        tm.assert_index_equal(result, expected)
+        for i in [0, 1, 3]:
+            assert result[i] == expected[i]
+        assert result[2] is NaT
+        assert result.name == expected.name
+
+        result_list = idx.tolist()
+        for i in [0, 1, 3]:
+            assert result_list[i] == expected_list[i]
+        assert result_list[2] is NaT
+
+    def test_astype_category(self):
+        obj = period_range("2000", periods=2, name="idx")
+        result = obj.astype("category")
+        expected = CategoricalIndex(
+            [Period("2000-01-01", freq="D"), Period("2000-01-02", freq="D")], name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+
+        result = obj._data.astype("category")
+        expected = expected.values
+        tm.assert_categorical_equal(result, expected)
+
+    def test_astype_array_fallback(self):
+        obj = period_range("2000", periods=2, name="idx")
+        result = obj.astype(bool)
+        expected = Index(np.array([True, True]), name="idx")
+        tm.assert_index_equal(result, expected)
+
+        result = obj._data.astype(bool)
+        expected = np.array([True, True])
+        tm.assert_numpy_array_equal(result, expected)
+
+    def test_period_astype_to_timestamp(self, unit):
+        # GH#55958
+        pi = PeriodIndex(["2011-01", "2011-02", "2011-03"], freq="M")
+
+        exp = DatetimeIndex(
+            ["2011-01-01", "2011-02-01", "2011-03-01"], tz="US/Eastern"
+        ).as_unit(unit)
+        res = pi.astype(f"datetime64[{unit}, US/Eastern]")
+        tm.assert_index_equal(res, exp)
+        assert res.freq == exp.freq