BENCH: add benchmarks for cached Index properties

asv_bench/benchmarks/index_cached_properties.py

@@ -0,0 +1,59 @@
+import pandas as pd
+
+
+class _IndexCache:
+    number = 1
+    repeat = (3, 100, 20)
+
+    def time_values(self):
+        self.idx._values
+
+    def time_shape(self):
+        self.idx.shape
+
+    def time_is_monotonic(self):
+        self.idx.is_monotonic
+
+    def time_is_monotonic_decreasing(self):
+        self.idx.is_monotonic_decreasing
+
+    def time_is_monotonic_increasing(self):
+        self.idx.is_monotonic_increasing
+
+    def time_is_unique(self):
+        self.idx.is_unique
+
+    def time_engine(self):
+        self.idx._engine
+
+    def time_inferred_type(self):
+        self.idx.inferred_type
+
+    def time_is_all_dates(self):
+        self.idx.is_all_dates
+
+
+class MultiIndexCached(_IndexCache):
+    def setup(self):
+        self.idx = pd.MultiIndex.from_product(
+            [pd.date_range("1/1/2000", end="1/1/2001", freq="T"), ["a", "b", "c"]]
+        )
+        self.idx._cache = {}
+
+
+class DatetimeIndex(_IndexCache):
+    def setup(self):
+        self.idx = pd.date_range("1/1/2000", end="1/1/2001", freq="T")
+        self.idx._cache = {}
+
+
+class PeriodIndex(_IndexCache):
+    def setup(self):
+        self.idx = pd.period_range("1/1/2000", end="1/1/2001", freq="T")
+        self.idx._cache = {}
+
+
+class Int64Index(_IndexCache):
+    def setup(self):
+        self.idx = pd.Index(range(100000))
+        self.idx._cache = {}