Alle Dateien aus dem Pythonkurs
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import numpy as np
cimport numpy as cnp
from libc.math cimport log10
from numpy cimport (
int32_t,
int64_t,
)
cnp.import_array()
# stdlib datetime imports
from datetime import timezone
from cpython.datetime cimport (
PyDate_Check,
PyDateTime_Check,
datetime,
import_datetime,
time,
timedelta,
tzinfo,
)
import_datetime()
from pandas._libs.missing cimport checknull_with_nat_and_na
from pandas._libs.tslibs.base cimport ABCTimestamp
from pandas._libs.tslibs.dtypes cimport (
abbrev_to_npy_unit,
get_supported_reso,
periods_per_second,
)
from pandas._libs.tslibs.np_datetime cimport (
NPY_DATETIMEUNIT,
NPY_FR_ns,
NPY_FR_us,
check_dts_bounds,
convert_reso,
get_conversion_factor,
get_datetime64_unit,
get_datetime64_value,
get_implementation_bounds,
import_pandas_datetime,
npy_datetime,
npy_datetimestruct,
npy_datetimestruct_to_datetime,
pandas_datetime_to_datetimestruct,
pydatetime_to_dt64,
pydatetime_to_dtstruct,
string_to_dts,
)
import_pandas_datetime()
from pandas._libs.tslibs.np_datetime import OutOfBoundsDatetime
from pandas._libs.tslibs.nattype cimport (
NPY_NAT,
c_nat_strings as nat_strings,
)
from pandas._libs.tslibs.parsing cimport parse_datetime_string
from pandas._libs.tslibs.timezones cimport (
get_utcoffset,
is_utc,
)
from pandas._libs.tslibs.tzconversion cimport (
Localizer,
tz_localize_to_utc_single,
)
from pandas._libs.tslibs.util cimport (
is_datetime64_object,
is_float_object,
is_integer_object,
)
# ----------------------------------------------------------------------
# Constants
DT64NS_DTYPE = np.dtype("M8[ns]")
TD64NS_DTYPE = np.dtype("m8[ns]")
# ----------------------------------------------------------------------
# Unit Conversion Helpers
cdef int64_t cast_from_unit(
object ts,
str unit,
NPY_DATETIMEUNIT out_reso=NPY_FR_ns
) except? -1:
"""
Return a casting of the unit represented to nanoseconds
round the fractional part of a float to our precision, p.
Parameters
----------
ts : int, float, or None
unit : str
Returns
-------
int64_t
"""
cdef:
int64_t m
int p
if unit in ["Y", "M"]:
if is_float_object(ts) and not ts.is_integer():
# GH#47267 it is clear that 2 "M" corresponds to 1970-02-01,
# but not clear what 2.5 "M" corresponds to, so we will
# disallow that case.
raise ValueError(
f"Conversion of non-round float with unit={unit} "
"is ambiguous"
)
# GH#47266 go through np.datetime64 to avoid weird results e.g. with "Y"
# and 150 we'd get 2120-01-01 09:00:00
if is_float_object(ts):
ts = int(ts)
dt64obj = np.datetime64(ts, unit)
return get_datetime64_nanos(dt64obj, out_reso)
m, p = precision_from_unit(unit, out_reso)
# cast the unit, multiply base/frac separately
# to avoid precision issues from float -> int
try:
base = <int64_t>ts
except OverflowError as err:
raise OutOfBoundsDatetime(
f"cannot convert input {ts} with the unit '{unit}'"
) from err
frac = ts - base
if p:
frac = round(frac, p)
try:
return <int64_t>(base * m) + <int64_t>(frac * m)
except OverflowError as err:
raise OutOfBoundsDatetime(
f"cannot convert input {ts} with the unit '{unit}'"
) from err
cpdef inline (int64_t, int) precision_from_unit(
str unit,
NPY_DATETIMEUNIT out_reso=NPY_DATETIMEUNIT.NPY_FR_ns,
):
"""
Return a casting of the unit represented to nanoseconds + the precision
to round the fractional part.
Notes
-----
The caller is responsible for ensuring that the default value of "ns"
takes the place of None.
