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pythonkurs/teil20b/lib/python3.11/site-packages/pandas/_libs/tslibs/timedeltas.pyx

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virtuelle Umgebung teil20b
1 year ago
import collections
import warnings
cimport cython
from cpython.object cimport (
Py_EQ,
Py_GE,
Py_GT,
Py_LE,
Py_LT,
Py_NE,
PyObject,
PyObject_RichCompare,
)
import numpy as np
cimport numpy as cnp
from numpy cimport (
int64_t,
ndarray,
)
cnp.import_array()
from cpython.datetime cimport (
PyDateTime_Check,
PyDelta_Check,
import_datetime,
timedelta,
)
import_datetime()
cimport pandas._libs.tslibs.util as util
from pandas._libs.missing cimport checknull_with_nat_and_na
from pandas._libs.tslibs.base cimport ABCTimestamp
from pandas._libs.tslibs.conversion cimport (
cast_from_unit,
precision_from_unit,
)
from pandas._libs.tslibs.dtypes cimport (
get_supported_reso,
is_supported_unit,
npy_unit_to_abbrev,
)
from pandas._libs.tslibs.nattype cimport (
NPY_NAT,
c_NaT as NaT,
c_nat_strings as nat_strings,
checknull_with_nat,
)
from pandas._libs.tslibs.np_datetime cimport (
NPY_DATETIMEUNIT,
NPY_FR_ns,
cmp_dtstructs,
cmp_scalar,
convert_reso,
get_datetime64_unit,
get_timedelta64_value,
get_unit_from_dtype,
import_pandas_datetime,
npy_datetimestruct,
pandas_datetime_to_datetimestruct,
pandas_timedelta_to_timedeltastruct,
pandas_timedeltastruct,
)
import_pandas_datetime()
from pandas._libs.tslibs.np_datetime import (
OutOfBoundsDatetime,
OutOfBoundsTimedelta,
)
from pandas._libs.tslibs.offsets cimport is_tick_object
from pandas._libs.tslibs.util cimport (
is_array,
is_datetime64_object,
is_float_object,
is_integer_object,
is_timedelta64_object,
)
from pandas._libs.tslibs.fields import (
RoundTo,
round_nsint64,
)
# ----------------------------------------------------------------------
# Constants
# components named tuple
Components = collections.namedtuple(
"Components",
[
"days",
"hours",
"minutes",
"seconds",
"milliseconds",
"microseconds",
"nanoseconds",
],
)
# This should be kept consistent with UnitChoices in pandas/_libs/tslibs/timedeltas.pyi
cdef dict timedelta_abbrevs = {
"Y": "Y",
"y": "Y",
"M": "M",
"W": "W",
"w": "W",
"D": "D",
"d": "D",
"days": "D",
"day": "D",
"hours": "h",
"hour": "h",
"hr": "h",
"h": "h",
"m": "m",
"minute": "m",
"min": "m",
"minutes": "m",
"t": "m",
"s": "s",
"seconds": "s",
"sec": "s",
"second": "s",
"ms": "ms",
"milliseconds": "ms",
"millisecond": "ms",
"milli": "ms",
"millis": "ms",
"l": "ms",
"us": "us",
"microseconds": "us",
"microsecond": "us",
"µs": "us",
"micro": "us",
"micros": "us",
"u": "us",
"ns": "ns",
"nanoseconds": "ns",
"nano": "ns",
"nanos": "ns",
"nanosecond": "ns",
"n": "ns",
}
_no_input = object()
# ----------------------------------------------------------------------
# API
@cython.boundscheck(False)
@cython.wraparound(False)
def ints_to_pytimedelta(ndarray m8values, box=False):
"""
convert an i8 repr to an ndarray of timedelta or Timedelta (if box ==
True)
Parameters
----------
arr : ndarray[timedelta64]
box : bool, default False
Returns
-------
result : ndarray[object]
array of Timedelta or timedeltas objects
"""
cdef:
NPY_DATETIMEUNIT reso = get_unit_from_dtype(m8values.dtype)
Py_ssize_t i, n = m8values.size
int64_t value
object res_val
# Note that `result` (and thus `result_flat`) is C-order and
# `it` iterates C-order as well, so the iteration matches
# See discussion at
# github.com/pandas-dev/pandas/pull/46886#discussion_r860261305
ndarray result = cnp.PyArray_EMPTY(
m8values.ndim, m8values.shape, cnp.NPY_OBJECT, 0
)
object[::1] res_flat = result.ravel() # should NOT be a copy
ndarray arr = m8values.view("i8")
cnp.flatiter it = cnp.PyArray_IterNew(arr)
for i in range(n):
# Analogous to: value = arr[i]
value = (<int64_t*>cnp.PyArray_ITER_DATA(it))[0]
if value == NPY_NAT:
res_val = <object>NaT
else:
if box:
res_val = _timedelta_from_value_and_reso(Timedelta, value, reso=reso)
elif reso == NPY_DATETIMEUNIT.NPY_FR_ns:
res_val = timedelta(microseconds=int(value) / 1000)
elif reso == NPY_DATETIMEUNIT.NPY_FR_us:
res_val = timedelta(microseconds=value)
elif reso == NPY_DATETIMEUNIT.NPY_FR_ms:
res_val = timedelta(milliseconds=value)
elif reso == NPY_DATETIMEUNIT.NPY_FR_s:
res_val = timedelta(seconds=value)
elif reso == NPY_DATETIMEUNIT.NPY_FR_m:
res_val = timedelta(minutes=value)
elif reso == NPY_DATETIMEUNIT.NPY_FR_h:
res_val = timedelta(hours=value)
elif reso == NPY_DATETIMEUNIT.NPY_FR_D:
res_val = timedelta(days=value)
elif reso == NPY_DATETIMEUNIT.NPY_FR_W:
res_val = timedelta(weeks=value)
else:
# Month, Year, NPY_FR_GENERIC, pico, femto, atto
raise NotImplementedError(reso)
# Note: we can index result directly instead of using PyArray_MultiIter_DATA
# like we do for the other functions because result is known C-contiguous
# and is the first argument to PyArray_MultiIterNew2. The usual pattern
# does not seem to work with object dtype.
# See discussion at
# github.com/pandas-dev/pandas/pull/46886#discussion_r860261305
res_flat[i] = res_val
cnp.PyArray_ITER_NEXT(it)
return result
# ----------------------------------------------------------------------
cpdef int64_t delta_to_nanoseconds(
delta,
NPY_DATETIMEUNIT reso=NPY_FR_ns,
bint round_ok=True,
) except? -1:
# Note: this will raise on timedelta64 with Y or M unit
cdef:
NPY_DATETIMEUNIT in_reso
int64_t n
if is_tick_object(delta):
n = delta.n
in_reso = delta._creso
elif isinstance(delta, _Timedelta):
n = delta._value
in_reso = delta._creso
elif is_timedelta64_object(delta):
in_reso = get_datetime64_unit(delta)
if in_reso == NPY_DATETIMEUNIT.NPY_FR_Y or in_reso == NPY_DATETIMEUNIT.NPY_FR_M:
raise ValueError(
"delta_to_nanoseconds does not support Y or M units, "
"as their duration in nanoseconds is ambiguous."
)
n = get_timedelta64_value(delta)
elif PyDelta_Check(delta):
in_reso = NPY_DATETIMEUNIT.NPY_FR_us
try:
n = (
delta.days * 24 * 3600 * 1_000_000
+ delta.seconds * 1_000_000
+ delta.microseconds
)
except OverflowError as err:
raise OutOfBoundsTimedelta(*err.args) from err
else:
raise TypeError(type(delta))
try:
return convert_reso(n, in_reso, reso, round_ok=round_ok)
except (OutOfBoundsDatetime, OverflowError) as err:
# Catch OutOfBoundsDatetime bc convert_reso can call check_dts_bounds
# for Y/M-resolution cases
unit_str = npy_unit_to_abbrev(reso)
raise OutOfBoundsTimedelta(
f"Cannot cast {str(delta)} to unit={unit_str} without overflow."
