def _simple_new(cls, values, name=None, freq=None, tz=None, dtype=None):
"""
We require the we have a dtype compat for the values
if we are passed a non-dtype compat, then coerce using the constructor
"""
if isinstance(values, DatetimeArray):
if tz:
tz = validate_tz_from_dtype(dtype, tz)
dtype = DatetimeTZDtype(tz=tz)
elif dtype is None:
dtype = _NS_DTYPE
values = DatetimeArray(values, freq=freq, dtype=dtype)
tz = values.tz
freq = values.freq
values = values._data
# DatetimeArray._simple_new will accept either i8 or M8[ns] dtypes
if isinstance(values, DatetimeIndex):
values = values._data
dtype = tz_to_dtype(tz)
dtarr = DatetimeArray._simple_new(values, freq=freq, dtype=dtype)
assert isinstance(dtarr, DatetimeArray)
result = object.__new__(cls)
result._data = dtarr
result.name = name
result._no_setting_name = False
# For groupby perf. See note in indexes/base about _index_data
result._index_data = dtarr._data
result._reset_identity()
return result
def _new_DatetimeIndex(cls, d):
"""
This is called upon unpickling, rather than the default which doesn't
have arguments and breaks __new__
"""
if "data" in d and not isinstance(d["data"], DatetimeIndex):
# Avoid need to verify integrity by calling simple_new directly
data = d.pop("data")
if not isinstance(data, DatetimeArray):
# For backward compat with older pickles, we may need to construct
# a DatetimeArray to adapt to the newer _simple_new signature
tz = d.pop("tz")
freq = d.pop("freq")
dta = DatetimeArray._simple_new(data, dtype=tz_to_dtype(tz), freq=freq)
else:
dta = data
for key in ["tz", "freq"]:
# These are already stored in our DatetimeArray; if they are
# also in the pickle and don't match, we have a problem.
if key in d:
assert d.pop(key) == getattr(dta, key)
result = cls._simple_new(dta, **d)
else:
with warnings.catch_warnings():
# TODO: If we knew what was going in to **d, we might be able to
# go through _simple_new instead
warnings.simplefilter("ignore")
result = cls.__new__(cls, **d)
return result
def __setstate__(self, state):
"""
Necessary for making this object picklable.
"""
if isinstance(state, dict):
super().__setstate__(state)
elif isinstance(state, tuple):
# < 0.15 compat
if len(state) == 2:
nd_state, own_state = state
data = np.empty(nd_state[1], dtype=nd_state[2])
np.ndarray.__setstate__(data, nd_state)
freq = own_state[1]
tz = timezones.tz_standardize(own_state[2])
dtype = tz_to_dtype(tz)
dtarr = DatetimeArray._simple_new(data, freq=freq, dtype=dtype)
self.name = own_state[0]
else: # pragma: no cover
data = np.empty(state)
np.ndarray.__setstate__(data, state)
dtarr = DatetimeArray(data)
self._data = dtarr
self._reset_identity()
else:
raise Exception("invalid pickle state")