"""
cdef:
int64_t m
int64_t multiplier
int p
NPY_DATETIMEUNIT reso = abbrev_to_npy_unit(unit)
if reso == NPY_DATETIMEUNIT.NPY_FR_GENERIC:
reso = NPY_DATETIMEUNIT.NPY_FR_ns
if reso == NPY_DATETIMEUNIT.NPY_FR_Y:
# each 400 years we have 97 leap years, for an average of 97/400=.2425
# extra days each year. We get 31556952 by writing
# 3600*24*365.2425=31556952
multiplier = periods_per_second(out_reso)
m = multiplier * 31556952
elif reso == NPY_DATETIMEUNIT.NPY_FR_M:
# 2629746 comes from dividing the "Y" case by 12.
multiplier = periods_per_second(out_reso)
m = multiplier * 2629746
else:
# Careful: if get_conversion_factor raises, the exception does
# not propagate, instead we get a warning about an ignored exception.
# https://github.com/pandas-dev/pandas/pull/51483#discussion_r1115198951
m = get_conversion_factor(reso, out_reso)
p = <int>log10(m) # number of digits in 'm' minus 1
return m, p
cdef int64_t get_datetime64_nanos(object val, NPY_DATETIMEUNIT reso) except? -1:
"""
Extract the value and unit from a np.datetime64 object, then convert the
value to nanoseconds if necessary.
"""
cdef:
npy_datetimestruct dts
NPY_DATETIMEUNIT unit
npy_datetime ival
ival = get_datetime64_value(val)
if ival == NPY_NAT:
return NPY_NAT
unit = get_datetime64_unit(val)
if unit != reso:
pandas_datetime_to_datetimestruct(ival, unit, &dts)
check_dts_bounds(&dts, reso)
ival = npy_datetimestruct_to_datetime(reso, &dts)
return ival
# ----------------------------------------------------------------------
# _TSObject Conversion
# lightweight C object to hold datetime & int64 pair
cdef class _TSObject:
# cdef:
# npy_datetimestruct dts # npy_datetimestruct
# int64_t value # numpy dt64
# tzinfo tzinfo
# bint fold
# NPY_DATETIMEUNIT creso
def __cinit__(self):
# GH 25057. As per PEP 495, set fold to 0 by default
self.fold = 0
self.creso = NPY_FR_ns # default value
cdef int64_t ensure_reso(self, NPY_DATETIMEUNIT creso, str val=None) except? -1:
if self.creso != creso:
try:
self.value = convert_reso(self.value, self.creso, creso, False)
except OverflowError as err:
if val is not None:
raise OutOfBoundsDatetime(
f"Out of bounds nanosecond timestamp: {val}"
) from err
raise OutOfBoundsDatetime from err
self.creso = creso
return self.value
cdef _TSObject convert_to_tsobject(object ts, tzinfo tz, str unit,
bint dayfirst, bint yearfirst, int32_t nanos=0):
"""
Extract datetime and int64 from any of:
- np.int64 (with unit providing a possible modifier)
- np.datetime64
- a float (with unit providing a possible modifier)
- python int or long object (with unit providing a possible modifier)
- iso8601 string object
- python datetime object
- another timestamp object
Raises
------
OutOfBoundsDatetime : ts cannot be converted within implementation bounds
"""
cdef:
_TSObject obj
NPY_DATETIMEUNIT reso
obj = _TSObject()
if isinstance(ts, str):
return convert_str_to_tsobject(ts, tz, unit, dayfirst, yearfirst)
if checknull_with_nat_and_na(ts):
obj.value = NPY_NAT
elif is_datetime64_object(ts):
reso = get_supported_reso(get_datetime64_unit(ts))
obj.creso = reso
obj.value = get_datetime64_nanos(ts, reso)
if obj.value != NPY_NAT:
pandas_datetime_to_datetimestruct(obj.value, reso, &obj.dts)
elif is_integer_object(ts):
try:
ts = <int64_t>ts
except OverflowError:
# GH#26651 re-raise as OutOfBoundsDatetime
raise OutOfBoundsDatetime(f"Out of bounds nanosecond timestamp {ts}")
if ts == NPY_NAT:
obj.value = NPY_NAT
else:
if unit is None:
unit = "ns"
in_reso = abbrev_to_npy_unit(unit)
reso = get_supported_reso(in_reso)
ts = cast_from_unit(ts, unit, reso)
obj.value = ts
obj.creso = reso
pandas_datetime_to_datetimestruct(ts, reso, &obj.dts)
elif is_float_object(ts):
if ts != ts or ts == NPY_NAT:
obj.value = NPY_NAT
else:
ts = cast_from_unit(ts, unit)
obj.value = ts
pandas_datetime_to_datetimestruct(ts, NPY_FR_ns, &obj.dts)
elif PyDateTime_Check(ts):
if nanos == 0:
if isinstance(ts, ABCTimestamp):
reso = abbrev_to_npy_unit(ts.unit) # TODO: faster way to do this?
