Don't catch ImportError when trying to unpack module functions

If the ImportError is encountered, it is more informative to raise it rather than hide it, possibly resulting in confusing NameErrors due to the import failure.

IPython/utils/pickleutil.py

@@ -1,281 +1,277 b''
 # encoding: utf-8
 
 """Pickle related utilities. Perhaps this should be called 'can'."""
 
 __docformat__ = "restructuredtext en"
 
 #-------------------------------------------------------------------------------
 #  Copyright (C) 2008-2011  The IPython Development Team
 #
 #  Distributed under the terms of the BSD License.  The full license is in
 #  the file COPYING, distributed as part of this software.
 #-------------------------------------------------------------------------------
 
 #-------------------------------------------------------------------------------
 # Imports
 #-------------------------------------------------------------------------------
 
 import copy
 import logging
 import sys
 from types import FunctionType
 
 try:
     import cPickle as pickle
 except ImportError:
     import pickle
 
 try:
     import numpy
 except:
     numpy = None
 
 import codeutil
 import py3compat
 from importstring import import_item
 
 from IPython.config import Application
 
 if py3compat.PY3:
     buffer = memoryview
 
 #-------------------------------------------------------------------------------
 # Classes
 #-------------------------------------------------------------------------------
 
 
 class CannedObject(object):
     def __init__(self, obj, keys=[]):
         self.keys = keys
         self.obj = copy.copy(obj)
         for key in keys:
             setattr(self.obj, key, can(getattr(obj, key)))
         
         self.buffers = []
 
     def get_object(self, g=None):
         if g is None:
             g = {}
         for key in self.keys:
             setattr(self.obj, key, uncan(getattr(self.obj, key), g))
         return self.obj
     
 
 class Reference(CannedObject):
     """object for wrapping a remote reference by name."""
     def __init__(self, name):
         if not isinstance(name, basestring):
             raise TypeError("illegal name: %r"%name)
         self.name = name
         self.buffers = []
 
     def __repr__(self):
         return "<Reference: %r>"%self.name
 
     def get_object(self, g=None):
         if g is None:
             g = {}
         
         return eval(self.name, g)
 
 
 class CannedFunction(CannedObject):
 
     def __init__(self, f):
         self._check_type(f)
         self.code = f.func_code
         if f.func_defaults:
             self.defaults = [ can(fd) for fd in f.func_defaults ]
         else:
             self.defaults = None
         self.module = f.__module__ or '__main__'
         self.__name__ = f.__name__
         self.buffers = []
 
     def _check_type(self, obj):
         assert isinstance(obj, FunctionType), "Not a function type"
 
     def get_object(self, g=None):
         # try to load function back into its module:
         if not self.module.startswith('__'):
-            try:
                 __import__(self.module)
-            except ImportError:
-                pass
-            else:
                 g = sys.modules[self.module].__dict__
 
         if g is None:
             g = {}
         if self.defaults:
             defaults = tuple(uncan(cfd, g) for cfd in self.defaults)
         else:
             defaults = None
         newFunc = FunctionType(self.code, g, self.__name__, defaults)
         return newFunc
 
 
 class CannedArray(CannedObject):
     def __init__(self, obj):
         self.shape = obj.shape
         self.dtype = obj.dtype.descr if obj.dtype.fields else obj.dtype.str
         if sum(obj.shape) == 0:
             # just pickle it
             self.buffers = [pickle.dumps(obj, -1)]
         else:
             # ensure contiguous
             obj = numpy.ascontiguousarray(obj, dtype=None)
             self.buffers = [buffer(obj)]
     
     def get_object(self, g=None):
         data = self.buffers[0]
         if sum(self.shape) == 0:
             # no shape, we just pickled it
             return pickle.loads(data)
         else:
             return numpy.frombuffer(data, dtype=self.dtype).reshape(self.shape)
 
 
 class CannedBytes(CannedObject):
     wrap = bytes
     def __init__(self, obj):
         self.buffers = [obj]
     
     def get_object(self, g=None):
         data = self.buffers[0]
         return self.wrap(data)
 
 def CannedBuffer(CannedBytes):
     wrap = buffer
 
 #-------------------------------------------------------------------------------
 # Functions
 #-------------------------------------------------------------------------------
 
 def _logger():
     """get the logger for the current Application
     
     the root logger will be used if no Application is running
     """
     if Application.initialized():
         logger = Application.instance().log
     else:
         logger = logging.getLogger()
         if not logger.handlers:
             logging.basicConfig()
     
     return logger
 
 def _import_mapping(mapping, original=None):
     """import any string-keys in a type mapping
     
     """
     log = _logger()
     log.debug("Importing canning map")
     for key,value in mapping.items():
         if isinstance(key, basestring):
             try:
                 cls = import_item(key)
             except Exception:
                 if original and key not in original:
                     # only message on user-added classes
                     log.error("cannning class not importable: %r", key, exc_info=True)
                 mapping.pop(key)
             else:
                 mapping[cls] = mapping.pop(key)
 
 def can(obj):
     """prepare an object for pickling"""
     
     import_needed = False
     
     for cls,canner in can_map.iteritems():
         if isinstance(cls, basestring):
             import_needed = True
             break
         elif isinstance(obj, cls):
             return canner(obj)
     
     if import_needed:
         # perform can_map imports, then try again
         # this will usually only happen once
         _import_mapping(can_map, _original_can_map)
         return can(obj)
     
     return obj
 
 def can_dict(obj):
     """can the *values* of a dict"""
     if isinstance(obj, dict):
         newobj = {}
         for k, v in obj.iteritems():
             newobj[k] = can(v)
         return newobj
     else:
         return obj
 
 def can_sequence(obj):
     """can the elements of a sequence"""
     if isinstance(obj, (list, tuple)):
         t = type(obj)
         return t([can(i) for i in obj])
     else:
         return obj
 
 def uncan(obj, g=None):
     """invert canning"""
     
     import_needed = False
     for cls,uncanner in uncan_map.iteritems():
         if isinstance(cls, basestring):
             import_needed = True
             break
         elif isinstance(obj, cls):
             return uncanner(obj, g)
     
     if import_needed:
         # perform uncan_map imports, then try again
         # this will usually only happen once
         _import_mapping(uncan_map, _original_uncan_map)
         return uncan(obj, g)
     
     return obj
 
 def uncan_dict(obj, g=None):
     if isinstance(obj, dict):
         newobj = {}
         for k, v in obj.iteritems():
             newobj[k] = uncan(v,g)
         return newobj
     else:
         return obj
 
 def uncan_sequence(obj, g=None):
     if isinstance(obj, (list, tuple)):
         t = type(obj)
         return t([uncan(i,g) for i in obj])
     else:
         return obj
 
 
 #-------------------------------------------------------------------------------
 # API dictionaries
 #-------------------------------------------------------------------------------
 
 # These dicts can be extended for custom serialization of new objects
 
 can_map = {
     'IPython.parallel.dependent' : lambda obj: CannedObject(obj, keys=('f','df')),
     'numpy.ndarray' : CannedArray,
     FunctionType : CannedFunction,
     bytes : CannedBytes,
     buffer : CannedBuffer,
 }
 
 uncan_map = {
     CannedObject : lambda obj, g: obj.get_object(g),
 }
 
 # for use in _import_mapping:
 _original_can_map = can_map.copy()
 _original_uncan_map = uncan_map.copy()