PERF: 30% faster is_period_object checks

pandas/_libs/lib.pyx

@@ -75,6 +75,7 @@ from pandas._libs.tslibs.nattype cimport (
 from pandas._libs.tslibs.conversion cimport convert_to_tsobject
 from pandas._libs.tslibs.timedeltas cimport convert_to_timedelta64
 from pandas._libs.tslibs.timezones cimport get_timezone, tz_compare
+from pandas._libs.tslibs.period cimport is_period_object
 
 from pandas._libs.missing cimport (
     checknull,
@@ -185,7 +186,7 @@ def is_scalar(val: object) -> bool:
 
     # Note: PyNumber_Check check includes Decimal, Fraction, numbers.Number
     return (PyNumber_Check(val)
-            or util.is_period_object(val)
+            or is_period_object(val)
             or is_interval(val)
             or util.is_offset_object(val))
 
@@ -942,7 +943,7 @@ def is_period(val: object) -> bool:
     -------
     bool
     """
-    return util.is_period_object(val)
+    return is_period_object(val)
 
 
 def is_list_like(obj: object, allow_sets: bool = True) -> bool:
@@ -1417,7 +1418,7 @@ def infer_dtype(value: object, skipna: bool = True) -> str:
         if is_bytes_array(values, skipna=skipna):
             return "bytes"
 
-    elif util.is_period_object(val):
+    elif is_period_object(val):
         if is_period_array(values):
             return "period"
 
@@ -1849,7 +1850,7 @@ cpdef bint is_time_array(ndarray values, bint skipna=False):
 
 cdef class PeriodValidator(TemporalValidator):
     cdef inline bint is_value_typed(self, object value) except -1:
-        return util.is_period_object(value)
+        return is_period_object(value)
 
     cdef inline bint is_valid_null(self, object value) except -1:
         return checknull_with_nat(value)

pandas/_libs/tslibs/period.pxd

@@ -0,0 +1 @@
+cdef bint is_period_object(object obj)

pandas/_libs/tslibs/period.pyx

@@ -36,7 +36,6 @@ cdef extern from "src/datetime/np_datetime.h":
                                            npy_datetimestruct *d) nogil
 
 cimport pandas._libs.tslibs.util as util
-from pandas._libs.tslibs.util cimport is_period_object
 
 from pandas._libs.tslibs.timestamps import Timestamp
 from pandas._libs.tslibs.timezones cimport is_utc, is_tzlocal, get_dst_info
@@ -2467,6 +2466,15 @@ class Period(_Period):
         return cls._from_ordinal(ordinal, freq)
 
 
+cdef bint is_period_object(object obj):
+    """
+    Cython-optimized equivalent of isinstance(obj, Period)
+    """
+    # Note: this is significantly faster than the implementation in tslibs.util,
+    #  only use the util version when necessary to prevent circular imports.
+    return isinstance(obj, _Period)
+
+
 cdef int64_t _ordinal_from_fields(int year, int month, quarter, int day,
                                   int hour, int minute, int second, freq):
     base, mult = get_freq_code(freq)