) from err
@cython.overflowcheck(True)
cdef object ensure_td64ns(object ts):
"""
Overflow-safe implementation of td64.astype("m8[ns]")
Parameters
----------
ts : np.timedelta64
Returns
-------
np.timedelta64[ns]
"""
cdef:
NPY_DATETIMEUNIT td64_unit
int64_t td64_value, mult
str unitstr
td64_unit = get_datetime64_unit(ts)
if (
td64_unit != NPY_DATETIMEUNIT.NPY_FR_ns
and td64_unit != NPY_DATETIMEUNIT.NPY_FR_GENERIC
):
unitstr = npy_unit_to_abbrev(td64_unit)
td64_value = get_timedelta64_value(ts)
mult = precision_from_unit(unitstr)[0]
try:
# NB: cython#1381 this cannot be *=
td64_value = td64_value * mult
except OverflowError as err:
raise OutOfBoundsTimedelta(ts) from err
return np.timedelta64(td64_value, "ns")
return ts
cdef convert_to_timedelta64(object ts, str unit):
"""
Convert an incoming object to a timedelta64 if possible.
Before calling, unit must be standardized to avoid repeated unit conversion
Handle these types of objects:
- timedelta/Timedelta
- timedelta64
- an offset
- np.int64 (with unit providing a possible modifier)
- None/NaT
Return an ns based int64
"""
# Caller is responsible for checking unit not in ["Y", "y", "M"]
if checknull_with_nat_and_na(ts):
return np.timedelta64(NPY_NAT, "ns")
elif isinstance(ts, _Timedelta):
# already in the proper format
if ts._creso != NPY_FR_ns:
ts = ts.as_unit("ns").asm8
else:
ts = np.timedelta64(ts._value, "ns")
elif is_timedelta64_object(ts):
ts = ensure_td64ns(ts)
elif is_integer_object(ts):
if ts == NPY_NAT:
return np.timedelta64(NPY_NAT, "ns")
else:
ts = _maybe_cast_from_unit(ts, unit)
elif is_float_object(ts):
ts = _maybe_cast_from_unit(ts, unit)
elif isinstance(ts, str):
if (len(ts) > 0 and ts[0] == "P") or (len(ts) > 1 and ts[:2] == "-P"):
ts = parse_iso_format_string(ts)
else:
ts = parse_timedelta_string(ts)
ts = np.timedelta64(ts, "ns")
elif is_tick_object(ts):
ts = np.timedelta64(ts.nanos, "ns")
if PyDelta_Check(ts):
ts = np.timedelta64(delta_to_nanoseconds(ts), "ns")
elif not is_timedelta64_object(ts):
raise TypeError(f"Invalid type for timedelta scalar: {type(ts)}")
return ts.astype("timedelta64[ns]")
cdef _maybe_cast_from_unit(ts, str unit):
# caller is responsible for checking
# assert unit not in ["Y", "y", "M"]
try:
ts = cast_from_unit(ts, unit)
except OutOfBoundsDatetime as err:
raise OutOfBoundsTimedelta(
f"Cannot cast {ts} from {unit} to 'ns' without overflow."
) from err
ts = np.timedelta64(ts, "ns")
return ts
@cython.boundscheck(False)
@cython.wraparound(False)
def array_to_timedelta64(
ndarray values, str unit=None, str errors="raise"
) -> ndarray:
# values is object-dtype, may be 2D
"""
Convert an ndarray to an array of timedeltas. If errors == 'coerce',
coerce non-convertible objects to NaT. Otherwise, raise.
Returns
-------
np.ndarray[timedelta64ns]
"""
# Caller is responsible for checking
assert unit not in ["Y", "y", "M"]
cdef:
Py_ssize_t i, n = values.size
ndarray result = np.empty((<object>values).shape, dtype="m8[ns]")
object item
int64_t ival
cnp.broadcast mi = cnp.PyArray_MultiIterNew2(result, values)
cnp.flatiter it
if values.descr.type_num != cnp.NPY_OBJECT:
# raise here otherwise we segfault below
raise TypeError("array_to_timedelta64 'values' must have object dtype")
if errors not in {"ignore", "raise", "coerce"}:
raise ValueError("errors must be one of {'ignore', 'raise', or 'coerce'}")
if unit is not None and errors != "coerce":
it = cnp.PyArray_IterNew(values)
for i in range(n):
# Analogous to: item = values[i]
item = cnp.PyArray_GETITEM(values, cnp.PyArray_ITER_DATA(it))
if isinstance(item, str):
raise ValueError(
"unit must not be specified if the input contains a str"
)
cnp.PyArray_ITER_NEXT(it)
# Usually, we have all strings. If so, we hit the fast path.
# If this path fails, we try conversion a different way, and
# this is where all of the error handling will take place.
try:
for i in range(n):
# Analogous to: item = values[i]
item = <object>(<PyObject**>cnp.PyArray_MultiIter_DATA(mi, 1))[0]
ival = _item_to_timedelta64_fastpath(item)
# Analogous to: iresult[i] = ival
(<int64_t*>cnp.PyArray_MultiIter_DATA(mi, 0))[0] = ival
cnp.PyArray_MultiIter_NEXT(mi)
except (TypeError, ValueError):
cnp.PyArray_MultiIter_RESET(mi)
parsed_unit = parse_timedelta_unit(unit or "ns")
for i in range(n):
item = <object>(<PyObject**>cnp.PyArray_MultiIter_DATA(mi, 1))[0]
ival = _item_to_timedelta64(item, parsed_unit, errors)
(<int64_t*>cnp.PyArray_MultiIter_DATA(mi, 0))[0] = ival
cnp.PyArray_MultiIter_NEXT(mi)
return result
cdef int64_t _item_to_timedelta64_fastpath(object item) except? -1:
"""
See array_to_timedelta64.
"""
if item is NaT:
# we allow this check in the fast-path because NaT is a C-object
# so this is an inexpensive check
return NPY_NAT
else:
return parse_timedelta_string(item)
cdef int64_t _item_to_timedelta64(
object item,
str parsed_unit,
str errors
) except? -1:
"""
See array_to_timedelta64.
"""
try:
return get_timedelta64_value(convert_to_timedelta64(item, parsed_unit))
except ValueError as err:
if errors == "coerce":
return NPY_NAT
elif "unit abbreviation w/o a number" in str(err):
# re-raise with more pertinent message
msg = f"Could not convert '{item}' to NumPy timedelta"
raise ValueError(msg) from err
else:
raise
@cython.cpow(True)
cdef int64_t parse_timedelta_string(str ts) except? -1:
"""
Parse a regular format timedelta string. Return an int64_t (in ns)
or raise a ValueError on an invalid parse.
