Updated script that can be controled by Nodejs web app

lib/python3.13/site-packages/pandas/tests/series/methods/test_update.py

@@ -0,0 +1,139 @@
+import numpy as np
+import pytest
+
+import pandas.util._test_decorators as td
+
+from pandas import (
+    CategoricalDtype,
+    DataFrame,
+    NaT,
+    Series,
+    Timestamp,
+)
+import pandas._testing as tm
+
+
+class TestUpdate:
+    def test_update(self, using_copy_on_write):
+        s = Series([1.5, np.nan, 3.0, 4.0, np.nan])
+        s2 = Series([np.nan, 3.5, np.nan, 5.0])
+        s.update(s2)
+
+        expected = Series([1.5, 3.5, 3.0, 5.0, np.nan])
+        tm.assert_series_equal(s, expected)
+
+        # GH 3217
+        df = DataFrame([{"a": 1}, {"a": 3, "b": 2}])
+        df["c"] = np.nan
+        # Cast to object to avoid upcast when setting "foo"
+        df["c"] = df["c"].astype(object)
+        df_orig = df.copy()
+
+        if using_copy_on_write:
+            with tm.raises_chained_assignment_error():
+                df["c"].update(Series(["foo"], index=[0]))
+            expected = df_orig
+        else:
+            with tm.assert_produces_warning(FutureWarning, match="inplace method"):
+                df["c"].update(Series(["foo"], index=[0]))
+            expected = DataFrame(
+                [[1, np.nan, "foo"], [3, 2.0, np.nan]], columns=["a", "b", "c"]
+            )
+            expected["c"] = expected["c"].astype(object)
+        tm.assert_frame_equal(df, expected)
+
+    @pytest.mark.parametrize(
+        "other, dtype, expected, warn",
+        [
+            # other is int
+            ([61, 63], "int32", Series([10, 61, 12], dtype="int32"), None),
+            ([61, 63], "int64", Series([10, 61, 12]), None),
+            ([61, 63], float, Series([10.0, 61.0, 12.0]), None),
+            ([61, 63], object, Series([10, 61, 12], dtype=object), None),
+            # other is float, but can be cast to int
+            ([61.0, 63.0], "int32", Series([10, 61, 12], dtype="int32"), None),
+            ([61.0, 63.0], "int64", Series([10, 61, 12]), None),
+            ([61.0, 63.0], float, Series([10.0, 61.0, 12.0]), None),
+            ([61.0, 63.0], object, Series([10, 61.0, 12], dtype=object), None),
+            # others is float, cannot be cast to int
+            ([61.1, 63.1], "int32", Series([10.0, 61.1, 12.0]), FutureWarning),
+            ([61.1, 63.1], "int64", Series([10.0, 61.1, 12.0]), FutureWarning),
+            ([61.1, 63.1], float, Series([10.0, 61.1, 12.0]), None),
+            ([61.1, 63.1], object, Series([10, 61.1, 12], dtype=object), None),
+            # other is object, cannot be cast
+            ([(61,), (63,)], "int32", Series([10, (61,), 12]), FutureWarning),
+            ([(61,), (63,)], "int64", Series([10, (61,), 12]), FutureWarning),
+            ([(61,), (63,)], float, Series([10.0, (61,), 12.0]), FutureWarning),
+            ([(61,), (63,)], object, Series([10, (61,), 12]), None),
+        ],
+    )
+    def test_update_dtypes(self, other, dtype, expected, warn):
+        ser = Series([10, 11, 12], dtype=dtype)
+        other = Series(other, index=[1, 3])
+        with tm.assert_produces_warning(warn, match="item of incompatible dtype"):
+            ser.update(other)
+
+        tm.assert_series_equal(ser, expected)
+
+    @pytest.mark.parametrize(
+        "series, other, expected",
+        [
+            # update by key
+            (
+                Series({"a": 1, "b": 2, "c": 3, "d": 4}),
+                {"b": 5, "c": np.nan},
+                Series({"a": 1, "b": 5, "c": 3, "d": 4}),
+            ),
+            # update by position
+            (Series([1, 2, 3, 4]), [np.nan, 5, 1], Series([1, 5, 1, 4])),
+        ],
+    )
+    def test_update_from_non_series(self, series, other, expected):
+        # GH 33215
+        series.update(other)
+        tm.assert_series_equal(series, expected)
+
+    @pytest.mark.parametrize(
+        "data, other, expected, dtype",
+        [
+            (["a", None], [None, "b"], ["a", "b"], "string[python]"),
+            pytest.param(
+                ["a", None],
+                [None, "b"],
+                ["a", "b"],
+                "string[pyarrow]",
+                marks=td.skip_if_no("pyarrow"),
+            ),
+            ([1, None], [None, 2], [1, 2], "Int64"),
+            ([True, None], [None, False], [True, False], "boolean"),
+            (
+                ["a", None],
+                [None, "b"],
+                ["a", "b"],
+                CategoricalDtype(categories=["a", "b"]),
+            ),
+            (
+                [Timestamp(year=2020, month=1, day=1, tz="Europe/London"), NaT],
+                [NaT, Timestamp(year=2020, month=1, day=1, tz="Europe/London")],
+                [Timestamp(year=2020, month=1, day=1, tz="Europe/London")] * 2,
+                "datetime64[ns, Europe/London]",
+            ),
+        ],
+    )
+    def test_update_extension_array_series(self, data, other, expected, dtype):
+        result = Series(data, dtype=dtype)
+        other = Series(other, dtype=dtype)
+        expected = Series(expected, dtype=dtype)
+
+        result.update(other)
+        tm.assert_series_equal(result, expected)
+
+    def test_update_with_categorical_type(self):
+        # GH 25744
+        dtype = CategoricalDtype(["a", "b", "c", "d"])
+        s1 = Series(["a", "b", "c"], index=[1, 2, 3], dtype=dtype)
+        s2 = Series(["b", "a"], index=[1, 2], dtype=dtype)
+        s1.update(s2)
+        result = s1
+        expected = Series(["b", "a", "c"], index=[1, 2, 3], dtype=dtype)
+        tm.assert_series_equal(result, expected)