656 lines
19 KiB
Cython
656 lines
19 KiB
Cython
cimport cython
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import warnings
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import numpy as np
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from pandas.util._exceptions import find_stack_level
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cimport numpy as cnp
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from cpython.object cimport PyObject
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from numpy cimport (
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int32_t,
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int64_t,
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intp_t,
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ndarray,
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)
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cnp.import_array()
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import pytz
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# stdlib datetime imports
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from cpython.datetime cimport (
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PyDate_Check,
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PyDateTime_Check,
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datetime,
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import_datetime,
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time,
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tzinfo,
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)
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import_datetime()
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from pandas._libs.tslibs.base cimport ABCTimestamp
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from pandas._libs.tslibs.dtypes cimport (
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abbrev_to_npy_unit,
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periods_per_second,
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)
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from pandas._libs.tslibs.np_datetime cimport (
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NPY_DATETIMEUNIT,
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NPY_FR_ns,
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astype_overflowsafe,
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check_dts_bounds,
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dtstruct_to_dt64,
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get_datetime64_unit,
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get_datetime64_value,
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get_implementation_bounds,
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get_unit_from_dtype,
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npy_datetime,
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npy_datetimestruct,
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npy_datetimestruct_to_datetime,
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pandas_datetime_to_datetimestruct,
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pydatetime_to_dt64,
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pydatetime_to_dtstruct,
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string_to_dts,
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)
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from pandas._libs.tslibs.np_datetime import (
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OutOfBoundsDatetime,
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OutOfBoundsTimedelta,
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)
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from pandas._libs.tslibs.timezones cimport (
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get_utcoffset,
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is_utc,
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maybe_get_tz,
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tz_compare,
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utc_pytz as UTC,
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)
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from pandas._libs.tslibs.util cimport (
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is_datetime64_object,
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is_float_object,
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is_integer_object,
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)
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from pandas._libs.tslibs.parsing import parse_datetime_string
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from pandas._libs.tslibs.nattype cimport (
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NPY_NAT,
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c_NaT as NaT,
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c_nat_strings as nat_strings,
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checknull_with_nat,
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)
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from pandas._libs.tslibs.tzconversion cimport (
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Localizer,
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tz_localize_to_utc_single,
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)
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# ----------------------------------------------------------------------
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# Constants
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DT64NS_DTYPE = np.dtype('M8[ns]')
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TD64NS_DTYPE = np.dtype('m8[ns]')
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# ----------------------------------------------------------------------
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# Unit Conversion Helpers
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cdef inline int64_t cast_from_unit(object ts, str unit) except? -1:
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"""
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Return a casting of the unit represented to nanoseconds
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round the fractional part of a float to our precision, p.
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Parameters
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----------
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ts : int, float, or None
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unit : str
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Returns
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-------
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int64_t
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"""
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cdef:
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int64_t m
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int p
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m, p = precision_from_unit(unit)
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# just give me the unit back
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if ts is None:
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return m
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# cast the unit, multiply base/frace separately
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# to avoid precision issues from float -> int
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base = <int64_t>ts
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frac = ts - base
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if p:
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frac = round(frac, p)
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return <int64_t>(base * m) + <int64_t>(frac * m)
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cpdef inline (int64_t, int) precision_from_unit(str unit):
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"""
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Return a casting of the unit represented to nanoseconds + the precision
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to round the fractional part.
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Notes
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-----
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The caller is responsible for ensuring that the default value of "ns"
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takes the place of None.
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"""
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cdef:
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int64_t m
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int p
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NPY_DATETIMEUNIT reso = abbrev_to_npy_unit(unit)
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if reso == NPY_DATETIMEUNIT.NPY_FR_Y:
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# each 400 years we have 97 leap years, for an average of 97/400=.2425
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# extra days each year. We get 31556952 by writing
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# 3600*24*365.2425=31556952
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m = 1_000_000_000 * 31556952
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p = 9
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elif reso == NPY_DATETIMEUNIT.NPY_FR_M:
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# 2629746 comes from dividing the "Y" case by 12.