"""
cdef:
unicode c
bint neg = 0, have_dot = 0, have_value = 0, have_hhmmss = 0
object current_unit = None
int64_t result = 0, m = 0, r
list number = [], frac = [], unit = []
# neg : tracks if we have a leading negative for the value
# have_dot : tracks if we are processing a dot (either post hhmmss or
# inside an expression)
# have_value : track if we have at least 1 leading unit
# have_hhmmss : tracks if we have a regular format hh:mm:ss
if len(ts) == 0 or ts in nat_strings:
return NPY_NAT
for c in ts:
# skip whitespace / commas
if c == " " or c == ",":
pass
# positive signs are ignored
elif c == "+":
pass
# neg
elif c == "-":
if neg or have_value or have_hhmmss:
raise ValueError("only leading negative signs are allowed")
neg = 1
# number (ascii codes)
elif ord(c) >= 48 and ord(c) <= 57:
if have_dot:
# we found a dot, but now its just a fraction
if len(unit):
number.append(c)
have_dot = 0
else:
frac.append(c)
elif not len(unit):
number.append(c)
else:
r = timedelta_from_spec(number, frac, unit)
unit, number, frac = [], [c], []
result += timedelta_as_neg(r, neg)
# hh:mm:ss.
elif c == ":":
# we flip this off if we have a leading value
if have_value:
neg = 0
# we are in the pattern hh:mm:ss pattern
if len(number):
if current_unit is None:
current_unit = "h"
m = 1000000000 * 3600
elif current_unit == "h":
current_unit = "m"
m = 1000000000 * 60
elif current_unit == "m":
current_unit = "s"
m = 1000000000
r = <int64_t>int("".join(number)) * m
result += timedelta_as_neg(r, neg)
have_hhmmss = 1
else:
raise ValueError(f"expecting hh:mm:ss format, received: {ts}")
unit, number = [], []
# after the decimal point
elif c == ".":
if len(number) and current_unit is not None:
# by definition we had something like
# so we need to evaluate the final field from a
# hh:mm:ss (so current_unit is 'm')
if current_unit != "m":
raise ValueError("expected hh:mm:ss format before .")
m = 1000000000
r = <int64_t>int("".join(number)) * m
result += timedelta_as_neg(r, neg)
have_value = 1
unit, number, frac = [], [], []
have_dot = 1
# unit
else:
unit.append(c)
have_value = 1
have_dot = 0
# we had a dot, but we have a fractional
# value since we have an unit
if have_dot and len(unit):
r = timedelta_from_spec(number, frac, unit)
result += timedelta_as_neg(r, neg)
# we have a dot as part of a regular format
# e.g. hh:mm:ss.fffffff
elif have_dot:
if ((len(number) or len(frac)) and not len(unit)
and current_unit is None):
raise ValueError("no units specified")
if len(frac) > 0 and len(frac) <= 3:
m = 10**(3 -len(frac)) * 1000 * 1000
elif len(frac) > 3 and len(frac) <= 6:
m = 10**(6 -len(frac)) * 1000
elif len(frac) > 6 and len(frac) <= 9:
m = 10**(9 -len(frac))
else:
m = 1
frac = frac[:9]
r = <int64_t>int("".join(frac)) * m
result += timedelta_as_neg(r, neg)
# we have a regular format
# we must have seconds at this point (hence the unit is still 'm')
elif current_unit is not None:
if current_unit != "m":
raise ValueError("expected hh:mm:ss format")
m = 1000000000
r = <int64_t>int("".join(number)) * m
result += timedelta_as_neg(r, neg)
# we have a last abbreviation
elif len(unit):
if len(number):
r = timedelta_from_spec(number, frac, unit)
result += timedelta_as_neg(r, neg)
else:
raise ValueError("unit abbreviation w/o a number")
# we only have symbols and no numbers
elif len(number) == 0:
raise ValueError("symbols w/o a number")
# treat as nanoseconds
# but only if we don't have anything else
else:
if have_value:
raise ValueError("have leftover units")
if len(number):
r = timedelta_from_spec(number, frac, "ns")
result += timedelta_as_neg(r, neg)
return result
cdef int64_t timedelta_as_neg(int64_t value, bint neg):
"""
Parameters
----------
value : int64_t of the timedelta value
neg : bool if the a negative value
"""
if neg:
return -value
return value
cdef timedelta_from_spec(object number, object frac, object unit):
"""
Parameters
----------
number : a list of number digits
frac : a list of frac digits
unit : a list of unit characters
"""
cdef:
str n
unit = "".join(unit)
if unit in ["M", "Y", "y"]:
raise ValueError(
"Units 'M', 'Y' and 'y' do not represent unambiguous timedelta "
"values and are not supported."
)
unit = parse_timedelta_unit(unit)
n = "".join(number) + "." + "".join(frac)
return cast_from_unit(float(n), unit)
cpdef inline str parse_timedelta_unit(str unit):
"""
Parameters
----------
unit : str or None
Returns
-------
str
Canonical unit string.
Raises
------
ValueError : on non-parseable input
"""
if unit is None:
return "ns"
elif unit == "M":
return unit
try:
return timedelta_abbrevs[unit.lower()]
except KeyError:
raise ValueError(f"invalid unit abbreviation: {unit}")
# ----------------------------------------------------------------------
# Timedelta ops utilities
cdef bint _validate_ops_compat(other):
# return True if we are compat with operating
if checknull_with_nat(other):
return True
elif is_any_td_scalar(other):
return True
elif isinstance(other, str):
return True
return False
def _op_unary_method(func, name):
def f(self):
new_value = func(self._value)
return _timedelta_from_value_and_reso(Timedelta, new_value, self._creso)
f.__name__ = name
return f
def _binary_op_method_timedeltalike(op, name):
# define a binary operation that only works if the other argument is
# timedelta like or an array of timedeltalike
def f(self, other):
if other is NaT:
return NaT
elif is_datetime64_object(other) or (
PyDateTime_Check(other) and not isinstance(other, ABCTimestamp)
):
# this case is for a datetime object that is specifically
# *not* a Timestamp, as the Timestamp case will be
# handled after `_validate_ops_compat` returns False below
from pandas._libs.tslibs.timestamps import Timestamp
return op(self, Timestamp(other))
# We are implicitly requiring the canonical behavior to be
# defined by Timestamp methods.
elif is_array(other):
if other.ndim == 0:
# see also: item_from_zerodim
item = cnp.PyArray_ToScalar(cnp.PyArray_DATA(other), other)
return f(self, item)
elif other.dtype.kind in "mM":
return op(self.to_timedelta64(), other)
elif other.dtype.kind == "O":
return np.array([op(self, x) for x in other])
else:
return NotImplemented
elif not _validate_ops_compat(other):
# Includes any of our non-cython classes
return NotImplemented
try:
other = Timedelta(other)
except ValueError:
# failed to parse as timedelta
return NotImplemented
if other is NaT:
# e.g. if original other was timedelta64('NaT')
return NaT
# Matching numpy, we cast to the higher resolution. Unlike numpy,
# we raise instead of silently overflowing during this casting.
if self._creso < other._creso:
self = (<_Timedelta>self)._as_creso(other._creso, round_ok=True)
elif self._creso > other._creso:
other = (<_Timedelta>other)._as_creso(self._creso, round_ok=True)
res = op(self._value, other._value)
if res == NPY_NAT:
