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