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"""Views of remote engines.
Authors:
* 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
#-----------------------------------------------------------------------------
import imp
import sys
import warnings
from contextlib import contextmanager
from types import ModuleType
import zmq
from IPython.testing.skipdoctest import skip_doctest
from IPython.utils.traitlets import (
HasTraits, Any, Bool, List, Dict, Set, Instance, CFloat, Integer
)
from IPython.external.decorator import decorator
from IPython.parallel import util
from IPython.parallel.controller.dependency import Dependency, dependent
from . import map as Map
from .asyncresult import AsyncResult, AsyncMapResult
from .remotefunction import ParallelFunction, parallel, remote, getname
#-----------------------------------------------------------------------------
# Decorators
#-----------------------------------------------------------------------------
@decorator
def save_ids(f, self, *args, **kwargs):
"""Keep our history and outstanding attributes up to date after a method call."""
n_previous = len(self.client.history)
try:
ret = f(self, *args, **kwargs)
finally:
nmsgs = len(self.client.history) - n_previous
msg_ids = self.client.history[-nmsgs:]
self.history.extend(msg_ids)
map(self.outstanding.add, msg_ids)
return ret
@decorator
def sync_results(f, self, *args, **kwargs):
"""sync relevant results from self.client to our results attribute."""
ret = f(self, *args, **kwargs)
delta = self.outstanding.difference(self.client.outstanding)
completed = self.outstanding.intersection(delta)
self.outstanding = self.outstanding.difference(completed)
return ret
@decorator
def spin_after(f, self, *args, **kwargs):
"""call spin after the method."""
ret = f(self, *args, **kwargs)
self.spin()
return ret
#-----------------------------------------------------------------------------
# Classes
#-----------------------------------------------------------------------------
@skip_doctest
class View(HasTraits):
"""Base View class for more convenint apply(f,*args,**kwargs) syntax via attributes.
Don't use this class, use subclasses.
Methods
-------
spin
flushes incoming results and registration state changes
control methods spin, and requesting `ids` also ensures up to date
wait
wait on one or more msg_ids
execution methods
apply
legacy: execute, run
data movement
push, pull, scatter, gather
query methods
get_result, queue_status, purge_results, result_status
control methods
abort, shutdown
"""
# flags
block=Bool(False)
track=Bool(True)
targets = Any()
history=List()
outstanding = Set()
results = Dict()
client = Instance('IPython.parallel.Client')
_socket = Instance('zmq.Socket')
_flag_names = List(['targets', 'block', 'track'])
_targets = Any()
_idents = Any()
def __init__(self, client=None, socket=None, **flags):
super(View, self).__init__(client=client, _socket=socket)
self.results = client.results
self.block = client.block
self.set_flags(**flags)
assert not self.__class__ is View, "Don't use base View objects, use subclasses"
def __repr__(self):
strtargets = str(self.targets)
if len(strtargets) > 16:
strtargets = strtargets[:12]+'...]'
return "<%s %s>"%(self.__class__.__name__, strtargets)
def __len__(self):
if isinstance(self.targets, list):
return len(self.targets)
elif isinstance(self.targets, int):
return 1
else:
return len(self.client)
def set_flags(self, **kwargs):
"""set my attribute flags by keyword.
Views determine behavior with a few attributes (`block`, `track`, etc.).
These attributes can be set all at once by name with this method.
Parameters
----------
block : bool
whether to wait for results
track : bool
whether to create a MessageTracker to allow the user to
safely edit after arrays and buffers during non-copying
sends.
"""
for name, value in kwargs.iteritems():
if name not in self._flag_names:
raise KeyError("Invalid name: %r"%name)
else:
setattr(self, name, value)
@contextmanager
def temp_flags(self, **kwargs):
"""temporarily set flags, for use in `with` statements.
See set_flags for permanent setting of flags
Examples
--------
>>> view.track=False
...
>>> with view.temp_flags(track=True):
... ar = view.apply(dostuff, my_big_array)
... ar.tracker.wait() # wait for send to finish
>>> view.track
False
"""
# preflight: save flags, and set temporaries
saved_flags = {}
for f in self._flag_names:
saved_flags[f] = getattr(self, f)
self.set_flags(**kwargs)
# yield to the with-statement block
try:
yield
finally:
# postflight: restore saved flags
self.set_flags(**saved_flags)
#----------------------------------------------------------------
# apply
#----------------------------------------------------------------
@sync_results
@save_ids
def _really_apply(self, f, args, kwargs, block=None, **options):
"""wrapper for client.send_apply_request"""
raise NotImplementedError("Implement in subclasses")
def apply(self, f, *args, **kwargs):
"""calls f(*args, **kwargs) on remote engines, returning the result.