# e.g. test_implementation_limits
# TODO: more generally could do an overflowcheck in op?
return NaT
return _timedelta_from_value_and_reso(Timedelta, res, reso=self._creso)
f.__name__ = name
return f
# ----------------------------------------------------------------------
# Timedelta Construction
cdef int64_t parse_iso_format_string(str ts) except? -1:
"""
Extracts and cleanses the appropriate values from a match object with
groups for each component of an ISO 8601 duration
Parameters
----------
ts: str
ISO 8601 Duration formatted string
Returns
-------
ns: int64_t
Precision in nanoseconds of matched ISO 8601 duration
Raises
------
ValueError
If ``ts`` cannot be parsed
"""
cdef:
unicode c
int64_t result = 0, r
int p = 0, sign = 1
object dec_unit = "ms", err_msg
bint have_dot = 0, have_value = 0, neg = 0
list number = [], unit = []
err_msg = f"Invalid ISO 8601 Duration format - {ts}"
if ts[0] == "-":
sign = -1
ts = ts[1:]
for c in ts:
# number (ascii codes)
if 48 <= ord(c) <= 57:
have_value = 1
if have_dot:
if p == 3 and dec_unit != "ns":
unit.append(dec_unit)
if dec_unit == "ms":
dec_unit = "us"
elif dec_unit == "us":
dec_unit = "ns"
p = 0
p += 1
if not len(unit):
number.append(c)
else:
r = timedelta_from_spec(number, "0", unit)
result += timedelta_as_neg(r, neg)
neg = 0
unit, number = [], [c]
else:
if c == "P" or c == "T":
pass # ignore marking characters P and T
elif c == "-":
if neg or have_value:
raise ValueError(err_msg)
else:
neg = 1
elif c == "+":
pass
elif c in ["W", "D", "H", "M"]:
if c in ["H", "M"] and len(number) > 2:
raise ValueError(err_msg)
if c == "M":
c = "min"
unit.append(c)
r = timedelta_from_spec(number, "0", unit)
result += timedelta_as_neg(r, neg)
neg = 0
unit, number = [], []
elif c == ".":
# append any seconds
if len(number):
r = timedelta_from_spec(number, "0", "S")
result += timedelta_as_neg(r, neg)
unit, number = [], []
have_dot = 1
elif c == "S":
if have_dot: # ms, us, or ns
if not len(number) or p > 3:
raise ValueError(err_msg)
# pad to 3 digits as required
pad = 3 - p
while pad > 0:
number.append("0")
pad -= 1
r = timedelta_from_spec(number, "0", dec_unit)
result += timedelta_as_neg(r, neg)
else: # seconds
r = timedelta_from_spec(number, "0", "S")
result += timedelta_as_neg(r, neg)
else:
raise ValueError(err_msg)
if not have_value:
# Received string only - never parsed any values
raise ValueError(err_msg)
return sign*result
cdef _to_py_int_float(v):
# Note: This used to be defined inside Timedelta.__new__
# but cython will not allow `cdef` functions to be defined dynamically.
if is_integer_object(v):
return int(v)
elif is_float_object(v):
return float(v)
raise TypeError(f"Invalid type {type(v)}. Must be int or float.")
def _timedelta_unpickle(value, reso):
return _timedelta_from_value_and_reso(Timedelta, value, reso)
cdef _timedelta_from_value_and_reso(cls, int64_t value, NPY_DATETIMEUNIT reso):
# Could make this a classmethod if/when cython supports cdef classmethods
cdef:
_Timedelta td_base
assert value != NPY_NAT
# For millisecond and second resos, we cannot actually pass int(value) because
# many cases would fall outside of the pytimedelta implementation bounds.
# We pass 0 instead, and override seconds, microseconds, days.
# In principle we could pass 0 for ns and us too.
if reso == NPY_FR_ns:
td_base = _Timedelta.__new__(cls, microseconds=int(value) // 1000)
elif reso == NPY_DATETIMEUNIT.NPY_FR_us:
td_base = _Timedelta.__new__(cls, microseconds=int(value))
elif reso == NPY_DATETIMEUNIT.NPY_FR_ms:
td_base = _Timedelta.__new__(cls, milliseconds=0)
elif reso == NPY_DATETIMEUNIT.NPY_FR_s:
td_base = _Timedelta.__new__(cls, seconds=0)
# Other resolutions are disabled but could potentially be implemented here:
# elif reso == NPY_DATETIMEUNIT.NPY_FR_m:
# td_base = _Timedelta.__new__(Timedelta, minutes=int(value))
# elif reso == NPY_DATETIMEUNIT.NPY_FR_h:
# td_base = _Timedelta.__new__(Timedelta, hours=int(value))
# elif reso == NPY_DATETIMEUNIT.NPY_FR_D:
# td_base = _Timedelta.__new__(Timedelta, days=int(value))
else:
raise NotImplementedError(
"Only resolutions 's', 'ms', 'us', 'ns' are supported."
)
td_base._value = value
td_base._is_populated = 0
td_base._creso = reso
return td_base
class MinMaxReso:
"""
We need to define min/max/resolution on both the Timedelta _instance_
and Timedelta class. On an instance, these depend on the object's _reso.
On the class, we default to the values we would get with nanosecond _reso.
"""
def __init__(self, name):
self._name = name
def __get__(self, obj, type=None):
if self._name == "min":
val = np.iinfo(np.int64).min + 1
elif self._name == "max":
val = np.iinfo(np.int64).max
else:
assert self._name == "resolution"
val = 1
if obj is None:
# i.e. this is on the class, default to nanos
return Timedelta(val)
else:
return Timedelta._from_value_and_reso(val, obj._creso)
def __set__(self, obj, value):
raise AttributeError(f"{self._name} is not settable.")
# Similar to Timestamp/datetime, this is a construction requirement for
# timedeltas that we need to do object instantiation in python. This will
# serve as a C extension type that shadows the Python class, where we do any
# heavy lifting.
cdef class _Timedelta(timedelta):
# cdef readonly:
# int64_t value # nanoseconds
# bint _is_populated # are my components populated
# int64_t _d, _h, _m, _s, _ms, _us, _ns
# NPY_DATETIMEUNIT _reso
# higher than np.ndarray and np.matrix
__array_priority__ = 100
min = MinMaxReso("min")
max = MinMaxReso("max")
resolution = MinMaxReso("resolution")
@property
def value(self):
try:
return convert_reso(self._value, self._creso, NPY_FR_ns, False)
except OverflowError:
raise OverflowError(
"Cannot convert Timedelta to nanoseconds without overflow. "
"Use `.asm8.view('i8')` to cast represent Timedelta in its own "
f"unit (here, {self.unit})."
)
@property
def _unit(self) -> str:
"""
The abbreviation associated with self._creso.
"""
return npy_unit_to_abbrev(self._creso)
@property
def days(self) -> int: # TODO(cython3): make cdef property
"""
Returns the days of the timedelta.
Returns
-------
int
Examples
--------
>>> td = pd.Timedelta(1, "d")
>>> td.days
1
>>> td = pd.Timedelta('4 min 3 us 42 ns')
>>> td.days
0
"""
# NB: using the python C-API PyDateTime_DELTA_GET_DAYS will fail
# (or be incorrect)
self._ensure_components()
return self._d
@property
def seconds(self) -> int: # TODO(cython3): make cdef property
"""
Return the total hours, minutes, and seconds of the timedelta as seconds.
Timedelta.seconds = hours * 3600 + minutes * 60 + seconds.
Returns
-------
int
Number of seconds.
See Also
--------
Timedelta.components : Return all attributes with assigned values
(i.e. days, hours, minutes, seconds, milliseconds, microseconds,
nanoseconds).
Timedelta.total_seconds : Express the Timedelta as total number of seconds.
Examples
--------
**Using string input**
>>> td = pd.Timedelta('1 days 2 min 3 us 42 ns')
>>> td.seconds
120
**Using integer input**
>>> td = pd.Timedelta(42, unit='s')
>>> td.seconds
42
"""
# NB: using the python C-API PyDateTime_DELTA_GET_SECONDS will fail
# (or be incorrect)
self._ensure_components()
return self._h * 3600 + self._m * 60 + self._s
@property
def microseconds(self) -> int: # TODO(cython3): make cdef property
# NB: using the python C-API PyDateTime_DELTA_GET_MICROSECONDS will fail
# (or be incorrect)
self._ensure_components()
return self._ms * 1000 + self._us
def total_seconds(self) -> float:
"""
Total seconds in the duration.
