Updated script that can be controled by Nodejs web app

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

@@ -0,0 +1,175 @@
+import numpy as np
+import pytest
+
+import pandas as pd
+import pandas._testing as tm
+
+
+def test_basic():
+    s = pd.Series([[0, 1, 2], np.nan, [], (3, 4)], index=list("abcd"), name="foo")
+    result = s.explode()
+    expected = pd.Series(
+        [0, 1, 2, np.nan, np.nan, 3, 4], index=list("aaabcdd"), dtype=object, name="foo"
+    )
+    tm.assert_series_equal(result, expected)
+
+
+def test_mixed_type():
+    s = pd.Series(
+        [[0, 1, 2], np.nan, None, np.array([]), pd.Series(["a", "b"])], name="foo"
+    )
+    result = s.explode()
+    expected = pd.Series(
+        [0, 1, 2, np.nan, None, np.nan, "a", "b"],
+        index=[0, 0, 0, 1, 2, 3, 4, 4],
+        dtype=object,
+        name="foo",
+    )
+    tm.assert_series_equal(result, expected)
+
+
+def test_empty():
+    s = pd.Series(dtype=object)
+    result = s.explode()
+    expected = s.copy()
+    tm.assert_series_equal(result, expected)
+
+
+def test_nested_lists():
+    s = pd.Series([[[1, 2, 3]], [1, 2], 1])
+    result = s.explode()
+    expected = pd.Series([[1, 2, 3], 1, 2, 1], index=[0, 1, 1, 2])
+    tm.assert_series_equal(result, expected)
+
+
+def test_multi_index():
+    s = pd.Series(
+        [[0, 1, 2], np.nan, [], (3, 4)],
+        name="foo",
+        index=pd.MultiIndex.from_product([list("ab"), range(2)], names=["foo", "bar"]),
+    )
+    result = s.explode()
+    index = pd.MultiIndex.from_tuples(
+        [("a", 0), ("a", 0), ("a", 0), ("a", 1), ("b", 0), ("b", 1), ("b", 1)],
+        names=["foo", "bar"],
+    )
+    expected = pd.Series(
+        [0, 1, 2, np.nan, np.nan, 3, 4], index=index, dtype=object, name="foo"
+    )
+    tm.assert_series_equal(result, expected)
+
+
+def test_large():
+    s = pd.Series([range(256)]).explode()
+    result = s.explode()
+    tm.assert_series_equal(result, s)
+
+
+def test_invert_array():
+    df = pd.DataFrame({"a": pd.date_range("20190101", periods=3, tz="UTC")})
+
+    listify = df.apply(lambda x: x.array, axis=1)
+    result = listify.explode()
+    tm.assert_series_equal(result, df["a"].rename())
+
+
+@pytest.mark.parametrize(
+    "s", [pd.Series([1, 2, 3]), pd.Series(pd.date_range("2019", periods=3, tz="UTC"))]
+)
+def test_non_object_dtype(s):
+    result = s.explode()
+    tm.assert_series_equal(result, s)
+
+
+def test_typical_usecase():
+    df = pd.DataFrame(
+        [{"var1": "a,b,c", "var2": 1}, {"var1": "d,e,f", "var2": 2}],
+        columns=["var1", "var2"],
+    )
+    exploded = df.var1.str.split(",").explode()
+    result = df[["var2"]].join(exploded)
+    expected = pd.DataFrame(
+        {"var2": [1, 1, 1, 2, 2, 2], "var1": list("abcdef")},
+        columns=["var2", "var1"],
+        index=[0, 0, 0, 1, 1, 1],
+    )
+    tm.assert_frame_equal(result, expected)
+
+
+def test_nested_EA():
+    # a nested EA array
+    s = pd.Series(
+        [
+            pd.date_range("20170101", periods=3, tz="UTC"),
+            pd.date_range("20170104", periods=3, tz="UTC"),
+        ]
+    )
+    result = s.explode()
+    expected = pd.Series(
+        pd.date_range("20170101", periods=6, tz="UTC"), index=[0, 0, 0, 1, 1, 1]
+    )
+    tm.assert_series_equal(result, expected)
+
+
+def test_duplicate_index():
+    # GH 28005
+    s = pd.Series([[1, 2], [3, 4]], index=[0, 0])
+    result = s.explode()
+    expected = pd.Series([1, 2, 3, 4], index=[0, 0, 0, 0], dtype=object)
+    tm.assert_series_equal(result, expected)
+
+
+def test_ignore_index():
+    # GH 34932
+    s = pd.Series([[1, 2], [3, 4]])
+    result = s.explode(ignore_index=True)
+    expected = pd.Series([1, 2, 3, 4], index=[0, 1, 2, 3], dtype=object)
+    tm.assert_series_equal(result, expected)
+
+
+def test_explode_sets():
+    # https://github.com/pandas-dev/pandas/issues/35614
+    s = pd.Series([{"a", "b", "c"}], index=[1])
+    result = s.explode().sort_values()
+    expected = pd.Series(["a", "b", "c"], index=[1, 1, 1])
+    tm.assert_series_equal(result, expected)
+
+
+def test_explode_scalars_can_ignore_index():
+    # https://github.com/pandas-dev/pandas/issues/40487
+    s = pd.Series([1, 2, 3], index=["a", "b", "c"])
+    result = s.explode(ignore_index=True)
+    expected = pd.Series([1, 2, 3])
+    tm.assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize("ignore_index", [True, False])
+def test_explode_pyarrow_list_type(ignore_index):
+    # GH 53602
+    pa = pytest.importorskip("pyarrow")
+
+    data = [
+        [None, None],
+        [1],
+        [],
+        [2, 3],
+        None,
+    ]
+    ser = pd.Series(data, dtype=pd.ArrowDtype(pa.list_(pa.int64())))
+    result = ser.explode(ignore_index=ignore_index)
+    expected = pd.Series(
+        data=[None, None, 1, None, 2, 3, None],
+        index=None if ignore_index else [0, 0, 1, 2, 3, 3, 4],
+        dtype=pd.ArrowDtype(pa.int64()),
+    )
+    tm.assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize("ignore_index", [True, False])
+def test_explode_pyarrow_non_list_type(ignore_index):
+    pa = pytest.importorskip("pyarrow")
+    data = [1, 2, 3]
+    ser = pd.Series(data, dtype=pd.ArrowDtype(pa.int64()))
+    result = ser.explode(ignore_index=ignore_index)
+    expected = pd.Series([1, 2, 3], dtype="int64[pyarrow]", index=[0, 1, 2])
+    tm.assert_series_equal(result, expected)