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| import numpy as np
| import pytest
|
| from pandas._libs.tslibs import (
| Period,
| to_offset,
| )
|
|
| @pytest.mark.parametrize(
| "freqstr,exp_freqstr",
| [("D", "D"), ("W", "D"), ("ME", "D"), ("s", "s"), ("min", "s"), ("h", "s")],
| )
| def test_get_to_timestamp_base(freqstr, exp_freqstr):
| off = to_offset(freqstr)
| per = Period._from_ordinal(1, off)
| exp_code = to_offset(exp_freqstr)._period_dtype_code
|
| result_code = per._dtype._get_to_timestamp_base()
| assert result_code == exp_code
|
|
| @pytest.mark.parametrize(
| "args,expected",
| [
| ((1.5, "min"), (90, "s")),
| ((62.4, "min"), (3744, "s")),
| ((1.04, "h"), (3744, "s")),
| ((1, "D"), (1, "D")),
| ((0.342931, "h"), (1234551600, "us")),
| ((1.2345, "D"), (106660800, "ms")),
| ],
| )
| def test_resolution_bumping(args, expected):
| # see gh-14378
| off = to_offset(str(args[0]) + args[1])
| assert off.n == expected[0]
| assert off._prefix == expected[1]
|
|
| @pytest.mark.parametrize(
| "args",
| [
| (0.5, "ns"),
| # Too much precision in the input can prevent.
| (0.3429324798798269273987982, "h"),
| ],
| )
| def test_cat(args):
| msg = "Invalid frequency"
|
| with pytest.raises(ValueError, match=msg):
| to_offset(str(args[0]) + args[1])
|
|
| @pytest.mark.parametrize(
| "freqstr,expected",
| [
| ("1h", "2021-01-01T09:00:00"),
| ("1D", "2021-01-02T08:00:00"),
| ("1W", "2021-01-03T08:00:00"),
| ("1ME", "2021-01-31T08:00:00"),
| ("1YE", "2021-12-31T08:00:00"),
| ],
| )
| def test_compatibility(freqstr, expected):
| ts_np = np.datetime64("2021-01-01T08:00:00.00")
| do = to_offset(freqstr)
| assert ts_np + do == np.datetime64(expected)
|
|