Examples
--------
>>> td = pd.Timedelta('1min')
>>> td
Timedelta('0 days 00:01:00')
>>> td.total_seconds()
60.0
"""
# We need to override bc we overrode days/seconds/microseconds
# TODO: add nanos/1e9?
return self.days * 24 * 3600 + self.seconds + self.microseconds / 1_000_000
@property
def unit(self) -> str:
return npy_unit_to_abbrev(self._creso)
def __hash__(_Timedelta self):
if self._has_ns():
# Note: this does *not* satisfy the invariance
# td1 == td2 \\Rightarrow hash(td1) == hash(td2)
# if td1 and td2 have different _resos. timedelta64 also has this
# non-invariant behavior.
# see GH#44504
return hash(self._value)
elif self._is_in_pytimedelta_bounds() and (
self._creso == NPY_FR_ns or self._creso == NPY_DATETIMEUNIT.NPY_FR_us
):
# If we can defer to timedelta.__hash__, do so, as that
# ensures the hash is invariant to our _reso.
# We can only defer for ns and us, as for these two resos we
# call _Timedelta.__new__ with the correct input in
# _timedelta_from_value_and_reso; so timedelta.__hash__
# will be correct
return timedelta.__hash__(self)
else:
# We want to ensure that two equivalent Timedelta objects
# have the same hash. So we try downcasting to the next-lowest
# resolution.
try:
obj = (<_Timedelta>self)._as_creso(<NPY_DATETIMEUNIT>(self._creso + 1))
except OutOfBoundsTimedelta:
# Doesn't fit, so we're off the hook
return hash(self._value)
else:
return hash(obj)
def __richcmp__(_Timedelta self, object other, int op):
cdef:
_Timedelta ots
if isinstance(other, _Timedelta):
ots = other
elif is_any_td_scalar(other):
try:
ots = Timedelta(other)
except OutOfBoundsTimedelta as err:
# GH#49021 pytimedelta.max overflows
if not PyDelta_Check(other):
# TODO: handle this case
raise
ltup = (self.days, self.seconds, self.microseconds, self.nanoseconds)
rtup = (other.days, other.seconds, other.microseconds, 0)
if op == Py_EQ:
return ltup == rtup
elif op == Py_NE:
return ltup != rtup
elif op == Py_LT:
return ltup < rtup
elif op == Py_LE:
return ltup <= rtup
elif op == Py_GT:
return ltup > rtup
elif op == Py_GE:
return ltup >= rtup
elif other is NaT:
return op == Py_NE
elif util.is_array(other):
if other.dtype.kind == "m":
return PyObject_RichCompare(self.asm8, other, op)
elif other.dtype.kind == "O":
# operate element-wise
return np.array(
[PyObject_RichCompare(self, x, op) for x in other],
dtype=bool,
)
if op == Py_EQ:
return np.zeros(other.shape, dtype=bool)
elif op == Py_NE:
return np.ones(other.shape, dtype=bool)
return NotImplemented # let other raise TypeError
else:
return NotImplemented
if self._creso == ots._creso:
return cmp_scalar(self._value, ots._value, op)
return self._compare_mismatched_resos(ots, op)
# TODO: re-use/share with Timestamp
cdef bint _compare_mismatched_resos(self, _Timedelta other, op):
# Can't just dispatch to numpy as they silently overflow and get it wrong
cdef:
npy_datetimestruct dts_self
npy_datetimestruct dts_other
# dispatch to the datetimestruct utils instead of writing new ones!
pandas_datetime_to_datetimestruct(self._value, self._creso, &dts_self)
pandas_datetime_to_datetimestruct(other._value, other._creso, &dts_other)
return cmp_dtstructs(&dts_self, &dts_other, op)
cdef bint _has_ns(self):
if self._creso == NPY_FR_ns:
return self._value % 1000 != 0
elif self._creso < NPY_FR_ns:
# i.e. seconds, millisecond, microsecond
return False
else:
raise NotImplementedError(self._creso)
cdef bint _is_in_pytimedelta_bounds(self):
"""
Check if we are within the bounds of datetime.timedelta.
"""
self._ensure_components()
return -999999999 <= self._d and self._d <= 999999999
cdef _ensure_components(_Timedelta self):
"""
compute the components
"""
if self._is_populated:
return
cdef:
pandas_timedeltastruct tds
pandas_timedelta_to_timedeltastruct(self._value, self._creso, &tds)
self._d = tds.days
self._h = tds.hrs
self._m = tds.min
self._s = tds.sec
self._ms = tds.ms
self._us = tds.us
self._ns = tds.ns
self._seconds = tds.seconds
self._microseconds = tds.microseconds
self._is_populated = 1
cpdef timedelta to_pytimedelta(_Timedelta self):
"""
Convert a pandas Timedelta object into a python ``datetime.timedelta`` object.
Timedelta objects are internally saved as numpy datetime64[ns] dtype.
Use to_pytimedelta() to convert to object dtype.
Returns
-------
datetime.timedelta or numpy.array of datetime.timedelta
See Also
--------
to_timedelta : Convert argument to Timedelta type.
Notes
-----
Any nanosecond resolution will be lost.
Examples
--------
>>> td = pd.Timedelta('3D')
>>> td
Timedelta('3 days 00:00:00')
>>> td.to_pytimedelta()
datetime.timedelta(days=3)
"""
if self._creso == NPY_FR_ns:
return timedelta(microseconds=int(self._value) / 1000)
# TODO(@WillAyd): is this the right way to use components?
self._ensure_components()
return timedelta(
days=self._d, seconds=self._seconds, microseconds=self._microseconds
)
def to_timedelta64(self) -> np.timedelta64:
"""
Return a numpy.timedelta64 object with 'ns' precision.
Examples
--------
>>> td = pd.Timedelta('3D')
>>> td
Timedelta('3 days 00:00:00')
>>> td.to_timedelta64()
numpy.timedelta64(259200000000000,'ns')
"""
cdef:
str abbrev = npy_unit_to_abbrev(self._creso)
# TODO: way to create a np.timedelta64 obj with the reso directly
# instead of having to get the abbrev?
return np.timedelta64(self._value, abbrev)
def to_numpy(self, dtype=None, copy=False) -> np.timedelta64:
"""
Convert the Timedelta to a NumPy timedelta64.
This is an alias method for `Timedelta.to_timedelta64()`. The dtype and
copy parameters are available here only for compatibility. Their values
will not affect the return value.
Returns
-------
numpy.timedelta64
See Also
--------
Series.to_numpy : Similar method for Series.
Examples
--------
>>> td = pd.Timedelta('3D')
>>> td
Timedelta('3 days 00:00:00')
>>> td.to_numpy()
numpy.timedelta64(259200000000000,'ns')
"""
if dtype is not None or copy is not False:
raise ValueError(
"Timedelta.to_numpy dtype and copy arguments are ignored"
)
return self.to_timedelta64()
def view(self, dtype):
"""
Array view compatibility.
Parameters
----------
dtype : str or dtype
The dtype to view the underlying data as.
Examples
--------
>>> td = pd.Timedelta('3D')
>>> td
Timedelta('3 days 00:00:00')
>>> td.view(int)
259200000000000
"""
return np.timedelta64(self._value).view(dtype)
@property
def components(self):
"""
Return a components namedtuple-like.
Examples
--------
>>> td = pd.Timedelta('2 day 4 min 3 us 42 ns')
>>> td.components
Components(days=2, hours=0, minutes=4, seconds=0, milliseconds=0,
microseconds=3, nanoseconds=42)
"""
self._ensure_components()
# return the named tuple
return Components(self._d, self._h, self._m, self._s,
self._ms, self._us, self._ns)
@property
def asm8(self) -> np.timedelta64:
"""
Return a numpy timedelta64 array scalar view.
Provides access to the array scalar view (i.e. a combination of the
value and the units) associated with the numpy.timedelta64().view(),
including a 64-bit integer representation of the timedelta in
nanoseconds (Python int compatible).
Returns
-------
numpy timedelta64 array scalar view
Array scalar view of the timedelta in nanoseconds.
Examples
--------
>>> td = pd.Timedelta('1 days 2 min 3 us 42 ns')
>>> td.asm8
numpy.timedelta64(86520000003042,'ns')
>>> td = pd.Timedelta('2 min 3 s')
>>> td.asm8
numpy.timedelta64(123000000000,'ns')
>>> td = pd.Timedelta('3 ms 5 us')
>>> td.asm8
numpy.timedelta64(3005000,'ns')
>>> td = pd.Timedelta(42, unit='ns')
>>> td.asm8
numpy.timedelta64(42,'ns')
"""
return self.to_timedelta64()
@property
def resolution_string(self) -> str:
"""
Return a string representing the lowest timedelta resolution.
