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- import numpy as np
- import pytest
- from pandas.core.dtypes.dtypes import DatetimeTZDtype
- import pandas as pd
- import pandas._testing as tm
- from pandas.core.arrays import DatetimeArray
- from pandas.core.arrays.datetimes import _sequence_to_dt64ns
- class TestDatetimeArrayConstructor:
- def test_from_sequence_invalid_type(self):
- mi = pd.MultiIndex.from_product([np.arange(5), np.arange(5)])
- with pytest.raises(TypeError, match="Cannot create a DatetimeArray"):
- DatetimeArray._from_sequence(mi)
- def test_only_1dim_accepted(self):
- arr = np.array([0, 1, 2, 3], dtype="M8[h]").astype("M8[ns]")
- with pytest.raises(ValueError, match="Only 1-dimensional"):
- # 3-dim, we allow 2D to sneak in for ops purposes GH#29853
- DatetimeArray(arr.reshape(2, 2, 1))
- with pytest.raises(ValueError, match="Only 1-dimensional"):
- # 0-dim
- DatetimeArray(arr[[0]].squeeze())
- def test_freq_validation(self):
- # GH#24623 check that invalid instances cannot be created with the
- # public constructor
- arr = np.arange(5, dtype=np.int64) * 3600 * 10**9
- msg = (
- "Inferred frequency H from passed values does not "
- "conform to passed frequency W-SUN"
- )
- with pytest.raises(ValueError, match=msg):
- DatetimeArray(arr, freq="W")
- @pytest.mark.parametrize(
- "meth",
- [
- DatetimeArray._from_sequence,
- _sequence_to_dt64ns,
- pd.to_datetime,
- pd.DatetimeIndex,
- ],
- )
- def test_mixing_naive_tzaware_raises(self, meth):
- # GH#24569
- arr = np.array([pd.Timestamp("2000"), pd.Timestamp("2000", tz="CET")])
- msg = (
- "Cannot mix tz-aware with tz-naive values|"
- "Tz-aware datetime.datetime cannot be converted "
- "to datetime64 unless utc=True"
- )
- for obj in [arr, arr[::-1]]:
- # check that we raise regardless of whether naive is found
- # before aware or vice-versa
- with pytest.raises(ValueError, match=msg):
- meth(obj)
- def test_from_pandas_array(self):
- arr = pd.array(np.arange(5, dtype=np.int64)) * 3600 * 10**9
- result = DatetimeArray._from_sequence(arr)._with_freq("infer")
- expected = pd.date_range("1970-01-01", periods=5, freq="H")._data
- tm.assert_datetime_array_equal(result, expected)
- def test_mismatched_timezone_raises(self):
- arr = DatetimeArray(
- np.array(["2000-01-01T06:00:00"], dtype="M8[ns]"),
- dtype=DatetimeTZDtype(tz="US/Central"),
- )
- dtype = DatetimeTZDtype(tz="US/Eastern")
- msg = r"dtype=datetime64\[ns.*\] does not match data dtype datetime64\[ns.*\]"
- with pytest.raises(TypeError, match=msg):
- DatetimeArray(arr, dtype=dtype)
- # also with mismatched tzawareness
- with pytest.raises(TypeError, match=msg):
- DatetimeArray(arr, dtype=np.dtype("M8[ns]"))
- with pytest.raises(TypeError, match=msg):
- DatetimeArray(arr.tz_localize(None), dtype=arr.dtype)
- def test_non_array_raises(self):
- with pytest.raises(ValueError, match="list"):
- DatetimeArray([1, 2, 3])
- def test_bool_dtype_raises(self):
- arr = np.array([1, 2, 3], dtype="bool")
- msg = "Unexpected value for 'dtype': 'bool'. Must be"
- with pytest.raises(ValueError, match=msg):
- DatetimeArray(arr)
- msg = r"dtype bool cannot be converted to datetime64\[ns\]"
- with pytest.raises(TypeError, match=msg):
- DatetimeArray._from_sequence(arr)
- with pytest.raises(TypeError, match=msg):
- _sequence_to_dt64ns(arr)
- with pytest.raises(TypeError, match=msg):
- pd.DatetimeIndex(arr)
- with pytest.raises(TypeError, match=msg):
- pd.to_datetime(arr)
- def test_incorrect_dtype_raises(self):
- with pytest.raises(ValueError, match="Unexpected value for 'dtype'."):
- DatetimeArray(np.array([1, 2, 3], dtype="i8"), dtype="category")
- def test_freq_infer_raises(self):
- with pytest.raises(ValueError, match="Frequency inference"):
- DatetimeArray(np.array([1, 2, 3], dtype="i8"), freq="infer")
- def test_copy(self):
- data = np.array([1, 2, 3], dtype="M8[ns]")
- arr = DatetimeArray(data, copy=False)
- assert arr._ndarray is data
- arr = DatetimeArray(data, copy=True)
- assert arr._ndarray is not data
- @pytest.mark.parametrize("unit", ["s", "ms", "us", "ns"])
- def test_numpy_datetime_unit(self, unit):
- data = np.array([1, 2, 3], dtype=f"M8[{unit}]")
- arr = DatetimeArray(data)
- assert arr.unit == unit
- assert arr[0].unit == unit
- class TestSequenceToDT64NS:
- def test_tz_dtype_mismatch_raises(self):
- arr = DatetimeArray._from_sequence(
- ["2000"], dtype=DatetimeTZDtype(tz="US/Central")
- )
- with pytest.raises(TypeError, match="data is already tz-aware"):
- DatetimeArray._from_sequence_not_strict(
- arr, dtype=DatetimeTZDtype(tz="UTC")
- )
- def test_tz_dtype_matches(self):
- dtype = DatetimeTZDtype(tz="US/Central")
- arr = DatetimeArray._from_sequence(["2000"], dtype=dtype)
- result = DatetimeArray._from_sequence_not_strict(arr, dtype=dtype)
- tm.assert_equal(arr, result)
- @pytest.mark.parametrize("order", ["F", "C"])
- def test_2d(self, order):
- dti = pd.date_range("2016-01-01", periods=6, tz="US/Pacific")
- arr = np.array(dti, dtype=object).reshape(3, 2)
- if order == "F":
- arr = arr.T
- res = _sequence_to_dt64ns(arr)
- expected = _sequence_to_dt64ns(arr.ravel())
- tm.assert_numpy_array_equal(res[0].ravel(), expected[0])
- assert res[1] == expected[1]
- assert res[2] == expected[2]
- res = DatetimeArray._from_sequence(arr)
- expected = DatetimeArray._from_sequence(arr.ravel()).reshape(arr.shape)
- tm.assert_datetime_array_equal(res, expected)
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