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m = 1_000_000_000 * 2629746
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p = 9
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elif reso == NPY_DATETIMEUNIT.NPY_FR_W:
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m = 1_000_000_000 * 3600 * 24 * 7
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p = 9
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elif reso == NPY_DATETIMEUNIT.NPY_FR_D:
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m = 1_000_000_000 * 3600 * 24
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p = 9
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elif reso == NPY_DATETIMEUNIT.NPY_FR_h:
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m = 1_000_000_000 * 3600
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p = 9
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elif reso == NPY_DATETIMEUNIT.NPY_FR_m:
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m = 1_000_000_000 * 60
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p = 9
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elif reso == NPY_DATETIMEUNIT.NPY_FR_s:
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m = 1_000_000_000
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p = 9
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elif reso == NPY_DATETIMEUNIT.NPY_FR_ms:
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m = 1_000_000
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p = 6
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elif reso == NPY_DATETIMEUNIT.NPY_FR_us:
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m = 1000
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p = 3
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elif reso == NPY_DATETIMEUNIT.NPY_FR_ns or reso == NPY_DATETIMEUNIT.NPY_FR_GENERIC:
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m = 1
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p = 0
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else:
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raise ValueError(f"cannot cast unit {unit}")
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return m, p
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cdef inline int64_t get_datetime64_nanos(object val) except? -1:
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"""
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Extract the value and unit from a np.datetime64 object, then convert the
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value to nanoseconds if necessary.
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"""
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cdef:
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npy_datetimestruct dts
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NPY_DATETIMEUNIT unit
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npy_datetime ival
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ival = get_datetime64_value(val)
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if ival == NPY_NAT:
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return NPY_NAT
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unit = get_datetime64_unit(val)
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if unit != NPY_FR_ns:
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pandas_datetime_to_datetimestruct(ival, unit, &dts)
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check_dts_bounds(&dts)
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ival = dtstruct_to_dt64(&dts)
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return ival
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# ----------------------------------------------------------------------
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# _TSObject Conversion
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# lightweight C object to hold datetime & int64 pair
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cdef class _TSObject:
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# cdef:
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# npy_datetimestruct dts # npy_datetimestruct
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# int64_t value # numpy dt64
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# tzinfo tzinfo
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# bint fold
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def __cinit__(self):
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# GH 25057. As per PEP 495, set fold to 0 by default
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self.fold = 0
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cdef _TSObject convert_to_tsobject(object ts, tzinfo tz, str unit,
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bint dayfirst, bint yearfirst, int32_t nanos=0):
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"""
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Extract datetime and int64 from any of:
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- np.int64 (with unit providing a possible modifier)
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- np.datetime64
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- a float (with unit providing a possible modifier)
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- python int or long object (with unit providing a possible modifier)
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- iso8601 string object
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- python datetime object
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- another timestamp object
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Raises
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------
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OutOfBoundsDatetime : ts cannot be converted within implementation bounds
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"""
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cdef:
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_TSObject obj
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obj = _TSObject()
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if isinstance(ts, str):
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return _convert_str_to_tsobject(ts, tz, unit, dayfirst, yearfirst)
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if ts is None or ts is NaT:
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obj.value = NPY_NAT
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elif is_datetime64_object(ts):
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obj.value = get_datetime64_nanos(ts)
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if obj.value != NPY_NAT:
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pandas_datetime_to_datetimestruct(obj.value, NPY_FR_ns, &obj.dts)
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elif is_integer_object(ts):
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try:
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ts = <int64_t>ts
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except OverflowError:
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# GH#26651 re-raise as OutOfBoundsDatetime
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raise OutOfBoundsDatetime(f"Out of bounds nanosecond timestamp {ts}")
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if ts == NPY_NAT:
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obj.value = NPY_NAT
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else:
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if unit in ["Y", "M"]:
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# GH#47266 cast_from_unit leads to weird results e.g. with "Y"
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# and 150 we'd get 2120-01-01 09:00:00
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ts = np.datetime64(ts, unit)
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return convert_to_tsobject(ts, tz, None, False, False)
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ts = ts * cast_from_unit(None, unit)
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obj.value = ts
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pandas_datetime_to_datetimestruct(ts, NPY_FR_ns, &obj.dts)
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elif is_float_object(ts):
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if ts != ts or ts == NPY_NAT:
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obj.value = NPY_NAT
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else:
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if unit in ["Y", "M"]:
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if ts == int(ts):
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# GH#47266 Avoid cast_from_unit, which would give weird results
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# e.g. with "Y" and 150.0 we'd get 2120-01-01 09:00:00
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return convert_to_tsobject(int(ts), tz, unit, False, False)
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else:
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# GH#47267 it is clear that 2 "M" corresponds to 1970-02-01,
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# but not clear what 2.5 "M" corresponds to, so we will
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# disallow that case.