Each timedelta has a defined resolution that represents the lowest OR
most granular level of precision. Each level of resolution is
represented by a short string as defined below:
Resolution: Return value
* Days: 'D'
* Hours: 'H'
* Minutes: 'T'
* Seconds: 'S'
* Milliseconds: 'L'
* Microseconds: 'U'
* Nanoseconds: 'N'
Returns
-------
str
Timedelta resolution.
Examples
--------
>>> td = pd.Timedelta('1 days 2 min 3 us 42 ns')
>>> td.resolution_string
'N'
>>> td = pd.Timedelta('1 days 2 min 3 us')
>>> td.resolution_string
'U'
>>> td = pd.Timedelta('2 min 3 s')
>>> td.resolution_string
'S'
>>> td = pd.Timedelta(36, unit='us')
>>> td.resolution_string
'U'
"""
self._ensure_components()
if self._ns:
return "N"
elif self._us:
return "U"
elif self._ms:
return "L"
elif self._s:
return "S"
elif self._m:
return "T"
elif self._h:
return "H"
else:
return "D"
@property
def nanoseconds(self):
"""
Return the number of nanoseconds (n), where 0 <= n < 1 microsecond.
Returns
-------
int
Number of nanoseconds.
See Also
--------
Timedelta.components : Return all attributes with assigned values
(i.e. days, hours, minutes, seconds, milliseconds, microseconds,
nanoseconds).
Examples
--------
**Using string input**
>>> td = pd.Timedelta('1 days 2 min 3 us 42 ns')
>>> td.nanoseconds
42
**Using integer input**
>>> td = pd.Timedelta(42, unit='ns')
>>> td.nanoseconds
42
"""
self._ensure_components()
return self._ns
def _repr_base(self, format=None) -> str:
"""
Parameters
----------
format : None|all|sub_day|long
Returns
-------
converted : string of a Timedelta
"""
cdef:
str sign, fmt
dict comp_dict
object subs
self._ensure_components()
if self._d < 0:
sign = " +"
else:
sign = " "
if format == "all":
fmt = ("{days} days{sign}{hours:02}:{minutes:02}:{seconds:02}."
"{milliseconds:03}{microseconds:03}{nanoseconds:03}")
else:
# if we have a partial day
subs = (self._h or self._m or self._s or
self._ms or self._us or self._ns)
if self._ms or self._us or self._ns:
seconds_fmt = "{seconds:02}.{milliseconds:03}{microseconds:03}"
if self._ns:
# GH#9309
seconds_fmt += "{nanoseconds:03}"
else:
seconds_fmt = "{seconds:02}"
if format == "sub_day" and not self._d:
fmt = "{hours:02}:{minutes:02}:" + seconds_fmt
elif subs or format == "long":
fmt = "{days} days{sign}{hours:02}:{minutes:02}:" + seconds_fmt
else:
fmt = "{days} days"
comp_dict = self.components._asdict()
comp_dict["sign"] = sign
return fmt.format(**comp_dict)
def __repr__(self) -> str:
repr_based = self._repr_base(format="long")
return f"Timedelta('{repr_based}')"
def __str__(self) -> str:
return self._repr_base(format="long")
def __bool__(self) -> bool:
return self._value!= 0
def isoformat(self) -> str:
"""
Format the Timedelta as ISO 8601 Duration.
``P[n]Y[n]M[n]DT[n]H[n]M[n]S``, where the ``[n]`` s are replaced by the
values. See https://en.wikipedia.org/wiki/ISO_8601#Durations.
Returns
-------
str
See Also
--------
Timestamp.isoformat : Function is used to convert the given
Timestamp object into the ISO format.
Notes
-----
The longest component is days, whose value may be larger than
365.
Every component is always included, even if its value is 0.
Pandas uses nanosecond precision, so up to 9 decimal places may
be included in the seconds component.
Trailing 0's are removed from the seconds component after the decimal.
We do not 0 pad components, so it's `...T5H...`, not `...T05H...`
Examples
--------
>>> td = pd.Timedelta(days=6, minutes=50, seconds=3,
... milliseconds=10, microseconds=10, nanoseconds=12)
>>> td.isoformat()
'P6DT0H50M3.010010012S'
>>> pd.Timedelta(hours=1, seconds=10).isoformat()
'P0DT1H0M10S'
>>> pd.Timedelta(days=500.5).isoformat()
'P500DT12H0M0S'
"""
components = self.components
seconds = (f"{components.seconds}."
f"{components.milliseconds:0>3}"
f"{components.microseconds:0>3}"
f"{components.nanoseconds:0>3}")
# Trim unnecessary 0s, 1.000000000 -> 1
seconds = seconds.rstrip("0").rstrip(".")
tpl = (f"P{components.days}DT{components.hours}"
f"H{components.minutes}M{seconds}S")
return tpl
# ----------------------------------------------------------------
# Constructors
@classmethod
def _from_value_and_reso(cls, int64_t value, NPY_DATETIMEUNIT reso):
# exposing as classmethod for testing
return _timedelta_from_value_and_reso(cls, value, reso)
def as_unit(self, str unit, bint round_ok=True):
"""
Convert the underlying int64 representation to the given unit.
Parameters
----------
unit : {"ns", "us", "ms", "s"}
round_ok : bool, default True
If False and the conversion requires rounding, raise.
Returns
-------
Timedelta
Examples
--------
>>> td = pd.Timedelta('1001ms')
>>> td
Timedelta('0 days 00:00:01.001000')
>>> td.as_unit('s')
Timedelta('0 days 00:00:01')
"""
dtype = np.dtype(f"m8[{unit}]")
reso = get_unit_from_dtype(dtype)
return self._as_creso(reso, round_ok=round_ok)
@cython.cdivision(False)
cdef _Timedelta _as_creso(self, NPY_DATETIMEUNIT reso, bint round_ok=True):
cdef:
int64_t value
if reso == self._creso:
return self
try:
value = convert_reso(self._value, self._creso, reso, round_ok=round_ok)
except OverflowError as err:
unit = npy_unit_to_abbrev(reso)
raise OutOfBoundsTimedelta(
f"Cannot cast {self} to unit='{unit}' without overflow."
) from err
return type(self)._from_value_and_reso(value, reso=reso)
cpdef _maybe_cast_to_matching_resos(self, _Timedelta other):
"""
If _resos do not match, cast to the higher resolution, raising on overflow.
"""
if self._creso > other._creso:
other = other._as_creso(self._creso)
elif self._creso < other._creso:
self = self._as_creso(other._creso)
return self, other
# Python front end to C extension type _Timedelta
# This serves as the box for timedelta64
class Timedelta(_Timedelta):
"""
Represents a duration, the difference between two dates or times.
Timedelta is the pandas equivalent of python's ``datetime.timedelta``
and is interchangeable with it in most cases.
Parameters
----------
value : Timedelta, timedelta, np.timedelta64, str, or int
unit : str, default 'ns'
Denote the unit of the input, if input is an integer.
Possible values:
* 'W', 'D', 'T', 'S', 'L', 'U', or 'N'
* 'days' or 'day'
* 'hours', 'hour', 'hr', or 'h'
* 'minutes', 'minute', 'min', or 'm'
* 'seconds', 'second', or 'sec'
* 'milliseconds', 'millisecond', 'millis', or 'milli'
* 'microseconds', 'microsecond', 'micros', or 'micro'
* 'nanoseconds', 'nanosecond', 'nanos', 'nano', or 'ns'.
**kwargs
Available kwargs: {days, seconds, microseconds,
milliseconds, minutes, hours, weeks}.
Values for construction in compat with datetime.timedelta.
