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merge functionality in io and openpy relating to encoding...
merge functionality in io and openpy relating to encoding New functions were introduced in openpy to deal with encoding in python files. This commit removes redundant code from io and moves source_to_unicode to openpy.

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pickleutil.py
281 lines | 7.6 KiB | text/x-python | PythonLexer
# 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()