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REF: simplify maybe_cast_to_datetime #41624

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Merged
merged 3 commits into from
May 25, 2021
Merged

REF: simplify maybe_cast_to_datetime #41624

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41685a8
REF: simplify maybe_cast_to_datetime
jbrockmendel May 22, 2021
8e9adf7
ignore-> cast
jbrockmendel May 23, 2021
9a0b35d
Merge branch 'master' into ref-maybe_cast_to_datetime-3
jbrockmendel May 23, 2021
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4 changes: 3 additions & 1 deletion pandas/core/construction.py
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Original file line number Diff line number Diff line change
Expand Up @@ -726,7 +726,9 @@ def _try_cast(
except (ValueError, TypeError) as err:
if dtype is not None and raise_cast_failure:
raise
elif "Cannot cast" in str(err):
elif "Cannot cast" in str(err) or "cannot be converted to timedelta64" in str(
err
):
# via _disallow_mismatched_datetimelike
raise
else:
Expand Down
132 changes: 66 additions & 66 deletions pandas/core/dtypes/cast.py
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Original file line number Diff line number Diff line change
Expand Up @@ -68,7 +68,6 @@
is_numeric_dtype,
is_object_dtype,
is_scalar,
is_sparse,
is_string_dtype,
is_timedelta64_dtype,
is_unsigned_integer_dtype,
Expand Down Expand Up @@ -1583,83 +1582,84 @@ def maybe_cast_to_datetime(
We allow a list *only* when dtype is not None.
"""
from pandas.core.arrays.datetimes import sequence_to_datetimes
from pandas.core.arrays.timedeltas import sequence_to_td64ns
from pandas.core.arrays.timedeltas import TimedeltaArray

if not is_list_like(value):
raise TypeError("value must be listlike")

if is_timedelta64_dtype(dtype):
# TODO: _from_sequence would raise ValueError in cases where
# ensure_nanosecond_dtype raises TypeError
dtype = cast(np.dtype, dtype)
dtype = ensure_nanosecond_dtype(dtype)
res = TimedeltaArray._from_sequence(value, dtype=dtype)
return res

if dtype is not None:
is_datetime64 = is_datetime64_dtype(dtype)
is_datetime64tz = is_datetime64tz_dtype(dtype)
is_timedelta64 = is_timedelta64_dtype(dtype)

vdtype = getattr(value, "dtype", None)

if is_datetime64 or is_datetime64tz or is_timedelta64:
if is_datetime64 or is_datetime64tz:
dtype = ensure_nanosecond_dtype(dtype)

if not is_sparse(value):
value = np.array(value, copy=False)

# we have an array of datetime or timedeltas & nulls
if value.size or not is_dtype_equal(value.dtype, dtype):
_disallow_mismatched_datetimelike(value, dtype)

try:
if is_datetime64:
dta = sequence_to_datetimes(value, allow_object=False)
# GH 25843: Remove tz information since the dtype
# didn't specify one

if dta.tz is not None:
warnings.warn(
"Data is timezone-aware. Converting "
"timezone-aware data to timezone-naive by "
"passing dtype='datetime64[ns]' to "
"DataFrame or Series is deprecated and will "
"raise in a future version. Use "
"`pd.Series(values).dt.tz_localize(None)` "
"instead.",
FutureWarning,
stacklevel=8,
)
# equiv: dta.view(dtype)
# Note: NOT equivalent to dta.astype(dtype)
dta = dta.tz_localize(None)

value = dta
elif is_datetime64tz:
dtype = cast(DatetimeTZDtype, dtype)
# The string check can be removed once issue #13712
# is solved. String data that is passed with a
# datetime64tz is assumed to be naive which should
# be localized to the timezone.
is_dt_string = is_string_dtype(value.dtype)
dta = sequence_to_datetimes(value, allow_object=False)
if dta.tz is not None:
value = dta.astype(dtype, copy=False)
elif is_dt_string:
# Strings here are naive, so directly localize
# equiv: dta.astype(dtype) # though deprecated

value = dta.tz_localize(dtype.tz)
else:
# Numeric values are UTC at this point,
# so localize and convert
# equiv: Series(dta).astype(dtype) # though deprecated

value = dta.tz_localize("UTC").tz_convert(dtype.tz)
elif is_timedelta64:
# if successful, we get a ndarray[td64ns]
value, _ = sequence_to_td64ns(value)
except OutOfBoundsDatetime:
raise
except ValueError:
# TODO(GH#40048): only catch dateutil's ParserError
# once we can reliably import it in all supported versions
if is_timedelta64:
raise
pass
value = np.array(value, copy=False)

# we have an array of datetime or timedeltas & nulls
if value.size or not is_dtype_equal(value.dtype, dtype):
_disallow_mismatched_datetimelike(value, dtype)

try:
if is_datetime64:
dta = sequence_to_datetimes(value, allow_object=False)
# GH 25843: Remove tz information since the dtype
# didn't specify one

if dta.tz is not None:
warnings.warn(
"Data is timezone-aware. Converting "
"timezone-aware data to timezone-naive by "
"passing dtype='datetime64[ns]' to "
"DataFrame or Series is deprecated and will "
"raise in a future version. Use "
"`pd.Series(values).dt.tz_localize(None)` "
"instead.",
FutureWarning,
stacklevel=8,
)
# equiv: dta.view(dtype)
# Note: NOT equivalent to dta.astype(dtype)
dta = dta.tz_localize(None)

value = dta
elif is_datetime64tz:
dtype = cast(DatetimeTZDtype, dtype)
# The string check can be removed once issue #13712
# is solved. String data that is passed with a
# datetime64tz is assumed to be naive which should
# be localized to the timezone.
is_dt_string = is_string_dtype(value.dtype)
dta = sequence_to_datetimes(value, allow_object=False)
if dta.tz is not None:
value = dta.astype(dtype, copy=False)
elif is_dt_string:
# Strings here are naive, so directly localize
# equiv: dta.astype(dtype) # though deprecated

value = dta.tz_localize(dtype.tz)
else:
# Numeric values are UTC at this point,
# so localize and convert
# equiv: Series(dta).astype(dtype) # though deprecated

value = dta.tz_localize("UTC").tz_convert(dtype.tz)
except OutOfBoundsDatetime:
raise
except ValueError:
# TODO(GH#40048): only catch dateutil's ParserError
# once we can reliably import it in all supported versions
pass

elif getattr(vdtype, "kind", None) in ["m", "M"]:
# we are already datetimelike and want to coerce to non-datetimelike;
Expand Down
13 changes: 11 additions & 2 deletions pandas/tests/frame/test_constructors.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2763,11 +2763,20 @@ def test_from_scalar_datetimelike_mismatched(self, constructor, cls, request):
scalar = cls("NaT", "ns")
dtype = {np.datetime64: "m8[ns]", np.timedelta64: "M8[ns]"}[cls]

with pytest.raises(TypeError, match="Cannot cast"):
msg = "Cannot cast"
if cls is np.datetime64:
msg = "|".join(
[
r"dtype datetime64\[ns\] cannot be converted to timedelta64\[ns\]",
"Cannot cast",
]
)

with pytest.raises(TypeError, match=msg):
constructor(scalar, dtype=dtype)

scalar = cls(4, "ns")
with pytest.raises(TypeError, match="Cannot cast"):
with pytest.raises(TypeError, match=msg):
constructor(scalar, dtype=dtype)

@pytest.mark.parametrize("cls", [datetime, np.datetime64])
Expand Down