else:
# TODO: what if user explicitly passes nanos=0?
reso = NPY_FR_us
else:
reso = NPY_FR_ns
return convert_datetime_to_tsobject(ts, tz, nanos, reso=reso)
elif PyDate_Check(ts):
# Keep the converter same as PyDateTime's
# For date object we give the lowest supported resolution, i.e. "s"
ts = datetime.combine(ts, time())
return convert_datetime_to_tsobject(
ts, tz, nanos=0, reso=NPY_DATETIMEUNIT.NPY_FR_s
)
else:
from .period import Period
if isinstance(ts, Period):
raise ValueError("Cannot convert Period to Timestamp "
"unambiguously. Use to_timestamp")
raise TypeError(f"Cannot convert input [{ts}] of type {type(ts)} to "
f"Timestamp")
maybe_localize_tso(obj, tz, obj.creso)
return obj
cdef maybe_localize_tso(_TSObject obj, tzinfo tz, NPY_DATETIMEUNIT reso):
if tz is not None:
_localize_tso(obj, tz, reso)
if obj.value != NPY_NAT:
# check_overflows needs to run after _localize_tso
check_dts_bounds(&obj.dts, reso)
check_overflows(obj, reso)
cdef _TSObject convert_datetime_to_tsobject(
datetime ts,
tzinfo tz,
int32_t nanos=0,
NPY_DATETIMEUNIT reso=NPY_FR_ns,
):
"""
Convert a datetime (or Timestamp) input `ts`, along with optional timezone
object `tz` to a _TSObject.
The optional argument `nanos` allows for cases where datetime input
needs to be supplemented with higher-precision information.
Parameters
----------
ts : datetime or Timestamp
Value to be converted to _TSObject
tz : tzinfo or None
timezone for the timezone-aware output
nanos : int32_t, default is 0
nanoseconds supplement the precision of the datetime input ts
reso : NPY_DATETIMEUNIT, default NPY_FR_ns
Returns
-------
obj : _TSObject
"""
cdef:
_TSObject obj = _TSObject()
int64_t pps
obj.creso = reso
obj.fold = ts.fold
if tz is not None:
if ts.tzinfo is not None:
# Convert the current timezone to the passed timezone
ts = ts.astimezone(tz)
pydatetime_to_dtstruct(ts, &obj.dts)
obj.tzinfo = ts.tzinfo
elif not is_utc(tz):
ts = _localize_pydatetime(ts, tz)
pydatetime_to_dtstruct(ts, &obj.dts)
obj.tzinfo = ts.tzinfo
else:
# UTC
pydatetime_to_dtstruct(ts, &obj.dts)
obj.tzinfo = tz
else:
pydatetime_to_dtstruct(ts, &obj.dts)
obj.tzinfo = ts.tzinfo
if isinstance(ts, ABCTimestamp):
obj.dts.ps = ts.nanosecond * 1000
if nanos:
obj.dts.ps = nanos * 1000
obj.value = npy_datetimestruct_to_datetime(reso, &obj.dts)
if obj.tzinfo is not None and not is_utc(obj.tzinfo):
offset = get_utcoffset(obj.tzinfo, ts)
pps = periods_per_second(reso)
obj.value -= int(offset.total_seconds() * pps)
check_dts_bounds(&obj.dts, reso)
check_overflows(obj, reso)
return obj
cdef _TSObject _create_tsobject_tz_using_offset(npy_datetimestruct dts,
int tzoffset, tzinfo tz=None,
NPY_DATETIMEUNIT reso=NPY_FR_ns):
"""
Convert a datetimestruct `dts`, along with initial timezone offset
`tzoffset` to a _TSObject (with timezone object `tz` - optional).
Parameters
----------
dts : npy_datetimestruct
tzoffset : int
tz : tzinfo or None
timezone for the timezone-aware output.
reso : NPY_DATETIMEUNIT, default NPY_FR_ns
Returns
-------
obj : _TSObject
"""
cdef:
_TSObject obj = _TSObject()
int64_t value # numpy dt64
datetime dt
Py_ssize_t pos
value = npy_datetimestruct_to_datetime(reso, &dts)
obj.dts = dts
obj.tzinfo = timezone(timedelta(minutes=tzoffset))
obj.value = tz_localize_to_utc_single(
value, obj.tzinfo, ambiguous=None, nonexistent=None, creso=reso
)
obj.creso = reso
if tz is None:
check_overflows(obj, reso)
return obj
cdef:
Localizer info = Localizer(tz, reso)
# Infer fold from offset-adjusted obj.value
# see PEP 495 https://www.python.org/dev/peps/pep-0495/#the-fold-attribute
if info.use_utc:
pass
elif info.use_tzlocal:
info.utc_val_to_local_val(obj.value, &pos, &obj.fold)
elif info.use_dst and not info.use_pytz:
# i.e. dateutil
info.utc_val_to_local_val(obj.value, &pos, &obj.fold)
# Keep the converter same as PyDateTime's
dt = datetime(obj.dts.year, obj.dts.month, obj.dts.day,
obj.dts.hour, obj.dts.min, obj.dts.sec,
obj.dts.us, obj.tzinfo, fold=obj.fold)
obj = convert_datetime_to_tsobject(
dt, tz, nanos=obj.dts.ps // 1000)
obj.ensure_reso(reso) # TODO: more performant to get reso right up front?
