Replace is_temporal checks with Cython version (#55506)

Author: WillAyd

pandas/_libs/lib.pyx

@@ -1649,7 +1649,7 @@ def infer_dtype(value: object, skipna: bool = True) -> str:
     if seen_val is False and skipna:
         return "empty"
 
-    if util.is_datetime64_object(val):
+    if cnp.is_datetime64_object(val):
         if is_datetime64_array(values, skipna=skipna):
             return "datetime64"
 
@@ -1733,7 +1733,7 @@ def infer_dtype(value: object, skipna: bool = True) -> str:
 
 
 cdef bint is_timedelta(object o):
-    return PyDelta_Check(o) or util.is_timedelta64_object(o)
+    return PyDelta_Check(o) or cnp.is_timedelta64_object(o)
 
 
 @cython.internal
@@ -2020,7 +2020,7 @@ cpdef bint is_datetime_array(ndarray values, bint skipna=True):
 @cython.internal
 cdef class Datetime64Validator(DatetimeValidator):
     cdef bint is_value_typed(self, object value) except -1:
-        return util.is_datetime64_object(value)
+        return cnp.is_datetime64_object(value)
 
 
 # Note: only python-exposed for tests
@@ -2034,7 +2034,7 @@ cpdef bint is_datetime64_array(ndarray values, bint skipna=True):
 @cython.internal
 cdef class AnyDatetimeValidator(DatetimeValidator):
     cdef bint is_value_typed(self, object value) except -1:
-        return util.is_datetime64_object(value) or (
+        return cnp.is_datetime64_object(value) or (
             PyDateTime_Check(value) and value.tzinfo is None
         )
 
@@ -2617,7 +2617,7 @@ def maybe_convert_objects(ndarray[object] objects,
             seen.complex_ = True
             if not convert_numeric:
                 break
-        elif PyDateTime_Check(val) or util.is_datetime64_object(val):
+        elif PyDateTime_Check(val) or cnp.is_datetime64_object(val):
 
             # if we have an tz's attached then return the objects
             if convert_non_numeric:

pandas/_libs/missing.pyx

@@ -120,17 +120,17 @@ cpdef bint is_matching_na(object left, object right, bint nan_matches_none=False
             and util.is_complex_object(right)
             and util.is_nan(right)
         )
-    elif util.is_datetime64_object(left):
+    elif cnp.is_datetime64_object(left):
         return (
             get_datetime64_value(left) == NPY_NAT
-            and util.is_datetime64_object(right)
+            and cnp.is_datetime64_object(right)
             and get_datetime64_value(right) == NPY_NAT
             and get_datetime64_unit(left) == get_datetime64_unit(right)
         )
-    elif util.is_timedelta64_object(left):
+    elif cnp.is_timedelta64_object(left):
         return (
             get_timedelta64_value(left) == NPY_NAT
-            and util.is_timedelta64_object(right)
+            and cnp.is_timedelta64_object(right)
             and get_timedelta64_value(right) == NPY_NAT
             and get_datetime64_unit(left) == get_datetime64_unit(right)
         )
@@ -169,9 +169,9 @@ cpdef bint checknull(object val, bint inf_as_na=False):
         elif inf_as_na:
             return val == INF or val == NEGINF
         return False
-    elif util.is_timedelta64_object(val):
+    elif cnp.is_timedelta64_object(val):
         return get_timedelta64_value(val) == NPY_NAT
-    elif util.is_datetime64_object(val):
+    elif cnp.is_datetime64_object(val):
         return get_datetime64_value(val) == NPY_NAT
     else:
         return is_decimal_na(val)

pandas/_libs/tslib.pyx

@@ -23,6 +23,7 @@ import_datetime()
 cimport numpy as cnp
 from numpy cimport (
     int64_t,
+    is_datetime64_object,
     ndarray,
 )
 
