Updated script that can be controled by Nodejs web app

lib/python3.13/site-packages/pandas/tests/io/parser/test_upcast.py

@@ -0,0 +1,102 @@
+import numpy as np
+import pytest
+
+from pandas._libs.parsers import (
+    _maybe_upcast,
+    na_values,
+)
+
+import pandas as pd
+from pandas import NA
+import pandas._testing as tm
+from pandas.core.arrays import (
+    ArrowStringArray,
+    BooleanArray,
+    FloatingArray,
+    IntegerArray,
+    StringArray,
+)
+
+
+def test_maybe_upcast(any_real_numpy_dtype):
+    # GH#36712
+
+    dtype = np.dtype(any_real_numpy_dtype)
+    na_value = na_values[dtype]
+    arr = np.array([1, 2, na_value], dtype=dtype)
+    result = _maybe_upcast(arr, use_dtype_backend=True)
+
+    expected_mask = np.array([False, False, True])
+    if issubclass(dtype.type, np.integer):
+        expected = IntegerArray(arr, mask=expected_mask)
+    else:
+        expected = FloatingArray(arr, mask=expected_mask)
+
+    tm.assert_extension_array_equal(result, expected)
+
+
+def test_maybe_upcast_no_na(any_real_numpy_dtype):
+    # GH#36712
+    arr = np.array([1, 2, 3], dtype=any_real_numpy_dtype)
+    result = _maybe_upcast(arr, use_dtype_backend=True)
+
+    expected_mask = np.array([False, False, False])
+    if issubclass(np.dtype(any_real_numpy_dtype).type, np.integer):
+        expected = IntegerArray(arr, mask=expected_mask)
+    else:
+        expected = FloatingArray(arr, mask=expected_mask)
+
+    tm.assert_extension_array_equal(result, expected)
+
+
+def test_maybe_upcaste_bool():
+    # GH#36712
+    dtype = np.bool_
+    na_value = na_values[dtype]
+    arr = np.array([True, False, na_value], dtype="uint8").view(dtype)
+    result = _maybe_upcast(arr, use_dtype_backend=True)
+
+    expected_mask = np.array([False, False, True])
+    expected = BooleanArray(arr, mask=expected_mask)
+    tm.assert_extension_array_equal(result, expected)
+
+
+def test_maybe_upcaste_bool_no_nan():
+    # GH#36712
+    dtype = np.bool_
+    arr = np.array([True, False, False], dtype="uint8").view(dtype)
+    result = _maybe_upcast(arr, use_dtype_backend=True)
+
+    expected_mask = np.array([False, False, False])
+    expected = BooleanArray(arr, mask=expected_mask)
+    tm.assert_extension_array_equal(result, expected)
+
+
+def test_maybe_upcaste_all_nan():
+    # GH#36712
+    dtype = np.int64
+    na_value = na_values[dtype]
+    arr = np.array([na_value, na_value], dtype=dtype)
+    result = _maybe_upcast(arr, use_dtype_backend=True)
+
+    expected_mask = np.array([True, True])
+    expected = IntegerArray(arr, mask=expected_mask)
+    tm.assert_extension_array_equal(result, expected)
+
+
+@pytest.mark.parametrize("val", [na_values[np.object_], "c"])
+def test_maybe_upcast_object(val, string_storage):
+    # GH#36712
+    pa = pytest.importorskip("pyarrow")
+
+    with pd.option_context("mode.string_storage", string_storage):
+        arr = np.array(["a", "b", val], dtype=np.object_)
+        result = _maybe_upcast(arr, use_dtype_backend=True)
+
+        if string_storage == "python":
+            exp_val = "c" if val == "c" else NA
+            expected = StringArray(np.array(["a", "b", exp_val], dtype=np.object_))
+        else:
+            exp_val = "c" if val == "c" else None
+            expected = ArrowStringArray(pa.array(["a", "b", exp_val]))
+        tm.assert_extension_array_equal(result, expected)