##// END OF EJS Templates
don't automatically add jobarray or queue lines to user template...
don't automatically add jobarray or queue lines to user template In parallel launchers, the queue and jobarray lines should not be added except in the default templates. user-templates must be fully specified. This prevents conflicts between PBS versions, which may not support jobarrays, etc. These lines are now only added to the *default* templates.

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newserialized.py
179 lines | 5.1 KiB | text/x-python | PythonLexer
# 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
#-------------------------------------------------------------------------------
import sys
import cPickle as pickle
try:
import numpy
except ImportError:
numpy = None
class SerializationError(Exception):
pass
if sys.version_info[0] >= 3:
buffer = memoryview
py3k = True
else:
py3k = False
#-----------------------------------------------------------------------------
# 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()
if numpy is not None and isinstance(self.obj, numpy.ndarray):
if py3k or len(self.obj.shape) == 0: # length 0 arrays are just pickled
# FIXME:
# also use pickle for numpy arrays on py3k, since
# pyzmq doesn't rebuild from memoryviews properly
self.typeDescriptor = 'pickle'
self.metadata = {}
else:
self.obj = numpy.ascontiguousarray(self.obj, dtype=None)
self.typeDescriptor = 'ndarray'
self.metadata = {'shape':self.obj.shape,
'dtype':self.obj.dtype.str}
elif isinstance(self.obj, bytes):
self.typeDescriptor = 'bytes'
self.metadata = {}
elif isinstance(self.obj, buffer):
self.typeDescriptor = 'buffer'
self.metadata = {}
else:
self.typeDescriptor = 'pickle'
self.metadata = {}
self._generateData()
def _generateData(self):
if self.typeDescriptor == 'ndarray':
self.data = numpy.getbuffer(self.obj)
elif self.typeDescriptor in ('bytes', 'buffer'):
self.data = self.obj
elif self.typeDescriptor == 'pickle':
self.data = pickle.dumps(self.obj, -1)
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()
if numpy is not None and typeDescriptor == 'ndarray':
buf = self.serialized.getData()
if isinstance(buf, (bytes, buffer)):
result = numpy.frombuffer(buf, dtype = self.serialized.metadata['dtype'])
else:
# memoryview
result = numpy.array(buf, dtype = self.serialized.metadata['dtype'])
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()