REF: simplify PeriodIndex.get_loc

pandas/_libs/index.pyx

@@ -17,6 +17,7 @@ cnp.import_array()
 
 cimport pandas._libs.util as util
 
+from pandas._libs.tslibs import Period
 from pandas._libs.tslibs.nattype cimport c_NaT as NaT
 from pandas._libs.tslibs.c_timestamp cimport _Timestamp
 
@@ -496,6 +497,28 @@ cdef class TimedeltaEngine(DatetimeEngine):
 
 cdef class PeriodEngine(Int64Engine):
 
+    cdef int64_t _unbox_scalar(self, scalar) except? -1:
+        if scalar is NaT:
+            return scalar.value
+        if isinstance(scalar, Period):
+            # NB: we assume that we have the correct freq here.
+            # TODO: potential optimize by checking for _Period?
+            return scalar.ordinal
+        raise TypeError(scalar)
+
+    cpdef get_loc(self, object val):
+        # NB: the caller is responsible for ensuring that we are called
+        #  with either a Period or NaT
+        cdef:
+            int64_t conv
+
+        try:
+            conv = self._unbox_scalar(val)
+        except TypeError:
+            raise KeyError(val)
+
+        return Int64Engine.get_loc(self, conv)
+
     cdef _get_index_values(self):
         return super(PeriodEngine, self).vgetter().view("i8")
 

pandas/core/indexes/period.py

@@ -5,7 +5,7 @@
 import numpy as np
 
 from pandas._libs import index as libindex
-from pandas._libs.tslibs import NaT, frequencies as libfrequencies, resolution
+from pandas._libs.tslibs import frequencies as libfrequencies, resolution
 from pandas._libs.tslibs.parsing import parse_time_string
 from pandas._libs.tslibs.period import Period
 from pandas.util._decorators import Appender, cache_readonly
@@ -468,6 +468,10 @@ def get_indexer(self, target, method=None, limit=None, tolerance=None):
 
         if tolerance is not None:
             tolerance = self._convert_tolerance(tolerance, target)
+            if self_index is not self:
+                # convert tolerance to i8
+                tolerance = self._maybe_convert_timedelta(tolerance)
+
         return Index.get_indexer(self_index, target, method, limit, tolerance)
 
     @Appender(_index_shared_docs["get_indexer_non_unique"] % _index_doc_kwargs)
@@ -504,6 +508,7 @@ def get_loc(self, key, method=None, tolerance=None):
         TypeError
             If key is listlike or otherwise not hashable.
         """
+        orig_key = key
 
         if not is_scalar(key):
             raise InvalidIndexError(key)
@@ -545,20 +550,12 @@ def get_loc(self, key, method=None, tolerance=None):
             key = Period(key, freq=self.freq)
         except ValueError:
             # we cannot construct the Period
-            raise KeyError(key)
+            raise KeyError(orig_key)
 
-        ordinal = key.ordinal if key is not NaT else key.value
         try:
-            return self._engine.get_loc(ordinal)
+            return Index.get_loc(self, key, method, tolerance)
         except KeyError:
-
-            try:
-                if tolerance is not None:
-                    tolerance = self._convert_tolerance(tolerance, np.asarray(key))
-                return self._int64index.get_loc(ordinal, method, tolerance)
-
-            except KeyError:
-                raise KeyError(key)
+            raise KeyError(orig_key)
 
     def _maybe_cast_slice_bound(self, label, side: str, kind: str):
         """
@@ -646,12 +643,6 @@ def _get_string_slice(self, key: str, use_lhs: bool = True, use_rhs: bool = True
             # try to find a the dates
             return (lhs_mask & rhs_mask).nonzero()[0]
 
-    def _convert_tolerance(self, tolerance, target):
-        tolerance = DatetimeIndexOpsMixin._convert_tolerance(self, tolerance, target)
-        if target.size != tolerance.size and tolerance.size > 1:
-            raise ValueError("list-like tolerance size must match target index size")
-        return self._maybe_convert_timedelta(tolerance)
-
     def insert(self, loc, item):
         if not isinstance(item, Period) or self.freq != item.freq:
             return self.astype(object).insert(loc, item)

pandas/tests/indexing/test_indexing.py

@@ -153,7 +153,6 @@ def test_setitem_ndarray_3d(self, index, obj, idxr, idxr_id):
                     "floating",
                     "string",
                     "datetime64",
-                    "period",
                     "timedelta64",
                     "boolean",
                     "categorical",