111 lines
3.8 KiB
Python
111 lines
3.8 KiB
Python
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from datetime import (
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datetime,
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timezone,
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)
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import numpy as np
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import pytest
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from pandas._libs.tslibs.dtypes import NpyDatetimeUnit
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from pandas._libs.tslibs.strptime import array_strptime
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from pandas import (
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NaT,
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Timestamp,
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)
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import pandas._testing as tm
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creso_infer = NpyDatetimeUnit.NPY_FR_GENERIC.value
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class TestArrayStrptimeResolutionInference:
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def test_array_strptime_resolution_all_nat(self):
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arr = np.array([NaT, np.nan], dtype=object)
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fmt = "%Y-%m-%d %H:%M:%S"
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res, _ = array_strptime(arr, fmt=fmt, utc=False, creso=creso_infer)
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assert res.dtype == "M8[s]"
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res, _ = array_strptime(arr, fmt=fmt, utc=True, creso=creso_infer)
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assert res.dtype == "M8[s]"
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@pytest.mark.parametrize("tz", [None, timezone.utc])
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def test_array_strptime_resolution_inference_homogeneous_strings(self, tz):
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dt = datetime(2016, 1, 2, 3, 4, 5, 678900, tzinfo=tz)
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fmt = "%Y-%m-%d %H:%M:%S"
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dtstr = dt.strftime(fmt)
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arr = np.array([dtstr] * 3, dtype=object)
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expected = np.array([dt.replace(tzinfo=None)] * 3, dtype="M8[s]")
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res, _ = array_strptime(arr, fmt=fmt, utc=False, creso=creso_infer)
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tm.assert_numpy_array_equal(res, expected)
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fmt = "%Y-%m-%d %H:%M:%S.%f"
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dtstr = dt.strftime(fmt)
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arr = np.array([dtstr] * 3, dtype=object)
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expected = np.array([dt.replace(tzinfo=None)] * 3, dtype="M8[us]")
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res, _ = array_strptime(arr, fmt=fmt, utc=False, creso=creso_infer)
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tm.assert_numpy_array_equal(res, expected)
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fmt = "ISO8601"
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res, _ = array_strptime(arr, fmt=fmt, utc=False, creso=creso_infer)
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tm.assert_numpy_array_equal(res, expected)
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@pytest.mark.parametrize("tz", [None, timezone.utc])
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def test_array_strptime_resolution_mixed(self, tz):
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dt = datetime(2016, 1, 2, 3, 4, 5, 678900, tzinfo=tz)
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ts = Timestamp(dt).as_unit("ns")
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arr = np.array([dt, ts], dtype=object)
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expected = np.array(
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[Timestamp(dt).as_unit("ns").asm8, ts.asm8],
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dtype="M8[ns]",
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)
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fmt = "%Y-%m-%d %H:%M:%S"
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res, _ = array_strptime(arr, fmt=fmt, utc=False, creso=creso_infer)
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tm.assert_numpy_array_equal(res, expected)
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fmt = "ISO8601"
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res, _ = array_strptime(arr, fmt=fmt, utc=False, creso=creso_infer)
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tm.assert_numpy_array_equal(res, expected)
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def test_array_strptime_resolution_todaynow(self):
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# specifically case where today/now is the *first* item
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vals = np.array(["today", np.datetime64("2017-01-01", "us")], dtype=object)
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now = Timestamp("now").asm8
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res, _ = array_strptime(vals, fmt="%Y-%m-%d", utc=False, creso=creso_infer)
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res2, _ = array_strptime(
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vals[::-1], fmt="%Y-%m-%d", utc=False, creso=creso_infer
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)
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# 1s is an arbitrary cutoff for call overhead; in local testing the
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# actual difference is about 250us
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tolerance = np.timedelta64(1, "s")
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assert res.dtype == "M8[us]"
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assert abs(res[0] - now) < tolerance
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assert res[1] == vals[1]
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assert res2.dtype == "M8[us]"
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assert abs(res2[1] - now) < tolerance * 2
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assert res2[0] == vals[1]
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def test_array_strptime_str_outside_nano_range(self):
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vals = np.array(["2401-09-15"], dtype=object)
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expected = np.array(["2401-09-15"], dtype="M8[s]")
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fmt = "ISO8601"
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res, _ = array_strptime(vals, fmt=fmt, creso=creso_infer)
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tm.assert_numpy_array_equal(res, expected)
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# non-iso -> different path
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vals2 = np.array(["Sep 15, 2401"], dtype=object)
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expected2 = np.array(["2401-09-15"], dtype="M8[s]")
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fmt2 = "%b %d, %Y"
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res2, _ = array_strptime(vals2, fmt=fmt2, creso=creso_infer)
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tm.assert_numpy_array_equal(res2, expected2)
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