return obj
cdef _TSObject convert_str_to_tsobject(str ts, tzinfo tz, str unit,
bint dayfirst=False,
bint yearfirst=False):
"""
Convert a string input `ts`, along with optional timezone object`tz`
to a _TSObject.
The optional arguments `dayfirst` and `yearfirst` are passed to the
dateutil parser.
Parameters
----------
ts : str
Value to be converted to _TSObject
tz : tzinfo or None
timezone for the timezone-aware output
unit : str or None
dayfirst : bool, default False
When parsing an ambiguous date string, interpret e.g. "3/4/1975" as
April 3, as opposed to the standard US interpretation March 4.
yearfirst : bool, default False
When parsing an ambiguous date string, interpret e.g. "01/05/09"
as "May 9, 2001", as opposed to the default "Jan 5, 2009"
Returns
-------
obj : _TSObject
"""
cdef:
npy_datetimestruct dts
int out_local = 0, out_tzoffset = 0, string_to_dts_failed
datetime dt
int64_t ival
NPY_DATETIMEUNIT out_bestunit, reso
if len(ts) == 0 or ts in nat_strings:
obj = _TSObject()
obj.value = NPY_NAT
obj.tzinfo = tz
return obj
elif ts == "now":
# Issue 9000, we short-circuit rather than going
# into np_datetime_strings which returns utc
dt = datetime.now(tz)
elif ts == "today":
# Issue 9000, we short-circuit rather than going
# into np_datetime_strings which returns a normalized datetime
dt = datetime.now(tz)
# equiv: datetime.today().replace(tzinfo=tz)
else:
string_to_dts_failed = string_to_dts(
ts, &dts, &out_bestunit, &out_local,
&out_tzoffset, False
)
if not string_to_dts_failed:
reso = get_supported_reso(out_bestunit)
check_dts_bounds(&dts, reso)
if out_local == 1:
return _create_tsobject_tz_using_offset(
dts, out_tzoffset, tz, reso
)
else:
ival = npy_datetimestruct_to_datetime(reso, &dts)
if tz is not None:
# shift for _localize_tso
ival = tz_localize_to_utc_single(
ival, tz, ambiguous="raise", nonexistent=None, creso=reso
)
obj = _TSObject()
obj.dts = dts
obj.value = ival
obj.creso = reso
maybe_localize_tso(obj, tz, obj.creso)
return obj
dt = parse_datetime_string(
ts, dayfirst=dayfirst, yearfirst=yearfirst, out_bestunit=&out_bestunit
)
reso = get_supported_reso(out_bestunit)
return convert_datetime_to_tsobject(dt, tz, nanos=0, reso=reso)
return convert_datetime_to_tsobject(dt, tz)
cdef check_overflows(_TSObject obj, NPY_DATETIMEUNIT reso=NPY_FR_ns):
"""
Check that we haven't silently overflowed in timezone conversion
Parameters
----------
obj : _TSObject
reso : NPY_DATETIMEUNIT, default NPY_FR_ns
Returns
-------
None
Raises
------
OutOfBoundsDatetime
"""
# GH#12677
cdef:
npy_datetimestruct lb, ub
get_implementation_bounds(reso, &lb, &ub)
if obj.dts.year == lb.year:
if not (obj.value < 0):
from pandas._libs.tslibs.timestamps import Timestamp
fmt = (f"{obj.dts.year}-{obj.dts.month:02d}-{obj.dts.day:02d} "
f"{obj.dts.hour:02d}:{obj.dts.min:02d}:{obj.dts.sec:02d}")
raise OutOfBoundsDatetime(
f"Converting {fmt} underflows past {Timestamp.min}"
)
elif obj.dts.year == ub.year:
if not (obj.value > 0):
from pandas._libs.tslibs.timestamps import Timestamp
fmt = (f"{obj.dts.year}-{obj.dts.month:02d}-{obj.dts.day:02d} "
f"{obj.dts.hour:02d}:{obj.dts.min:02d}:{obj.dts.sec:02d}")
raise OutOfBoundsDatetime(
f"Converting {fmt} overflows past {Timestamp.max}"
)
# ----------------------------------------------------------------------
# Localization
cdef void _localize_tso(_TSObject obj, tzinfo tz, NPY_DATETIMEUNIT reso) noexcept:
"""
Given the UTC nanosecond timestamp in obj.value, find the wall-clock
representation of that timestamp in the given timezone.
