| import numpy as np |
|
|
| from pandas._libs.tslibs.dtypes import abbrev_to_npy_unit |
| from pandas._libs.tslibs.vectorized import is_date_array_normalized |
|
|
| |
| day_arr = np.arange(10, dtype="i8").view("M8[D]") |
|
|
|
|
| class TestIsDateArrayNormalized: |
| def test_is_date_array_normalized_day(self): |
| arr = day_arr |
| abbrev = "D" |
| unit = abbrev_to_npy_unit(abbrev) |
| result = is_date_array_normalized(arr.view("i8"), None, unit) |
| assert result is True |
|
|
| def test_is_date_array_normalized_seconds(self): |
| abbrev = "s" |
| arr = day_arr.astype(f"M8[{abbrev}]") |
| unit = abbrev_to_npy_unit(abbrev) |
| result = is_date_array_normalized(arr.view("i8"), None, unit) |
| assert result is True |
|
|
| arr[0] += np.timedelta64(1, abbrev) |
| result2 = is_date_array_normalized(arr.view("i8"), None, unit) |
| assert result2 is False |
|
|