##// END OF EJS Templates
use CFRunLoop directly in `ipython kernel --pylab osx`...
use CFRunLoop directly in `ipython kernel --pylab osx` via matplotlib.backend_macosx.TimerMac, rather than Tk Fallback on Tk if matplotlib is < 1.1.0, which introduces the necessary Timer. This means that it still won't work on current EPD, which has X11-linked libtk and matplotlib 1.0.1, but at least it will display a warning explaining why. also remove caveat in docs that qtconsole doesn't work with native MacOSX, since it does on normal (non-EPD) installs. So this will work in more places, but still not in most common failure case (stock EPD) described in #640.

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newserialized.py
177 lines | 5.0 KiB | text/x-python | PythonLexer
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r3539 # encoding: utf-8
# -*- test-case-name: IPython.kernel.test.test_newserialized -*-
"""Refactored serialization classes and interfaces."""
__docformat__ = "restructuredtext en"
# Tell nose to skip this module
__test__ = {}
#-------------------------------------------------------------------------------
# Copyright (C) 2008 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
#-------------------------------------------------------------------------------
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r4155 import sys
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r3539 import cPickle as pickle
try:
import numpy
except ImportError:
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r4155 numpy = None
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r3539
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r3557 class SerializationError(Exception):
pass
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r3539
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r4155 if sys.version_info[0] >= 3:
buffer = memoryview
py3k = True
else:
py3k = False
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r4571 if sys.version_info[:2] <= (2,6):
memoryview = buffer
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r4155
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r3539 #-----------------------------------------------------------------------------
# Classes and functions
#-----------------------------------------------------------------------------
class ISerialized:
def getData():
""""""
def getDataSize(units=10.0**6):
""""""
def getTypeDescriptor():
""""""
def getMetadata():
""""""
class IUnSerialized:
def getObject():
""""""
class Serialized(object):
# implements(ISerialized)
def __init__(self, data, typeDescriptor, metadata={}):
self.data = data
self.typeDescriptor = typeDescriptor
self.metadata = metadata
def getData(self):
return self.data
def getDataSize(self, units=10.0**6):
return len(self.data)/units
def getTypeDescriptor(self):
return self.typeDescriptor
def getMetadata(self):
return self.metadata
class UnSerialized(object):
# implements(IUnSerialized)
def __init__(self, obj):
self.obj = obj
def getObject(self):
return self.obj
class SerializeIt(object):
# implements(ISerialized)
def __init__(self, unSerialized):
self.data = None
self.obj = unSerialized.getObject()
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r4155 if numpy is not None and isinstance(self.obj, numpy.ndarray):
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r4571 if len(self.obj.shape) == 0: # length 0 arrays are just pickled
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r3648 self.typeDescriptor = 'pickle'
self.metadata = {}
else:
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r3539 self.obj = numpy.ascontiguousarray(self.obj, dtype=None)
self.typeDescriptor = 'ndarray'
self.metadata = {'shape':self.obj.shape,
'dtype':self.obj.dtype.str}
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r4155 elif isinstance(self.obj, bytes):
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r3539 self.typeDescriptor = 'bytes'
self.metadata = {}
elif isinstance(self.obj, buffer):
self.typeDescriptor = 'buffer'
self.metadata = {}
else:
self.typeDescriptor = 'pickle'
self.metadata = {}
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r3642 self._generateData()
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r3539
def _generateData(self):
if self.typeDescriptor == 'ndarray':
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r4571 self.data = buffer(self.obj)
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r3539 elif self.typeDescriptor in ('bytes', 'buffer'):
self.data = self.obj
elif self.typeDescriptor == 'pickle':
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r3545 self.data = pickle.dumps(self.obj, -1)
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r3539 else:
raise SerializationError("Really wierd serialization error.")
del self.obj
def getData(self):
return self.data
def getDataSize(self, units=10.0**6):
return 1.0*len(self.data)/units
def getTypeDescriptor(self):
return self.typeDescriptor
def getMetadata(self):
return self.metadata
class UnSerializeIt(UnSerialized):
# implements(IUnSerialized)
def __init__(self, serialized):
self.serialized = serialized
def getObject(self):
typeDescriptor = self.serialized.getTypeDescriptor()
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r4155 if numpy is not None and typeDescriptor == 'ndarray':
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r3642 buf = self.serialized.getData()
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r4571 if isinstance(buf, (bytes, buffer, memoryview)):
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r3642 result = numpy.frombuffer(buf, dtype = self.serialized.metadata['dtype'])
else:
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r4571 raise TypeError("Expected bytes or buffer/memoryview, but got %r"%type(buf))
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r3539 result.shape = self.serialized.metadata['shape']
elif typeDescriptor == 'pickle':
result = pickle.loads(self.serialized.getData())
elif typeDescriptor in ('bytes', 'buffer'):
result = self.serialized.getData()
else:
raise SerializationError("Really wierd serialization error.")
return result
def serialize(obj):
return SerializeIt(UnSerialized(obj))
def unserialize(serialized):
return UnSerializeIt(serialized).getObject()