Numpy ints and floats will be coerced to python ints and floats.
Notes
-----
The constructor may take in either both values of value and unit or
kwargs as above. Either one of them must be used during initialization
The ``.value`` attribute is always in ns.
If the precision is higher than nanoseconds, the precision of the duration is
truncated to nanoseconds.
Examples
--------
Here we initialize Timedelta object with both value and unit
>>> td = pd.Timedelta(1, "d")
>>> td
Timedelta('1 days 00:00:00')
Here we initialize the Timedelta object with kwargs
>>> td2 = pd.Timedelta(days=1)
>>> td2
Timedelta('1 days 00:00:00')
We see that either way we get the same result
"""
_req_any_kwargs_new = {"weeks", "days", "hours", "minutes", "seconds",
"milliseconds", "microseconds", "nanoseconds"}
def __new__(cls, object value=_no_input, unit=None, **kwargs):
if value is _no_input:
if not len(kwargs):
raise ValueError("cannot construct a Timedelta without a "
"value/unit or descriptive keywords "
"(days,seconds....)")
kwargs = {key: _to_py_int_float(kwargs[key]) for key in kwargs}
unsupported_kwargs = set(kwargs)
unsupported_kwargs.difference_update(cls._req_any_kwargs_new)
if unsupported_kwargs or not cls._req_any_kwargs_new.intersection(kwargs):
raise ValueError(
"cannot construct a Timedelta from the passed arguments, "
"allowed keywords are "
"[weeks, days, hours, minutes, seconds, "
"milliseconds, microseconds, nanoseconds]"
)
# GH43764, convert any input to nanoseconds first and then
# create the timestamp. This ensures that any potential
# nanosecond contributions from kwargs parsed as floats
# are taken into consideration.
seconds = int((
(
(kwargs.get("days", 0) + kwargs.get("weeks", 0) * 7) * 24
+ kwargs.get("hours", 0)
) * 3600
+ kwargs.get("minutes", 0) * 60
+ kwargs.get("seconds", 0)
) * 1_000_000_000
)
value = np.timedelta64(
int(kwargs.get("nanoseconds", 0))
+ int(kwargs.get("microseconds", 0) * 1_000)
+ int(kwargs.get("milliseconds", 0) * 1_000_000)
+ seconds
)
if unit in {"Y", "y", "M"}:
raise ValueError(
"Units 'M', 'Y', and 'y' are no longer supported, as they do not "
"represent unambiguous timedelta values durations."
)
# GH 30543 if pd.Timedelta already passed, return it
# check that only value is passed
if isinstance(value, _Timedelta):
# 'unit' is benign in this case, but e.g. days or seconds
# doesn't make sense here.
if len(kwargs):
# GH#48898
raise ValueError(
"Cannot pass both a Timedelta input and timedelta keyword "
"arguments, got "
f"{list(kwargs.keys())}"
)
return value
elif isinstance(value, str):
if unit is not None:
raise ValueError("unit must not be specified if the value is a str")
if (len(value) > 0 and value[0] == "P") or (
len(value) > 1 and value[:2] == "-P"
):
value = parse_iso_format_string(value)
else:
value = parse_timedelta_string(value)
value = np.timedelta64(value)
elif PyDelta_Check(value):
# pytimedelta object -> microsecond resolution
new_value = delta_to_nanoseconds(
value, reso=NPY_DATETIMEUNIT.NPY_FR_us
)
return cls._from_value_and_reso(
new_value, reso=NPY_DATETIMEUNIT.NPY_FR_us
)
elif is_timedelta64_object(value):
# Retain the resolution if possible, otherwise cast to the nearest
# supported resolution.
new_value = get_timedelta64_value(value)
if new_value == NPY_NAT:
# i.e. np.timedelta64("NaT")
return NaT
reso = get_datetime64_unit(value)
if not (is_supported_unit(reso) or
reso in [NPY_DATETIMEUNIT.NPY_FR_m,
NPY_DATETIMEUNIT.NPY_FR_h,
NPY_DATETIMEUNIT.NPY_FR_D,
NPY_DATETIMEUNIT.NPY_FR_W,
NPY_DATETIMEUNIT.NPY_FR_GENERIC]):
err = npy_unit_to_abbrev(reso)
raise ValueError(
f"Unit {err} is not supported. "
"Only unambiguous timedelta values durations are supported. "
"Allowed units are 'W', 'D', 'h', 'm', 's', 'ms', 'us', 'ns'")
new_reso = get_supported_reso(reso)
if reso != NPY_DATETIMEUNIT.NPY_FR_GENERIC:
try:
new_value = convert_reso(
new_value,
reso,
new_reso,
round_ok=True,
)
except (OverflowError, OutOfBoundsDatetime) as err:
raise OutOfBoundsTimedelta(value) from err
return cls._from_value_and_reso(new_value, reso=new_reso)
elif is_tick_object(value):
new_reso = get_supported_reso(value._creso)
new_value = delta_to_nanoseconds(value, reso=new_reso)
return cls._from_value_and_reso(new_value, reso=new_reso)
elif is_integer_object(value) or is_float_object(value):
# unit=None is de-facto 'ns'
unit = parse_timedelta_unit(unit)
value = convert_to_timedelta64(value, unit)
elif checknull_with_nat_and_na(value):
return NaT
else:
raise ValueError(
"Value must be Timedelta, string, integer, "
f"float, timedelta or convertible, not {type(value).__name__}"
)
if is_timedelta64_object(value):
value = value.view("i8")
# nat
if value == NPY_NAT:
return NaT
return _timedelta_from_value_and_reso(cls, value, NPY_FR_ns)
def __setstate__(self, state):
if len(state) == 1:
# older pickle, only supported nanosecond
value = state[0]
reso = NPY_FR_ns
else:
value, reso = state
self._value= value
self._creso = reso
def __reduce__(self):
object_state = self._value, self._creso
return (_timedelta_unpickle, object_state)
@cython.cdivision(True)
def _round(self, freq, mode):
cdef:
int64_t result, unit
ndarray[int64_t] arr
from pandas._libs.tslibs.offsets import to_offset
to_offset(freq).nanos # raises on non-fixed freq
unit = delta_to_nanoseconds(to_offset(freq), self._creso)
arr = np.array([self._value], dtype="i8")
try:
result = round_nsint64(arr, mode, unit)[0]
except OverflowError as err:
raise OutOfBoundsTimedelta(
f"Cannot round {self} to freq={freq} without overflow"
) from err
return Timedelta._from_value_and_reso(result, self._creso)
def round(self, freq):
"""
Round the Timedelta to the specified resolution.
Parameters
----------
freq : str
Frequency string indicating the rounding resolution.
Returns
-------
a new Timedelta rounded to the given resolution of `freq`
Raises
------
ValueError if the freq cannot be converted
Examples
--------
>>> td = pd.Timedelta('1001ms')
>>> td
Timedelta('0 days 00:00:01.001000')
>>> td.round('s')
Timedelta('0 days 00:00:01')
"""
return self._round(freq, RoundTo.NEAREST_HALF_EVEN)
def floor(self, freq):
"""
Return a new Timedelta floored to this resolution.
Parameters
----------
freq : str
Frequency string indicating the flooring resolution.
Examples
--------
>>> td = pd.Timedelta('1001ms')
>>> td
Timedelta('0 days 00:00:01.001000')
>>> td.floor('s')
Timedelta('0 days 00:00:01')
"""
return self._round(freq, RoundTo.MINUS_INFTY)
def ceil(self, freq):
"""
Return a new Timedelta ceiled to this resolution.
Parameters
----------
freq : str
Frequency string indicating the ceiling resolution.
