CLN: remove _pickle_array, _unpkckle_array from common.py

Author: jreback

pandas/core/common.py

@@ -8,15 +8,13 @@
 from datetime import datetime, timedelta
 from functools import partial
 
-from numpy.lib.format import read_array, write_array
 import numpy as np
-
 import pandas as pd
 import pandas.algos as algos
 import pandas.lib as lib
 import pandas.tslib as tslib
 from pandas import compat
-from pandas.compat import (BytesIO, range, long, u, zip, map, string_types,
+from pandas.compat import (range, long, u, zip, map, string_types,
                            iteritems)
 from pandas.types import api as gt
 from pandas.types.api import *  # noqa
@@ -378,27 +376,6 @@ def flatten(l):
             yield el
 
 
-def _pickle_array(arr):
-    arr = arr.view(np.ndarray)
-
-    buf = BytesIO()
-    write_array(buf, arr)
-
-    return buf.getvalue()
-
-
-def _unpickle_array(bytes):
-    arr = read_array(BytesIO(bytes))
-
-    # All datetimes should be stored as M8[ns].  When unpickling with
-    # numpy1.6, it will read these as M8[us].  So this ensures all
-    # datetime64 types are read as MS[ns]
-    if is_datetime64_dtype(arr):
-        arr = arr.view(_NS_DTYPE)
-
-    return arr
-
-
 def _coerce_indexer_dtype(indexer, categories):
     """ coerce the indexer input array to the smallest dtype possible """
     l = len(categories)

pandas/io/pickle.py

@@ -1,4 +1,9 @@
-from pandas.compat import cPickle as pkl, pickle_compat as pc, PY3
+""" pickle compat """
+
+import numpy as np
+from numpy.lib.format import read_array, write_array
+from pandas.compat import BytesIO, cPickle as pkl, pickle_compat as pc, PY3
+import pandas.core.common as com
 
 
 def to_pickle(obj, path):
@@ -62,3 +67,26 @@ def try_read(path, encoding=None):
         if PY3:
             return try_read(path, encoding='latin1')
         raise
+
+# compat with sparse pickle / unpickle
+
+
+def _pickle_array(arr):
+    arr = arr.view(np.ndarray)
+
+    buf = BytesIO()
+    write_array(buf, arr)
+
+    return buf.getvalue()
+
+
+def _unpickle_array(bytes):
+    arr = read_array(BytesIO(bytes))
+
+    # All datetimes should be stored as M8[ns].  When unpickling with
+    # numpy1.6, it will read these as M8[us].  So this ensures all
+    # datetime64 types are read as MS[ns]
+    if com.is_datetime64_dtype(arr):
+        arr = arr.view(com._NS_DTYPE)
+
+    return arr

pandas/sparse/frame.py

@@ -10,7 +10,7 @@
 from pandas import compat
 import numpy as np
 
-from pandas.core.common import isnull, _unpickle_array, _try_sort
+from pandas.core.common import isnull, _try_sort
 from pandas.core.index import Index, MultiIndex, _ensure_index
 from pandas.core.series import Series
 from pandas.core.frame import (DataFrame, extract_index, _prep_ndarray,
@@ -217,11 +217,13 @@ def _unpickle_sparse_frame_compat(self, state):
         series, cols, idx, fv, kind = state
 
         if not isinstance(cols, Index):  # pragma: no cover
+            from pandas.io.pickle import _unpickle_array
             columns = _unpickle_array(cols)
         else:
             columns = cols
 
         if not isinstance(idx, Index):  # pragma: no cover
+            from pandas.io.pickle import _unpickle_array
             index = _unpickle_array(idx)
         else:
             index = idx

pandas/sparse/panel.py

@@ -250,19 +250,21 @@ def __delitem__(self, key):
 
     def __getstate__(self):
         # pickling
-        return (self._frames, com._pickle_array(self.items),
-                com._pickle_array(self.major_axis),
-                com._pickle_array(self.minor_axis), self.default_fill_value,
+        from pandas.io.pickle import _pickle_array
+        return (self._frames, _pickle_array(self.items),
+                _pickle_array(self.major_axis),
+                _pickle_array(self.minor_axis), self.default_fill_value,
                 self.default_kind)
 
     def __setstate__(self, state):
         frames, items, major, minor, fv, kind = state
 
+        from pandas.io.pickle import _unpickle_array
         self.default_fill_value = fv
         self.default_kind = kind
-        self._items = _ensure_index(com._unpickle_array(items))
-        self._major_axis = _ensure_index(com._unpickle_array(major))
-        self._minor_axis = _ensure_index(com._unpickle_array(minor))
+        self._items = _ensure_index(_unpickle_array(items))
+        self._major_axis = _ensure_index(_unpickle_array(major))
+        self._minor_axis = _ensure_index(_unpickle_array(minor))
         self._frames = frames
 
     def copy(self, deep=True):