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warnings.warn(
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"Conversion of non-round float with unit={unit} is ambiguous "
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"and will raise in a future version.",
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FutureWarning,
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stacklevel=find_stack_level(),
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)
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ts = cast_from_unit(ts, unit)
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obj.value = ts
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pandas_datetime_to_datetimestruct(ts, NPY_FR_ns, &obj.dts)
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elif PyDateTime_Check(ts):
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return convert_datetime_to_tsobject(ts, tz, nanos)
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elif PyDate_Check(ts):
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# Keep the converter same as PyDateTime's
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ts = datetime.combine(ts, time())
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return convert_datetime_to_tsobject(ts, tz)
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else:
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from .period import Period
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if isinstance(ts, Period):
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raise ValueError("Cannot convert Period to Timestamp "
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"unambiguously. Use to_timestamp")
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raise TypeError(f'Cannot convert input [{ts}] of type {type(ts)} to '
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f'Timestamp')
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maybe_localize_tso(obj, tz, NPY_FR_ns)
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return obj
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cdef maybe_localize_tso(_TSObject obj, tzinfo tz, NPY_DATETIMEUNIT reso):
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if tz is not None:
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_localize_tso(obj, tz, reso)
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if obj.value != NPY_NAT:
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# check_overflows needs to run after _localize_tso
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check_dts_bounds(&obj.dts, reso)
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check_overflows(obj, reso)
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cdef _TSObject convert_datetime_to_tsobject(
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datetime ts,
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tzinfo tz,
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int32_t nanos=0,
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NPY_DATETIMEUNIT reso=NPY_FR_ns,
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):
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"""
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Convert a datetime (or Timestamp) input `ts`, along with optional timezone
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object `tz` to a _TSObject.
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The optional argument `nanos` allows for cases where datetime input
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needs to be supplemented with higher-precision information.
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Parameters
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----------
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ts : datetime or Timestamp
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Value to be converted to _TSObject
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tz : tzinfo or None
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timezone for the timezone-aware output
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nanos : int32_t, default is 0
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nanoseconds supplement the precision of the datetime input ts
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reso : NPY_DATETIMEUNIT, default NPY_FR_ns
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Returns
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-------
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obj : _TSObject
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"""
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cdef:
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_TSObject obj = _TSObject()
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int64_t pps
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obj.fold = ts.fold
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if tz is not None:
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tz = maybe_get_tz(tz)
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if ts.tzinfo is not None:
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# Convert the current timezone to the passed timezone
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ts = ts.astimezone(tz)
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pydatetime_to_dtstruct(ts, &obj.dts)
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obj.tzinfo = ts.tzinfo
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elif not is_utc(tz):
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ts = _localize_pydatetime(ts, tz)
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pydatetime_to_dtstruct(ts, &obj.dts)
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obj.tzinfo = ts.tzinfo
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else:
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# UTC
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pydatetime_to_dtstruct(ts, &obj.dts)
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obj.tzinfo = tz
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else:
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pydatetime_to_dtstruct(ts, &obj.dts)
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obj.tzinfo = ts.tzinfo
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if isinstance(ts, ABCTimestamp):
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obj.dts.ps = ts.nanosecond * 1000
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if nanos:
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obj.dts.ps = nanos * 1000
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obj.value = npy_datetimestruct_to_datetime(reso, &obj.dts)
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if obj.tzinfo is not None and not is_utc(obj.tzinfo):
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offset = get_utcoffset(obj.tzinfo, ts)
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pps = periods_per_second(reso)
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obj.value -= int(offset.total_seconds() * pps)
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check_dts_bounds(&obj.dts, reso)
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check_overflows(obj, reso)
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return obj
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cdef _TSObject _create_tsobject_tz_using_offset(npy_datetimestruct dts,
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int tzoffset, tzinfo tz=None):
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"""
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Convert a datetimestruct `dts`, along with initial timezone offset
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`tzoffset` to a _TSObject (with timezone object `tz` - optional).
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Parameters
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----------
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dts: npy_datetimestruct
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tzoffset: int
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tz : tzinfo or None
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timezone for the timezone-aware output.
