add utils.pickleutil.use_dill

enables dill extended serialization support

IPython/utils/pickleutil.py

@@ -1,352 +1,382 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
 
 from . import codeutil  # This registers a hook when it's imported
 from . import py3compat
 from .importstring import import_item
 from .py3compat import string_types, iteritems
 
 from IPython.config import Application
 
 if py3compat.PY3:
     buffer = memoryview
     class_type = type
 else:
     from types import ClassType
     class_type = (type, ClassType)
 
 #-------------------------------------------------------------------------------
+# Functions
+#-------------------------------------------------------------------------------
+
+
+def use_dill():
+    """use dill to expand serialization support
+    
+    adds support for object methods and closures to serialization.
+    """
+    # import dill causes most of the magic
+    import dill
+    
+    # dill doesn't work with cPickle,
+    # tell the two relevant modules to use plain pickle
+    
+    global pickle
+    import pickle
+
+    try:
+        from IPython.kernel.zmq import serialize
+    except ImportError:
+        pass
+    else:
+        serialize.pickle = pickle
+    
+    # disable special function handling, let dill take care of it
+    can_map.pop(FunctionType, None)
+
+
+#-------------------------------------------------------------------------------
 # Classes
 #-------------------------------------------------------------------------------
 
 
 class CannedObject(object):
     def __init__(self, obj, keys=[], hook=None):
         """can an object for safe pickling
         
         Parameters
         ==========
         
         obj:
             The object to be canned
         keys: list (optional)
             list of attribute names that will be explicitly canned / uncanned
         hook: callable (optional)
             An optional extra callable,
             which can do additional processing of the uncanned object.
         
         large data may be offloaded into the buffers list,
         used for zero-copy transfers.
         """
         self.keys = keys
         self.obj = copy.copy(obj)
         self.hook = can(hook)
         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 = {}
         obj = self.obj
         for key in self.keys:
             setattr(obj, key, uncan(getattr(obj, key), g))
         
         if self.hook:
             self.hook = uncan(self.hook, g)
             self.hook(obj, g)
         return self.obj
     
 
 class Reference(CannedObject):
     """object for wrapping a remote reference by name."""
     def __init__(self, name):
         if not isinstance(name, string_types):
             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.__code__
         if f.__defaults__:
             self.defaults = [ can(fd) for fd in f.__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('__'):
             __import__(self.module)
             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 CannedClass(CannedObject):
 
     def __init__(self, cls):
         self._check_type(cls)
         self.name = cls.__name__
         self.old_style = not isinstance(cls, type)
         self._canned_dict = {}
         for k,v in cls.__dict__.items():
             if k not in ('__weakref__', '__dict__'):
                 self._canned_dict[k] = can(v)
         if self.old_style:
             mro = []
         else:
             mro = cls.mro()
         
         self.parents = [ can(c) for c in mro[1:] ]
         self.buffers = []
 
     def _check_type(self, obj):
         assert isinstance(obj, class_type), "Not a class type"
 
     def get_object(self, g=None):
         parents = tuple(uncan(p, g) for p in self.parents)
         return type(self.name, parents, uncan_dict(self._canned_dict, g=g))
 
 class CannedArray(CannedObject):
     def __init__(self, obj):
         from numpy import ascontiguousarray
         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 = ascontiguousarray(obj, dtype=None)
             self.buffers = [buffer(obj)]
     
     def get_object(self, g=None):
         from numpy import frombuffer
         data = self.buffers[0]
         if sum(self.shape) == 0:
             # no shape, we just pickled it
             return pickle.loads(data)
         else:
             return 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 list(mapping.items()):
         if isinstance(key, string_types):
             try:
                 cls = import_item(key)
             except Exception:
                 if original and key not in original:
                     # only message on user-added classes
                     log.error("canning class not importable: %r", key, exc_info=True)
                 mapping.pop(key)
             else:
                 mapping[cls] = mapping.pop(key)
 
 def istype(obj, check):
     """like isinstance(obj, check), but strict
     
     This won't catch subclasses.
     """
     if isinstance(check, tuple):
         for cls in check:
             if type(obj) is cls:
                 return True
         return False
     else:
         return type(obj) is check
 
 def can(obj):
     """prepare an object for pickling"""
     
     import_needed = False
     
     for cls,canner in iteritems(can_map):
         if isinstance(cls, string_types):
             import_needed = True
             break
         elif istype(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_class(obj):
     if isinstance(obj, class_type) and obj.__module__ == '__main__':
         return CannedClass(obj)
     else:
         return obj
 
 def can_dict(obj):
     """can the *values* of a dict"""
     if istype(obj, dict):
         newobj = {}
         for k, v in iteritems(obj):
             newobj[k] = can(v)
         return newobj
     else:
         return obj
 
 sequence_types = (list, tuple, set)
 
 def can_sequence(obj):
     """can the elements of a sequence"""
     if istype(obj, sequence_types):
         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 iteritems(uncan_map):
         if isinstance(cls, string_types):
             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 istype(obj, dict):
         newobj = {}
         for k, v in iteritems(obj):
             newobj[k] = uncan(v,g)
         return newobj
     else:
         return obj
 
 def uncan_sequence(obj, g=None):
     if istype(obj, sequence_types):
         t = type(obj)
         return t([uncan(i,g) for i in obj])
     else:
         return obj
 
 def _uncan_dependent_hook(dep, g=None):
     dep.check_dependency()
     
 def can_dependent(obj):
     return CannedObject(obj, keys=('f', 'df'), hook=_uncan_dependent_hook)
 
 #-------------------------------------------------------------------------------
 # API dictionaries
 #-------------------------------------------------------------------------------
 
 # These dicts can be extended for custom serialization of new objects
 
 can_map = {
     'IPython.parallel.dependent' : can_dependent,
     'numpy.ndarray' : CannedArray,
     FunctionType : CannedFunction,
     bytes : CannedBytes,
     buffer : CannedBuffer,
     class_type : can_class,
 }
 
 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()