Examples
--------
>>> td = pd.Timedelta('1001ms')
>>> td
Timedelta('0 days 00:00:01.001000')
>>> td.ceil('s')
Timedelta('0 days 00:00:02')
"""
return self._round(freq, RoundTo.PLUS_INFTY)
# ----------------------------------------------------------------
# Arithmetic Methods
# TODO: Can some of these be defined in the cython class?
__neg__ = _op_unary_method(lambda x: -x, "__neg__")
__pos__ = _op_unary_method(lambda x: x, "__pos__")
__abs__ = _op_unary_method(lambda x: abs(x), "__abs__")
__add__ = _binary_op_method_timedeltalike(lambda x, y: x + y, "__add__")
__radd__ = _binary_op_method_timedeltalike(lambda x, y: x + y, "__radd__")
__sub__ = _binary_op_method_timedeltalike(lambda x, y: x - y, "__sub__")
__rsub__ = _binary_op_method_timedeltalike(lambda x, y: y - x, "__rsub__")
def __mul__(self, other):
if is_integer_object(other) or is_float_object(other):
if util.is_nan(other):
# np.nan * timedelta -> np.timedelta64("NaT"), in this case NaT
return NaT
return _timedelta_from_value_and_reso(
Timedelta,
<int64_t>(other * self._value),
reso=self._creso,
)
elif is_array(other):
if other.ndim == 0:
# see also: item_from_zerodim
item = cnp.PyArray_ToScalar(cnp.PyArray_DATA(other), other)
return self.__mul__(item)
return other * self.to_timedelta64()
return NotImplemented
__rmul__ = __mul__
def __truediv__(self, other):
if _should_cast_to_timedelta(other):
# We interpret NaT as timedelta64("NaT")
other = Timedelta(other)
if other is NaT:
return np.nan
if other._creso != self._creso:
self, other = self._maybe_cast_to_matching_resos(other)
return self._value/ float(other._value)
elif is_integer_object(other) or is_float_object(other):
# integers or floats
if util.is_nan(other):
return NaT
return Timedelta._from_value_and_reso(
<int64_t>(self._value/ other), self._creso
)
elif is_array(other):
if other.ndim == 0:
# see also: item_from_zerodim
item = cnp.PyArray_ToScalar(cnp.PyArray_DATA(other), other)
return self.__truediv__(item)
return self.to_timedelta64() / other
return NotImplemented
def __rtruediv__(self, other):
if _should_cast_to_timedelta(other):
# We interpret NaT as timedelta64("NaT")
other = Timedelta(other)
if other is NaT:
return np.nan
if self._creso != other._creso:
self, other = self._maybe_cast_to_matching_resos(other)
return float(other._value) / self._value
elif is_array(other):
if other.ndim == 0:
# see also: item_from_zerodim
item = cnp.PyArray_ToScalar(cnp.PyArray_DATA(other), other)
return self.__rtruediv__(item)
elif other.dtype.kind == "O":
# GH#31869
return np.array([x / self for x in other])
# TODO: if other.dtype.kind == "m" and other.dtype != self.asm8.dtype
# then should disallow for consistency with scalar behavior; requires
# deprecation cycle. (or changing scalar behavior)
return other / self.to_timedelta64()
return NotImplemented
def __floordiv__(self, other):
# numpy does not implement floordiv for timedelta64 dtype, so we cannot
# just defer
if _should_cast_to_timedelta(other):
# We interpret NaT as timedelta64("NaT")
other = Timedelta(other)
if other is NaT:
return np.nan
if self._creso != other._creso:
self, other = self._maybe_cast_to_matching_resos(other)
return self._value// other._value
elif is_integer_object(other) or is_float_object(other):
if util.is_nan(other):
return NaT
return type(self)._from_value_and_reso(self._value// other, self._creso)
elif is_array(other):
if other.ndim == 0:
# see also: item_from_zerodim
item = cnp.PyArray_ToScalar(cnp.PyArray_DATA(other), other)
return self.__floordiv__(item)
if other.dtype.kind == "m":
# also timedelta-like
with warnings.catch_warnings():
warnings.filterwarnings(
"ignore",
"invalid value encountered in floor_divide",
RuntimeWarning
)
result = self.asm8 // other
mask = other.view("i8") == NPY_NAT
if mask.any():
# We differ from numpy here
result = result.astype("f8")
result[mask] = np.nan
return result
elif other.dtype.kind in "iuf":
if other.ndim == 0:
return self // other.item()
else:
return self.to_timedelta64() // other
raise TypeError(f"Invalid dtype {other.dtype} for __floordiv__")
return NotImplemented
def __rfloordiv__(self, other):
# numpy does not implement floordiv for timedelta64 dtype, so we cannot
# just defer
if _should_cast_to_timedelta(other):
# We interpret NaT as timedelta64("NaT")
other = Timedelta(other)
if other is NaT:
return np.nan
if self._creso != other._creso:
self, other = self._maybe_cast_to_matching_resos(other)
return other._value// self._value
elif is_array(other):
if other.ndim == 0:
# see also: item_from_zerodim
item = cnp.PyArray_ToScalar(cnp.PyArray_DATA(other), other)
return self.__rfloordiv__(item)
if other.dtype.kind == "m":
# also timedelta-like
with warnings.catch_warnings():
warnings.filterwarnings(
"ignore",
"invalid value encountered in floor_divide",
RuntimeWarning
)
result = other // self.asm8
mask = other.view("i8") == NPY_NAT
if mask.any():
# We differ from numpy here
result = result.astype("f8")
result[mask] = np.nan
return result
# Includes integer array // Timedelta, disallowed in GH#19761
raise TypeError(f"Invalid dtype {other.dtype} for __floordiv__")
return NotImplemented
def __mod__(self, other):
# Naive implementation, room for optimization
return self.__divmod__(other)[1]
def __rmod__(self, other):
# Naive implementation, room for optimization
return self.__rdivmod__(other)[1]
def __divmod__(self, other):
# Naive implementation, room for optimization
div = self // other
return div, self - div * other
def __rdivmod__(self, other):
# Naive implementation, room for optimization
div = other // self
return div, other - div * self
def truediv_object_array(ndarray left, ndarray right):
cdef:
ndarray[object] result = np.empty((<object>left).shape, dtype=object)
object td64 # really timedelta64 if we find a way to declare that
object obj, res_value
_Timedelta td
Py_ssize_t i
for i in range(len(left)):
td64 = left[i]
obj = right[i]
if get_timedelta64_value(td64) == NPY_NAT:
# td here should be interpreted as a td64 NaT
if _should_cast_to_timedelta(obj):
res_value = np.nan
else:
# if its a number then let numpy handle division, otherwise
# numpy will raise
res_value = td64 / obj
else:
td = Timedelta(td64)
res_value = td / obj
result[i] = res_value
return result
def floordiv_object_array(ndarray left, ndarray right):
cdef:
ndarray[object] result = np.empty((<object>left).shape, dtype=object)
object td64 # really timedelta64 if we find a way to declare that
object obj, res_value
_Timedelta td
Py_ssize_t i
for i in range(len(left)):
td64 = left[i]
obj = right[i]
if get_timedelta64_value(td64) == NPY_NAT:
# td here should be interpreted as a td64 NaT
if _should_cast_to_timedelta(obj):
res_value = np.nan
else:
# if its a number then let numpy handle division, otherwise
# numpy will raise
res_value = td64 // obj
else:
td = Timedelta(td64)
res_value = td // obj
result[i] = res_value
return result
cdef bint is_any_td_scalar(object obj):
"""
Cython equivalent for `isinstance(obj, (timedelta, np.timedelta64, Tick))`
Parameters
----------
obj : object
Returns
-------
bool
"""
return (
PyDelta_Check(obj) or is_timedelta64_object(obj) or is_tick_object(obj)
)
cdef bint _should_cast_to_timedelta(object obj):
"""
Should we treat this object as a Timedelta for the purpose of a binary op
"""
return (
is_any_td_scalar(obj) or obj is None or obj is NaT or isinstance(obj, str)
)