2to3: Apply `imports` fixer.

The `imports` fixer deals with the standard packages that have been
renamed, removed, or methods that have moved.

cPickle      -- removed, use pickle
commands     -- removed, getoutput, getstatusoutput moved to subprocess
urlparse     -- removed, urlparse moved to urllib.parse
cStringIO    -- removed, use StringIO or io.StringIO
copy_reg     -- renamed copyreg
_winreg      -- renamed winreg
ConfigParser -- renamed configparser
__builtin__  -- renamed builtins

In the case of `cPickle`, it is imported as `pickle` when python < 3 and
performance may be a consideration, but otherwise plain old `pickle` is
used.

Dealing with `StringIO` is a bit tricky. There is an `io.StringIO`
function in the `io` module, available since Python 2.6, but it expects
unicode whereas `StringIO.StringIO` expects ascii. The Python 3
equivalent is then `io.BytesIO`. What I have done here is used BytesIO
for anything that is emulating a file for testing purposes. That is more
explicit than using a redefined StringIO as was done before we dropped
support for Python 2.4 and 2.5.

Closes #3180.

1 files changed, 7 insertions, 4 deletions

diff --git a/numpy/lib/format.py b/numpy/lib/format.py
index 21b0607e7..dedfabfd2 100644
--- a/numpy/lib/format.py
+++ b/numpy/lib/format.py
@@ -136,13 +136,16 @@ alternatives, is described fully in the "npy-format" NEP.
 """
 from __future__ import division, absolute_import
 
-import cPickle
-
 import numpy
 import sys
 from numpy.lib.utils import safe_eval
 from numpy.compat import asbytes, isfileobj
 
+if sys.version_info[0] >= 3:
+    import pickle
+else:
+    import cPickle as pickle
+
 MAGIC_PREFIX = asbytes('\x93NUMPY')
 MAGIC_LEN = len(MAGIC_PREFIX) + 2
 
@@ -399,7 +402,7 @@ def write_array(fp, array, version=(1,0)):
     if array.dtype.hasobject:
         # We contain Python objects so we cannot write out the data directly.
         # Instead, we will pickle it out with version 2 of the pickle protocol.
-        cPickle.dump(array, fp, protocol=2)
+        pickle.dump(array, fp, protocol=2)
     elif array.flags.f_contiguous and not array.flags.c_contiguous:
         if isfileobj(fp):
             array.T.tofile(fp)
@@ -447,7 +450,7 @@ def read_array(fp):
     # Now read the actual data.
     if dtype.hasobject:
         # The array contained Python objects. We need to unpickle the data.
-        array = cPickle.load(fp)
+        array = pickle.load(fp)
     else:
         if isfileobj(fp):
             # We can use the fast fromfile() function.