WIP: deprecate internal use of box

Author: Chris Bertinato

pandas/core/dtypes/cast.py

@@ -794,10 +794,10 @@ def soft_convert_objects(values, datetime=True, numeric=True, timedelta=True,
         # Immediate return if coerce
         if datetime:
             from pandas import to_datetime
-            return to_datetime(values, errors='coerce', box=False)
+            return to_datetime(values, errors='coerce').to_numpy()
         elif timedelta:
             from pandas import to_timedelta
-            return to_timedelta(values, errors='coerce', box=False)
+            return to_timedelta(values, errors='coerce').to_numpy()
         elif numeric:
             from pandas import to_numeric
             return to_numeric(values, errors='coerce')

pandas/core/indexes/datetimelike.py

@@ -300,7 +300,12 @@ def asobject(self):
         return self.astype(object)
 
     def _convert_tolerance(self, tolerance, target):
-        tolerance = np.asarray(to_timedelta(tolerance, box=False))
+        tolerance = to_timedelta(tolerance)
+        if isinstance(tolerance, ABCIndexClass):
+            tolerance = tolerance.to_numpy()
+        else:
+            tolerance = np.asarray(tolerance.to_timedelta64())
+
         if target.size != tolerance.size and tolerance.size > 1:
             raise ValueError('list-like tolerance size must match '
                              'target index size')

pandas/io/parsers.py

@@ -14,10 +14,12 @@
 
 import numpy as np
 
+from pandas import DatetimeIndex
+
 import pandas._libs.lib as lib
 import pandas._libs.ops as libops
 import pandas._libs.parsers as parsers
-from pandas._libs.tslibs import parsing
+from pandas._libs.tslibs import parsing, Timestamp
 import pandas.compat as compat
 from pandas.compat import (
     PY3, StringIO, lrange, lzip, map, range, string_types, u, zip)
@@ -3139,17 +3141,28 @@ def _get_lines(self, rows=None):
 def _make_date_converter(date_parser=None, dayfirst=False,
                          infer_datetime_format=False):
     def converter(*date_cols):
+        from pandas.core.dtypes.common import is_datetime64_dtype
         if date_parser is None:
             strs = _concat_date_cols(date_cols)
 
             try:
-                return tools.to_datetime(
+                dti = tools.to_datetime(
                     ensure_object(strs),
                     utc=None,
                     dayfirst=dayfirst,
                     errors='ignore',
                     infer_datetime_format=infer_datetime_format
                 )
+
+                if isinstance(dti, DatetimeIndex):
+                    dti = dti.to_pydatetime()
+                elif is_datetime64_dtype(dti):
+                    dti = np.array([Timestamp(ts).to_pydatetime()
+                                    for ts in dti])
+                else:
+                    dti = dti.to_numpy()
+
+                return dti
             except ValueError:
                 return tools.to_datetime(
                     parsing.try_parse_dates(strs, dayfirst=dayfirst))