@@ -47,7 +48,6 @@ import_pandas_datetime()
 
 from pandas._libs.tslibs.strptime cimport parse_today_now
 from pandas._libs.util cimport (
-    is_datetime64_object,
     is_float_object,
     is_integer_object,
 )

pandas/_libs/tslibs/conversion.pyx

@@ -5,6 +5,7 @@ from libc.math cimport log10
 from numpy cimport (
     int32_t,
     int64_t,
+    is_datetime64_object,
 )
 
 cnp.import_array()
@@ -71,7 +72,6 @@ from pandas._libs.tslibs.tzconversion cimport (
     tz_localize_to_utc_single,
 )
 from pandas._libs.tslibs.util cimport (
-    is_datetime64_object,
     is_float_object,
     is_integer_object,
 )

pandas/_libs/tslibs/nattype.pyx

@@ -67,7 +67,7 @@ def _make_error_func(func_name: str, cls):
 
 
 cdef _nat_divide_op(self, other):
-    if PyDelta_Check(other) or util.is_timedelta64_object(other) or other is c_NaT:
+    if PyDelta_Check(other) or cnp.is_timedelta64_object(other) or other is c_NaT:
         return np.nan
     if util.is_integer_object(other) or util.is_float_object(other):
         return c_NaT
@@ -95,11 +95,11 @@ cdef class _NaT(datetime):
     __array_priority__ = 100
 
     def __richcmp__(_NaT self, object other, int op):
-        if util.is_datetime64_object(other) or PyDateTime_Check(other):
+        if cnp.is_datetime64_object(other) or PyDateTime_Check(other):
             # We treat NaT as datetime-like for this comparison
             return op == Py_NE
 
-        elif util.is_timedelta64_object(other) or PyDelta_Check(other):
+        elif cnp.is_timedelta64_object(other) or PyDelta_Check(other):
             # We treat NaT as timedelta-like for this comparison
             return op == Py_NE
 
@@ -137,7 +137,7 @@ cdef class _NaT(datetime):
             return c_NaT
         elif PyDelta_Check(other):
             return c_NaT
-        elif util.is_datetime64_object(other) or util.is_timedelta64_object(other):
+        elif cnp.is_datetime64_object(other) or cnp.is_timedelta64_object(other):
             return c_NaT
 
         elif util.is_integer_object(other):
@@ -175,7 +175,7 @@ cdef class _NaT(datetime):
             return c_NaT
         elif PyDelta_Check(other):
             return c_NaT
-        elif util.is_datetime64_object(other) or util.is_timedelta64_object(other):
+        elif cnp.is_datetime64_object(other) or cnp.is_timedelta64_object(other):
             return c_NaT
 
         elif util.is_integer_object(other):
@@ -1438,7 +1438,7 @@ cdef bint is_dt64nat(object val):
     """
     Is this a np.datetime64 object np.datetime64("NaT").
     """
-    if util.is_datetime64_object(val):
+    if cnp.is_datetime64_object(val):
         return get_datetime64_value(val) == NPY_NAT
     return False
 
@@ -1447,6 +1447,6 @@ cdef bint is_td64nat(object val):
     """
     Is this a np.timedelta64 object np.timedelta64("NaT").
     """
-    if util.is_timedelta64_object(val):
+    if cnp.is_timedelta64_object(val):
         return get_timedelta64_value(val) == NPY_NAT
     return False

pandas/_libs/tslibs/offsets.pyx

@@ -25,6 +25,7 @@ import numpy as np
 cimport numpy as cnp
 from numpy cimport (
     int64_t,
+    is_datetime64_object,
     ndarray,
 )
 
@@ -36,7 +37,6 @@ from pandas._libs.properties import cache_readonly
 
 from pandas._libs.tslibs cimport util
 from pandas._libs.tslibs.util cimport (
-    is_datetime64_object,
     is_float_object,
     is_integer_object,
 )
@@ -155,7 +155,7 @@ def apply_wraps(func):
         elif (
             isinstance(other, BaseOffset)
             or PyDelta_Check(other)
-            or util.is_timedelta64_object(other)
+            or cnp.is_timedelta64_object(other)
         ):
             # timedelta path
             return func(self, other)
@@ -762,7 +762,7 @@ cdef class BaseOffset:
         TypeError if `int(n)` raises
         ValueError if n != int(n)
         """
-        if util.is_timedelta64_object(n):
+        if cnp.is_timedelta64_object(n):
             raise TypeError(f"`n` argument must be an integer, got {type(n)}")
         try:
             nint = int(n)
@@ -1091,7 +1091,7 @@ cdef class Tick(SingleConstructorOffset):
             # PyDate_Check includes date, datetime
             return Timestamp(other) + self
 
