Updated script that can be controled by Nodejs web app

lib/python3.13/site-packages/pandas/tests/io/pytables/test_complex.py

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+import numpy as np
+import pytest
+
+import pandas as pd
+from pandas import (
+    DataFrame,
+    Series,
+)
+import pandas._testing as tm
+from pandas.tests.io.pytables.common import ensure_clean_store
+
+from pandas.io.pytables import read_hdf
+
+
+def test_complex_fixed(tmp_path, setup_path):
+    df = DataFrame(
+        np.random.default_rng(2).random((4, 5)).astype(np.complex64),
+        index=list("abcd"),
+        columns=list("ABCDE"),
+    )
+
+    path = tmp_path / setup_path
+    df.to_hdf(path, key="df")
+    reread = read_hdf(path, "df")
+    tm.assert_frame_equal(df, reread)
+
+    df = DataFrame(
+        np.random.default_rng(2).random((4, 5)).astype(np.complex128),
+        index=list("abcd"),
+        columns=list("ABCDE"),
+    )
+    path = tmp_path / setup_path
+    df.to_hdf(path, key="df")
+    reread = read_hdf(path, "df")
+    tm.assert_frame_equal(df, reread)
+
+
+def test_complex_table(tmp_path, setup_path):
+    df = DataFrame(
+        np.random.default_rng(2).random((4, 5)).astype(np.complex64),
+        index=list("abcd"),
+        columns=list("ABCDE"),
+    )
+
+    path = tmp_path / setup_path
+    df.to_hdf(path, key="df", format="table")
+    reread = read_hdf(path, key="df")
+    tm.assert_frame_equal(df, reread)
+
+    df = DataFrame(
+        np.random.default_rng(2).random((4, 5)).astype(np.complex128),
+        index=list("abcd"),
+        columns=list("ABCDE"),
+    )
+
+    path = tmp_path / setup_path
+    df.to_hdf(path, key="df", format="table", mode="w")
+    reread = read_hdf(path, "df")
+    tm.assert_frame_equal(df, reread)
+
+
+def test_complex_mixed_fixed(tmp_path, setup_path):
+    complex64 = np.array(
+        [1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j], dtype=np.complex64
+    )
+    complex128 = np.array(
+        [1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j], dtype=np.complex128
+    )
+    df = DataFrame(
+        {
+            "A": [1, 2, 3, 4],
+            "B": ["a", "b", "c", "d"],
+            "C": complex64,
+            "D": complex128,
+            "E": [1.0, 2.0, 3.0, 4.0],
+        },
+        index=list("abcd"),
+    )
+    path = tmp_path / setup_path
+    df.to_hdf(path, key="df")
+    reread = read_hdf(path, "df")
+    tm.assert_frame_equal(df, reread)
+
+
+def test_complex_mixed_table(tmp_path, setup_path):
+    complex64 = np.array(
+        [1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j], dtype=np.complex64
+    )
+    complex128 = np.array(
+        [1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j], dtype=np.complex128
+    )
+    df = DataFrame(
+        {
+            "A": [1, 2, 3, 4],
+            "B": ["a", "b", "c", "d"],
+            "C": complex64,
+            "D": complex128,
+            "E": [1.0, 2.0, 3.0, 4.0],
+        },
+        index=list("abcd"),
+    )
+
+    with ensure_clean_store(setup_path) as store:
+        store.append("df", df, data_columns=["A", "B"])
+        result = store.select("df", where="A>2")
+        tm.assert_frame_equal(df.loc[df.A > 2], result)
+
+    path = tmp_path / setup_path
+    df.to_hdf(path, key="df", format="table")
+    reread = read_hdf(path, "df")
+    tm.assert_frame_equal(df, reread)
+
+
+def test_complex_across_dimensions_fixed(tmp_path, setup_path):
+    complex128 = np.array([1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j])
+    s = Series(complex128, index=list("abcd"))
+    df = DataFrame({"A": s, "B": s})
+
+    objs = [s, df]
+    comps = [tm.assert_series_equal, tm.assert_frame_equal]
+    for obj, comp in zip(objs, comps):
+        path = tmp_path / setup_path
+        obj.to_hdf(path, key="obj", format="fixed")
+        reread = read_hdf(path, "obj")
+        comp(obj, reread)
+
+
+def test_complex_across_dimensions(tmp_path, setup_path):
+    complex128 = np.array([1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j])
+    s = Series(complex128, index=list("abcd"))
+    df = DataFrame({"A": s, "B": s})
+
+    path = tmp_path / setup_path
+    df.to_hdf(path, key="obj", format="table")
+    reread = read_hdf(path, "obj")
+    tm.assert_frame_equal(df, reread)
+
+
+def test_complex_indexing_error(setup_path):
+    complex128 = np.array(
+        [1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j], dtype=np.complex128
+    )
+    df = DataFrame(
+        {"A": [1, 2, 3, 4], "B": ["a", "b", "c", "d"], "C": complex128},
+        index=list("abcd"),
+    )
+
+    msg = (
+        "Columns containing complex values can be stored "
+        "but cannot be indexed when using table format. "
+        "Either use fixed format, set index=False, "
+        "or do not include the columns containing complex "
+        "values to data_columns when initializing the table."
+    )
+
+    with ensure_clean_store(setup_path) as store:
+        with pytest.raises(TypeError, match=msg):
+            store.append("df", df, data_columns=["C"])
+
+
+def test_complex_series_error(tmp_path, setup_path):
+    complex128 = np.array([1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j])
+    s = Series(complex128, index=list("abcd"))
+
+    msg = (
+        "Columns containing complex values can be stored "
+        "but cannot be indexed when using table format. "
+        "Either use fixed format, set index=False, "
+        "or do not include the columns containing complex "
+        "values to data_columns when initializing the table."
+    )
+
+    path = tmp_path / setup_path
+    with pytest.raises(TypeError, match=msg):
+        s.to_hdf(path, key="obj", format="t")
+
+    path = tmp_path / setup_path
+    s.to_hdf(path, key="obj", format="t", index=False)
+    reread = read_hdf(path, "obj")
+    tm.assert_series_equal(s, reread)
+
+
+def test_complex_append(setup_path):
+    df = DataFrame(
+        {
+            "a": np.random.default_rng(2).standard_normal(100).astype(np.complex128),
+            "b": np.random.default_rng(2).standard_normal(100),
+        }
+    )
+
+    with ensure_clean_store(setup_path) as store:
+        store.append("df", df, data_columns=["b"])
+        store.append("df", df)
+        result = store.select("df")
+        tm.assert_frame_equal(pd.concat([df, df], axis=0), result)