Updated script that can be controled by Nodejs web app

lib/python3.13/site-packages/pandas/tests/indexes/period/methods/test_to_timestamp.py

@@ -0,0 +1,142 @@
+from datetime import datetime
+
+import numpy as np
+import pytest
+
+from pandas import (
+    DatetimeIndex,
+    NaT,
+    PeriodIndex,
+    Timedelta,
+    Timestamp,
+    date_range,
+    period_range,
+)
+import pandas._testing as tm
+
+
+class TestToTimestamp:
+    def test_to_timestamp_non_contiguous(self):
+        # GH#44100
+        dti = date_range("2021-10-18", periods=9, freq="D")
+        pi = dti.to_period()
+
+        result = pi[::2].to_timestamp()
+        expected = dti[::2]
+        tm.assert_index_equal(result, expected)
+
+        result = pi._data[::2].to_timestamp()
+        expected = dti._data[::2]
+        # TODO: can we get the freq to round-trip?
+        tm.assert_datetime_array_equal(result, expected, check_freq=False)
+
+        result = pi[::-1].to_timestamp()
+        expected = dti[::-1]
+        tm.assert_index_equal(result, expected)
+
+        result = pi._data[::-1].to_timestamp()
+        expected = dti._data[::-1]
+        tm.assert_datetime_array_equal(result, expected, check_freq=False)
+
+        result = pi[::2][::-1].to_timestamp()
+        expected = dti[::2][::-1]
+        tm.assert_index_equal(result, expected)
+
+        result = pi._data[::2][::-1].to_timestamp()
+        expected = dti._data[::2][::-1]
+        tm.assert_datetime_array_equal(result, expected, check_freq=False)
+
+    def test_to_timestamp_freq(self):
+        idx = period_range("2017", periods=12, freq="Y-DEC")
+        result = idx.to_timestamp()
+        expected = date_range("2017", periods=12, freq="YS-JAN")
+        tm.assert_index_equal(result, expected)
+
+    def test_to_timestamp_pi_nat(self):
+        # GH#7228
+        index = PeriodIndex(["NaT", "2011-01", "2011-02"], freq="M", name="idx")
+
+        result = index.to_timestamp("D")
+        expected = DatetimeIndex(
+            [NaT, datetime(2011, 1, 1), datetime(2011, 2, 1)],
+            dtype="M8[ns]",
+            name="idx",
+        )
+        tm.assert_index_equal(result, expected)
+        assert result.name == "idx"
+
+        result2 = result.to_period(freq="M")
+        tm.assert_index_equal(result2, index)
+        assert result2.name == "idx"
+
+        result3 = result.to_period(freq="3M")
+        exp = PeriodIndex(["NaT", "2011-01", "2011-02"], freq="3M", name="idx")
+        tm.assert_index_equal(result3, exp)
+        assert result3.freqstr == "3M"
+
+        msg = "Frequency must be positive, because it represents span: -2Y"
+        with pytest.raises(ValueError, match=msg):
+            result.to_period(freq="-2Y")
+
+    def test_to_timestamp_preserve_name(self):
+        index = period_range(freq="Y", start="1/1/2001", end="12/1/2009", name="foo")
+        assert index.name == "foo"
+
+        conv = index.to_timestamp("D")
+        assert conv.name == "foo"
+
+    def test_to_timestamp_quarterly_bug(self):
+        years = np.arange(1960, 2000).repeat(4)
+        quarters = np.tile(list(range(1, 5)), 40)
+
+        pindex = PeriodIndex.from_fields(year=years, quarter=quarters)
+
+        stamps = pindex.to_timestamp("D", "end")
+        expected = DatetimeIndex([x.to_timestamp("D", "end") for x in pindex])
+        tm.assert_index_equal(stamps, expected)
+        assert stamps.freq == expected.freq
+
+    def test_to_timestamp_pi_mult(self):
+        idx = PeriodIndex(["2011-01", "NaT", "2011-02"], freq="2M", name="idx")
+
+        result = idx.to_timestamp()
+        expected = DatetimeIndex(
+            ["2011-01-01", "NaT", "2011-02-01"], dtype="M8[ns]", name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+
+        result = idx.to_timestamp(how="E")
+        expected = DatetimeIndex(
+            ["2011-02-28", "NaT", "2011-03-31"], dtype="M8[ns]", name="idx"
+        )
+        expected = expected + Timedelta(1, "D") - Timedelta(1, "ns")
+        tm.assert_index_equal(result, expected)
+
+    def test_to_timestamp_pi_combined(self):
+        idx = period_range(start="2011", periods=2, freq="1D1h", name="idx")
+
+        result = idx.to_timestamp()
+        expected = DatetimeIndex(
+            ["2011-01-01 00:00", "2011-01-02 01:00"], dtype="M8[ns]", name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+
+        result = idx.to_timestamp(how="E")
+        expected = DatetimeIndex(
+            ["2011-01-02 00:59:59", "2011-01-03 01:59:59"], name="idx", dtype="M8[ns]"
+        )
+        expected = expected + Timedelta(1, "s") - Timedelta(1, "ns")
+        tm.assert_index_equal(result, expected)
+
+        result = idx.to_timestamp(how="E", freq="h")
+        expected = DatetimeIndex(
+            ["2011-01-02 00:00", "2011-01-03 01:00"], dtype="M8[ns]", name="idx"
+        )
+        expected = expected + Timedelta(1, "h") - Timedelta(1, "ns")
+        tm.assert_index_equal(result, expected)
+
+    def test_to_timestamp_1703(self):
+        index = period_range("1/1/2012", periods=4, freq="D")
+
+        result = index.to_timestamp()
+        assert result[0] == Timestamp("1/1/2012")