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"""Remote Functions and decorators for Views.
Authors:
* Brian Granger
* Min RK
"""
#-----------------------------------------------------------------------------
# Copyright (C) 2010-2011 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
#-----------------------------------------------------------------------------
from __future__ import division
import sys
import warnings
from IPython.testing.skipdoctest import skip_doctest
from . import map as Map
from .asyncresult import AsyncMapResult
#-----------------------------------------------------------------------------
# Functions and Decorators
#-----------------------------------------------------------------------------
@skip_doctest
def remote(view, block=None, **flags):
"""Turn a function into a remote function.
This method can be used for map:
In [1]: @remote(view,block=True)
...: def func(a):
...: pass
"""
def remote_function(f):
return RemoteFunction(view, f, block=block, **flags)
return remote_function
@skip_doctest
def parallel(view, dist='b', block=None, ordered=True, **flags):
"""Turn a function into a parallel remote function.
This method can be used for map:
In [1]: @parallel(view, block=True)
...: def func(a):
...: pass
"""
def parallel_function(f):
return ParallelFunction(view, f, dist=dist, block=block, ordered=ordered, **flags)
return parallel_function
def getname(f):
"""Get the name of an object.
For use in case of callables that are not functions, and
thus may not have __name__ defined.
Order: f.__name__ > f.name > str(f)
"""
try:
return f.__name__
except:
pass
try:
return f.name
except:
pass
return str(f)
#--------------------------------------------------------------------------
# Classes
#--------------------------------------------------------------------------
class RemoteFunction(object):
"""Turn an existing function into a remote function.
Parameters
----------
view : View instance
The view to be used for execution
f : callable
The function to be wrapped into a remote function
block : bool [default: None]
Whether to wait for results or not. The default behavior is
to use the current `block` attribute of `view`
**flags : remaining kwargs are passed to View.temp_flags
"""
view = None # the remote connection
func = None # the wrapped function
block = None # whether to block
flags = None # dict of extra kwargs for temp_flags
def __init__(self, view, f, block=None, **flags):
self.view = view
self.func = f
self.block=block
self.flags=flags
def __call__(self, *args, **kwargs):
block = self.view.block if self.block is None else self.block
with self.view.temp_flags(block=block, **self.flags):
return self.view.apply(self.func, *args, **kwargs)
class ParallelFunction(RemoteFunction):
"""Class for mapping a function to sequences.
This will distribute the sequences according the a mapper, and call
the function on each sub-sequence. If called via map, then the function
will be called once on each element, rather that each sub-sequence.
Parameters
----------
view : View instance
The view to be used for execution
f : callable
The function to be wrapped into a remote function
dist : str [default: 'b']
The key for which mapObject to use to distribute sequences
options are:
* 'b' : use contiguous chunks in order
* 'r' : use round-robin striping
block : bool [default: None]
Whether to wait for results or not. The default behavior is
to use the current `block` attribute of `view`
chunksize : int or None
The size of chunk to use when breaking up sequences in a load-balanced manner
ordered : bool [default: True]
Whether
**flags : remaining kwargs are passed to View.temp_flags
"""
chunksize=None
ordered=None
mapObject=None
def __init__(self, view, f, dist='b', block=None, chunksize=None, ordered=True, **flags):
super(ParallelFunction, self).__init__(view, f, block=block, **flags)
self.chunksize = chunksize
self.ordered = ordered
mapClass = Map.dists[dist]
self.mapObject = mapClass()
def __call__(self, *sequences):
client = self.view.client
# check that the length of sequences match
len_0 = len(sequences[0])
for s in sequences:
if len(s)!=len_0:
msg = 'all sequences must have equal length, but %i!=%i'%(len_0,len(s))
raise ValueError(msg)
balanced = 'Balanced' in self.view.__class__.__name__
if balanced:
if self.chunksize:
nparts = len_0//self.chunksize + int(len_0%self.chunksize > 0)
else:
nparts = len_0
targets = [None]*nparts
else:
if self.chunksize:
warnings.warn("`chunksize` is ignored unless load balancing", UserWarning)
# multiplexed:
targets = self.view.targets
# 'all' is lazily evaluated at execution time, which is now:
if targets == 'all':
targets = client._build_targets(targets)[1]
elif isinstance(targets, int):
# single-engine view, targets must be iterable
targets = [targets]
nparts = len(targets)
msg_ids = []
for index, t in enumerate(targets):
args = []
for seq in sequences:
part = self.mapObject.getPartition(seq, index, nparts)
if len(part) == 0:
continue
else:
args.append(part)
if not args:
continue
# print (args)
if hasattr(self, '_map'):
if sys.version_info[0] >= 3:
f = lambda f, *sequences: list(map(f, *sequences))
else:
f = map
args = [self.func]+args
else:
f=self.func
view = self.view if balanced else client[t]
with view.temp_flags(block=False, **self.flags):
ar = view.apply(f, *args)
msg_ids.append(ar.msg_ids[0])
r = AsyncMapResult(self.view.client, msg_ids, self.mapObject,
fname=getname(self.func),
ordered=self.ordered
)
if self.block:
try:
return r.get()
except KeyboardInterrupt:
return r
else:
return r
def map(self, *sequences):
"""call a function on each element of a sequence remotely.
This should behave very much like the builtin map, but return an AsyncMapResult
if self.block is False.
"""
# set _map as a flag for use inside self.__call__
self._map = True
try:
ret = self.__call__(*sequences)
finally:
del self._map
return ret
__all__ = ['remote', 'parallel', 'RemoteFunction', 'ParallelFunction']
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