Parameters
----------
obj : _TSObject
tz : tzinfo
reso : NPY_DATETIMEUNIT
Returns
-------
None
Notes
-----
Sets obj.tzinfo inplace, alters obj.dts inplace.
"""
cdef:
int64_t local_val
Py_ssize_t outpos = -1
Localizer info = Localizer(tz, reso)
assert obj.tzinfo is None
if info.use_utc:
pass
elif obj.value == NPY_NAT:
pass
else:
local_val = info.utc_val_to_local_val(obj.value, &outpos, &obj.fold)
if info.use_pytz:
# infer we went through a pytz path, will have outpos!=-1
tz = tz._tzinfos[tz._transition_info[outpos]]
pandas_datetime_to_datetimestruct(local_val, reso, &obj.dts)
obj.tzinfo = tz
cdef datetime _localize_pydatetime(datetime dt, tzinfo tz):
"""
Take a datetime/Timestamp in UTC and localizes to timezone tz.
NB: Unlike the public version, this treats datetime and Timestamp objects
identically, i.e. discards nanos from Timestamps.
It also assumes that the `tz` input is not None.
"""
try:
# datetime.replace with pytz may be incorrect result
return tz.localize(dt)
except AttributeError:
return dt.replace(tzinfo=tz)
cpdef inline datetime localize_pydatetime(datetime dt, tzinfo tz):
"""
Take a datetime/Timestamp in UTC and localizes to timezone tz.
Parameters
----------
dt : datetime or Timestamp
tz : tzinfo or None
Returns
-------
localized : datetime or Timestamp
"""
if tz is None:
return dt
elif isinstance(dt, ABCTimestamp):
return dt.tz_localize(tz)
return _localize_pydatetime(dt, tz)
cdef tzinfo convert_timezone(
tzinfo tz_in,
tzinfo tz_out,
bint found_naive,
bint found_tz,
bint utc_convert,
):
"""
Validate that ``tz_in`` can be converted/localized to ``tz_out``.
Parameters
----------
tz_in : tzinfo or None
Timezone info of element being processed.
tz_out : tzinfo or None
Timezone info of output.
found_naive : bool
Whether a timezone-naive element has been found so far.
found_tz : bool
Whether a timezone-aware element has been found so far.
utc_convert : bool
Whether to convert/localize to UTC.
Returns
-------
tz_info
Timezone info of output.
Raises
------
ValueError
If ``tz_in`` can't be converted/localized to ``tz_out``.
"""
if tz_in is not None:
if utc_convert:
pass
elif found_naive:
raise ValueError("Tz-aware datetime.datetime "
"cannot be converted to "
"datetime64 unless utc=True")
elif tz_out is not None and not tz_compare(tz_out, tz_in):
raise ValueError("Tz-aware datetime.datetime "
"cannot be converted to "
"datetime64 unless utc=True")
else:
tz_out = tz_in
else:
if found_tz and not utc_convert:
raise ValueError("Cannot mix tz-aware with "
"tz-naive values")
return tz_out
cdef int64_t parse_pydatetime(
datetime val,
npy_datetimestruct *dts,
bint utc_convert,
) except? -1:
"""
Convert pydatetime to datetime64.
Parameters
----------
val : datetime
Element being processed.
dts : *npy_datetimestruct
Needed to use in pydatetime_to_dt64, which writes to it.
utc_convert : bool
Whether to convert/localize to UTC.
Raises
------
OutOfBoundsDatetime
"""
cdef:
_TSObject _ts
int64_t result
if val.tzinfo is not None:
if utc_convert:
_ts = convert_datetime_to_tsobject(val, None)
_ts.ensure_reso(NPY_FR_ns)
result = _ts.value
else:
_ts = convert_datetime_to_tsobject(val, None)
_ts.ensure_reso(NPY_FR_ns)
result = _ts.value
else:
if isinstance(val, ABCTimestamp):
result = val.as_unit("ns")._value
else:
result = pydatetime_to_dt64(val, dts)
check_dts_bounds(dts)
return result