-        if util.is_timedelta64_object(other) or PyDelta_Check(other):
+        if cnp.is_timedelta64_object(other) or PyDelta_Check(other):
             return other + self.delta
 
         raise ApplyTypeError(f"Unhandled type: {type(other).__name__}")

pandas/_libs/tslibs/period.pyx

@@ -1821,7 +1821,7 @@ cdef class _Period(PeriodMixin):
                                         f"Period(freq={self.freqstr})")
 
         if (
-            util.is_timedelta64_object(other) and
+            cnp.is_timedelta64_object(other) and
             get_timedelta64_value(other) == NPY_NAT
         ):
             # i.e. np.timedelta64("nat")
@@ -2810,7 +2810,7 @@ class Period(_Period):
                 raise ValueError("Must supply freq for datetime value")
             if isinstance(dt, Timestamp):
                 nanosecond = dt.nanosecond
-        elif util.is_datetime64_object(value):
+        elif cnp.is_datetime64_object(value):
             dt = Timestamp(value)
             if freq is None:
                 raise ValueError("Must supply freq for datetime value")

pandas/_libs/tslibs/strptime.pyx

@@ -25,6 +25,7 @@ from cpython.datetime cimport (
     timedelta,
     tzinfo,
 )
+
 from _strptime import (
     TimeRE as _TimeRE,
     _getlang,
@@ -42,6 +43,7 @@ import pytz
 cimport numpy as cnp
 from numpy cimport (
     int64_t,
+    is_datetime64_object,
     ndarray,
 )
 
@@ -69,9 +71,9 @@ from pandas._libs.tslibs.np_datetime cimport (
 import_pandas_datetime()
 
 from pandas._libs.tslibs.np_datetime import OutOfBoundsDatetime
+
 from pandas._libs.tslibs.timestamps cimport _Timestamp
 from pandas._libs.util cimport (
-    is_datetime64_object,
     is_float_object,
     is_integer_object,
 )

pandas/_libs/tslibs/timedeltas.pyx

@@ -20,6 +20,8 @@ import numpy as np
 cimport numpy as cnp
 from numpy cimport (
     int64_t,
+    is_datetime64_object,
+    is_timedelta64_object,
     ndarray,
 )
 
@@ -80,10 +82,8 @@ from pandas._libs.tslibs.np_datetime import (
 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 (

pandas/_libs/tslibs/timestamps.pyx

@@ -16,6 +16,7 @@ import numpy as np
 cimport numpy as cnp
 from numpy cimport (
     int64_t,
+    is_datetime64_object,
     ndarray,
     uint8_t,
 )
@@ -65,7 +66,6 @@ from pandas._libs.tslibs.dtypes cimport (
 )
 from pandas._libs.tslibs.util cimport (
     is_array,
-    is_datetime64_object,
     is_integer_object,
 )
 

pandas/_libs/tslibs/util.pxd

@@ -25,6 +25,7 @@ cdef extern from "Python.h":
 from numpy cimport (
     float64_t,
     int64_t,
+    is_timedelta64_object,
 )
 
 
@@ -51,7 +52,7 @@ cdef inline int64_t get_nat() noexcept:
 # --------------------------------------------------------------------
 # Type Checking
 
-cdef inline bint is_integer_object(object obj) noexcept nogil:
+cdef inline bint is_integer_object(object obj) noexcept:
     """
     Cython equivalent of
 
@@ -121,40 +122,10 @@ cdef inline bint is_bool_object(object obj) noexcept nogil:
             PyObject_TypeCheck(obj, &PyBoolArrType_Type))
 
 
-cdef inline bint is_real_number_object(object obj) noexcept nogil:
+cdef inline bint is_real_number_object(object obj) noexcept:
     return is_bool_object(obj) or is_integer_object(obj) or is_float_object(obj)
 
 
-cdef inline bint is_timedelta64_object(object obj) noexcept nogil:
-    """
-    Cython equivalent of `isinstance(val, np.timedelta64)`
-
-    Parameters
-    ----------
-    val : object
-
-    Returns
-    -------
-    is_timedelta64 : bool
-    """
-    return PyObject_TypeCheck(obj, &PyTimedeltaArrType_Type)
-
-
-cdef inline bint is_datetime64_object(object obj) noexcept nogil:
-    """
-    Cython equivalent of `isinstance(val, np.datetime64)`
-
-    Parameters
-    ----------
-    val : object
-
-    Returns
-    -------
-    is_datetime64 : bool
-    """
-    return PyObject_TypeCheck(obj, &PyDatetimeArrType_Type)
-
-
 cdef inline bint is_array(object val) noexcept:
     """
     Cython equivalent of `isinstance(val, np.ndarray)`