Updated script that can be controled by Nodejs web app

lib/python3.13/site-packages/pandas/tests/indexing/test_datetime.py

@@ -0,0 +1,191 @@
+import re
+
+import pytest
+
+import pandas as pd
+from pandas import (
+    DataFrame,
+    Index,
+    Series,
+    Timestamp,
+    date_range,
+)
+import pandas._testing as tm
+
+
+class TestDatetimeIndex:
+    def test_get_loc_naive_dti_aware_str_deprecated(self):
+        # GH#46903
+        ts = Timestamp("20130101")._value
+        dti = pd.DatetimeIndex([ts + 50 + i for i in range(100)])
+        ser = Series(range(100), index=dti)
+
+        key = "2013-01-01 00:00:00.000000050+0000"
+        msg = re.escape(repr(key))
+        with pytest.raises(KeyError, match=msg):
+            ser[key]
+
+        with pytest.raises(KeyError, match=msg):
+            dti.get_loc(key)
+
+    def test_indexing_with_datetime_tz(self):
+        # GH#8260
+        # support datetime64 with tz
+
+        idx = Index(date_range("20130101", periods=3, tz="US/Eastern"), name="foo")
+        dr = date_range("20130110", periods=3)
+        df = DataFrame({"A": idx, "B": dr})
+        df["C"] = idx
+        df.iloc[1, 1] = pd.NaT
+        df.iloc[1, 2] = pd.NaT
+
+        expected = Series(
+            [Timestamp("2013-01-02 00:00:00-0500", tz="US/Eastern"), pd.NaT, pd.NaT],
+            index=list("ABC"),
+            dtype="object",
+            name=1,
+        )
+
+        # indexing
+        result = df.iloc[1]
+        tm.assert_series_equal(result, expected)
+        result = df.loc[1]
+        tm.assert_series_equal(result, expected)
+
+    def test_indexing_fast_xs(self):
+        # indexing - fast_xs
+        df = DataFrame({"a": date_range("2014-01-01", periods=10, tz="UTC")})
+        result = df.iloc[5]
+        expected = Series(
+            [Timestamp("2014-01-06 00:00:00+0000", tz="UTC")],
+            index=["a"],
+            name=5,
+            dtype="M8[ns, UTC]",
+        )
+        tm.assert_series_equal(result, expected)
+
+        result = df.loc[5]
+        tm.assert_series_equal(result, expected)
+
+        # indexing - boolean
+        result = df[df.a > df.a[3]]
+        expected = df.iloc[4:]
+        tm.assert_frame_equal(result, expected)
+
+    def test_consistency_with_tz_aware_scalar(self):
+        # xef gh-12938
+        # various ways of indexing the same tz-aware scalar
+        df = Series([Timestamp("2016-03-30 14:35:25", tz="Europe/Brussels")]).to_frame()
+
+        df = pd.concat([df, df]).reset_index(drop=True)
+        expected = Timestamp("2016-03-30 14:35:25+0200", tz="Europe/Brussels")
+
+        result = df[0][0]
+        assert result == expected
+
+        result = df.iloc[0, 0]
+        assert result == expected
+
+        result = df.loc[0, 0]
+        assert result == expected
+
+        result = df.iat[0, 0]
+        assert result == expected
+
+        result = df.at[0, 0]
+        assert result == expected
+
+        result = df[0].loc[0]
+        assert result == expected
+
+        result = df[0].at[0]
+        assert result == expected
+
+    def test_indexing_with_datetimeindex_tz(self, indexer_sl):
+        # GH 12050
+        # indexing on a series with a datetimeindex with tz
+        index = date_range("2015-01-01", periods=2, tz="utc")
+
+        ser = Series(range(2), index=index, dtype="int64")
+
+        # list-like indexing
+
+        for sel in (index, list(index)):
+            # getitem
+            result = indexer_sl(ser)[sel]
+            expected = ser.copy()
+            if sel is not index:
+                expected.index = expected.index._with_freq(None)
+            tm.assert_series_equal(result, expected)
+
+            # setitem
+            result = ser.copy()
+            indexer_sl(result)[sel] = 1
+            expected = Series(1, index=index)
+            tm.assert_series_equal(result, expected)
+
+        # single element indexing
+
+        # getitem
+        assert indexer_sl(ser)[index[1]] == 1
+
+        # setitem
+        result = ser.copy()
+        indexer_sl(result)[index[1]] = 5
+        expected = Series([0, 5], index=index)
+        tm.assert_series_equal(result, expected)
+
+    def test_nanosecond_getitem_setitem_with_tz(self):
+        # GH 11679
+        data = ["2016-06-28 08:30:00.123456789"]
+        index = pd.DatetimeIndex(data, dtype="datetime64[ns, America/Chicago]")
+        df = DataFrame({"a": [10]}, index=index)
+        result = df.loc[df.index[0]]
+        expected = Series(10, index=["a"], name=df.index[0])
+        tm.assert_series_equal(result, expected)
+
+        result = df.copy()
+        result.loc[df.index[0], "a"] = -1
+        expected = DataFrame(-1, index=index, columns=["a"])
+        tm.assert_frame_equal(result, expected)
+
+    def test_getitem_str_slice_millisecond_resolution(self, frame_or_series):
+        # GH#33589
+
+        keys = [
+            "2017-10-25T16:25:04.151",
+            "2017-10-25T16:25:04.252",
+            "2017-10-25T16:50:05.237",
+            "2017-10-25T16:50:05.238",
+        ]
+        obj = frame_or_series(
+            [1, 2, 3, 4],
+            index=[Timestamp(x) for x in keys],
+        )
+        result = obj[keys[1] : keys[2]]
+        expected = frame_or_series(
+            [2, 3],
+            index=[
+                Timestamp(keys[1]),
+                Timestamp(keys[2]),
+            ],
+        )
+        tm.assert_equal(result, expected)
+
+    def test_getitem_pyarrow_index(self, frame_or_series):
+        # GH 53644
+        pytest.importorskip("pyarrow")
+        obj = frame_or_series(
+            range(5),
+            index=date_range("2020", freq="D", periods=5).astype(
+                "timestamp[us][pyarrow]"
+            ),
+        )
+        result = obj.loc[obj.index[:-3]]
+        expected = frame_or_series(
+            range(2),
+            index=date_range("2020", freq="D", periods=2).astype(
+                "timestamp[us][pyarrow]"
+            ),
+        )
+        tm.assert_equal(result, expected)