CLN: use idiomatic pandas_dtypes in pandas/dtypes/common.py

Author: jreback

asv_bench/benchmarks/dtypes.py

@@ -0,0 +1,44 @@
+from pandas.api.types import pandas_dtype
+
+import numpy as np
+from .pandas_vb_common import (
+    numeric_dtypes, datetime_dtypes, string_dtypes, extension_dtypes)
+
+
+_numpy_dtypes = list(map(np.dtype, (numeric_dtypes +
+                                    datetime_dtypes +
+                                    string_dtypes)))
+_dtypes = _numpy_dtypes + extension_dtypes
+
+
+class Dtypes(object):
+    params = (_dtypes +
+              list(map(lambda dt: dt.name, _dtypes)))
+    param_names = ['dtype']
+
+    def time_pandas_dtype(self, dtype):
+        pandas_dtype(dtype)
+
+
+class DtypesInvalid(object):
+    params = ['foo', 1, ['foo'] * 1000, np.array(['foo'] * 1000)]
+    param_names = ['dtype']
+
+    def time_pandas_dtype_invalid(self, dtype):
+        try:
+            pandas_dtype(dtype)
+        except TypeError:
+            pass
+
+    param_names = ['dtype']
+    params = ['scalar-string', 'scalar-int', 'list-string', 'array-string']
+    data_dict = {'scalar-string': 'foo',
+                 'scalar-int': 1,
+                 'list-string': ['foo'] * 1000,
+                 'array-string': np.array(['foo'] * 1000)}
+
+    def setup(self, dtype):
+        self.data = self.data_dict[dtype]
+
+
+from .pandas_vb_common import setup  # noqa: F401

asv_bench/benchmarks/pandas_vb_common.py

@@ -2,6 +2,7 @@
 from importlib import import_module
 
 import numpy as np
+import pandas as pd
 
 # Compatibility import for lib
 for imp in ['pandas._libs.lib', 'pandas.lib']:
@@ -14,6 +15,15 @@
 numeric_dtypes = [np.int64, np.int32, np.uint32, np.uint64, np.float32,
                   np.float64, np.int16, np.int8, np.uint16, np.uint8]
 datetime_dtypes = [np.datetime64, np.timedelta64]
+string_dtypes = [np.object]
+extension_dtypes = [pd.Int8Dtype, pd.Int16Dtype,
+                    pd.Int32Dtype, pd.Int64Dtype,
+                    pd.UInt8Dtype, pd.UInt16Dtype,
+                    pd.UInt32Dtype, pd.UInt64Dtype,
+                    pd.CategoricalDtype,
+                    pd.IntervalDtype,
+                    pd.DatetimeTZDtype('ns', 'UTC'),
+                    pd.PeriodDtype('D')]
 
 
 def setup(*args, **kwargs):