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Returns
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-------
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obj : _TSObject
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"""
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cdef:
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_TSObject obj = _TSObject()
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int64_t value # numpy dt64
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datetime dt
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Py_ssize_t pos
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value = dtstruct_to_dt64(&dts)
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obj.dts = dts
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obj.tzinfo = pytz.FixedOffset(tzoffset)
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obj.value = tz_localize_to_utc_single(value, obj.tzinfo)
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if tz is None:
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check_overflows(obj, NPY_FR_ns)
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return obj
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cdef:
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Localizer info = Localizer(tz, NPY_FR_ns)
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# Infer fold from offset-adjusted obj.value
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# see PEP 495 https://www.python.org/dev/peps/pep-0495/#the-fold-attribute
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if info.use_utc:
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pass
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elif info.use_tzlocal:
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info.utc_val_to_local_val(obj.value, &pos, &obj.fold)
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elif info.use_dst and not info.use_pytz:
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# i.e. dateutil
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info.utc_val_to_local_val(obj.value, &pos, &obj.fold)
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# Keep the converter same as PyDateTime's
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dt = datetime(obj.dts.year, obj.dts.month, obj.dts.day,
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obj.dts.hour, obj.dts.min, obj.dts.sec,
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obj.dts.us, obj.tzinfo, fold=obj.fold)
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obj = convert_datetime_to_tsobject(
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dt, tz, nanos=obj.dts.ps // 1000)
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return obj
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cdef _TSObject _convert_str_to_tsobject(object ts, tzinfo tz, str unit,
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bint dayfirst=False,
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bint yearfirst=False):
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"""
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Convert a string input `ts`, along with optional timezone object`tz`
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to a _TSObject.
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The optional arguments `dayfirst` and `yearfirst` are passed to the
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dateutil parser.
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Parameters
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----------
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ts : str
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Value to be converted to _TSObject
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tz : tzinfo or None
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timezone for the timezone-aware output
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unit : str or None
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dayfirst : bool, default False
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When parsing an ambiguous date string, interpret e.g. "3/4/1975" as
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April 3, as opposed to the standard US interpretation March 4.
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yearfirst : bool, default False
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When parsing an ambiguous date string, interpret e.g. "01/05/09"
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as "May 9, 2001", as opposed to the default "Jan 5, 2009"
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Returns
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-------
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obj : _TSObject
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"""
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cdef:
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npy_datetimestruct dts
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int out_local = 0, out_tzoffset = 0, string_to_dts_failed
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datetime dt
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int64_t ival
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NPY_DATETIMEUNIT out_bestunit
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if len(ts) == 0 or ts in nat_strings:
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ts = NaT
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obj = _TSObject()
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obj.value = NPY_NAT
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obj.tzinfo = tz
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return obj
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elif ts == 'now':
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# Issue 9000, we short-circuit rather than going
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# into np_datetime_strings which returns utc
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dt = datetime.now(tz)
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elif ts == 'today':
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# Issue 9000, we short-circuit rather than going
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# into np_datetime_strings which returns a normalized datetime
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dt = datetime.now(tz)
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# equiv: datetime.today().replace(tzinfo=tz)
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else:
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string_to_dts_failed = string_to_dts(
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ts, &dts, &out_bestunit, &out_local,
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&out_tzoffset, False
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)
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if not string_to_dts_failed:
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try:
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check_dts_bounds(&dts)
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if out_local == 1:
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return _create_tsobject_tz_using_offset(dts,
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out_tzoffset, tz)
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else:
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ival = dtstruct_to_dt64(&dts)
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if tz is not None:
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# shift for _localize_tso
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ival = tz_localize_to_utc_single(ival, tz,
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ambiguous="raise")
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return convert_to_tsobject(ival, tz, None, False, False)
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except OutOfBoundsDatetime:
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# GH#19382 for just-barely-OutOfBounds falling back to dateutil
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# parser will return incorrect result because it will ignore
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# nanoseconds
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raise
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except ValueError:
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# Fall through to parse_datetime_string
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pass
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try:
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|
dt = parse_datetime_string(ts, dayfirst=dayfirst,
|
|
yearfirst=yearfirst)
|
|
except (ValueError, OverflowError):
|
|
raise ValueError("could not convert string to Timestamp")
|
|
|
|
return convert_datetime_to_tsobject(dt, tz)
|
|
|
|
|
|
cdef inline 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 inline void _localize_tso(_TSObject obj, tzinfo tz, NPY_DATETIMEUNIT reso):
|
|
"""
|
|
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 inline 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)
|