This method sets all apply flags via this View's attributes.
if self.block is False:
returns AsyncResult
else:
returns actual result of f(*args, **kwargs)
"""
return self._really_apply(f, args, kwargs)
def apply_async(self, f, *args, **kwargs):
"""calls f(*args, **kwargs) on remote engines in a nonblocking manner.
returns AsyncResult
"""
return self._really_apply(f, args, kwargs, block=False)
@spin_after
def apply_sync(self, f, *args, **kwargs):
"""calls f(*args, **kwargs) on remote engines in a blocking manner,
returning the result.
returns: actual result of f(*args, **kwargs)
"""
return self._really_apply(f, args, kwargs, block=True)
#----------------------------------------------------------------
# wrappers for client and control methods
#----------------------------------------------------------------
@sync_results
def spin(self):
"""spin the client, and sync"""
self.client.spin()
@sync_results
def wait(self, jobs=None, timeout=-1):
"""waits on one or more `jobs`, for up to `timeout` seconds.
Parameters
----------
jobs : int, str, or list of ints and/or strs, or one or more AsyncResult objects
ints are indices to self.history
strs are msg_ids
default: wait on all outstanding messages
timeout : float
a time in seconds, after which to give up.
default is -1, which means no timeout
Returns
-------
True : when all msg_ids are done
False : timeout reached, some msg_ids still outstanding
"""
if jobs is None:
jobs = self.history
return self.client.wait(jobs, timeout)
def abort(self, jobs=None, targets=None, block=None):
"""Abort jobs on my engines.
Parameters
----------
jobs : None, str, list of strs, optional
if None: abort all jobs.
else: abort specific msg_id(s).
"""
block = block if block is not None else self.block
targets = targets if targets is not None else self.targets
jobs = jobs if jobs is not None else list(self.outstanding)
return self.client.abort(jobs=jobs, targets=targets, block=block)
def queue_status(self, targets=None, verbose=False):
"""Fetch the Queue status of my engines"""
targets = targets if targets is not None else self.targets
return self.client.queue_status(targets=targets, verbose=verbose)
def purge_results(self, jobs=[], targets=[]):
"""Instruct the controller to forget specific results."""
if targets is None or targets == 'all':
targets = self.targets
return self.client.purge_results(jobs=jobs, targets=targets)
def shutdown(self, targets=None, restart=False, hub=False, block=None):
"""Terminates one or more engine processes, optionally including the hub.
"""
block = self.block if block is None else block
if targets is None or targets == 'all':
targets = self.targets
return self.client.shutdown(targets=targets, restart=restart, hub=hub, block=block)
@spin_after
def get_result(self, indices_or_msg_ids=None):
"""return one or more results, specified by history index or msg_id.
See client.get_result for details.
"""
if indices_or_msg_ids is None:
indices_or_msg_ids = -1
if isinstance(indices_or_msg_ids, int):
indices_or_msg_ids = self.history[indices_or_msg_ids]
elif isinstance(indices_or_msg_ids, (list,tuple,set)):
indices_or_msg_ids = list(indices_or_msg_ids)
for i,index in enumerate(indices_or_msg_ids):
if isinstance(index, int):
indices_or_msg_ids[i] = self.history[index]
return self.client.get_result(indices_or_msg_ids)
#-------------------------------------------------------------------
# Map
#-------------------------------------------------------------------
def map(self, f, *sequences, **kwargs):
"""override in subclasses"""
raise NotImplementedError
def map_async(self, f, *sequences, **kwargs):
"""Parallel version of builtin `map`, using this view's engines.
This is equivalent to map(...block=False)
See `self.map` for details.
"""
if 'block' in kwargs:
raise TypeError("map_async doesn't take a `block` keyword argument.")
kwargs['block'] = False
return self.map(f,*sequences,**kwargs)
def map_sync(self, f, *sequences, **kwargs):
"""Parallel version of builtin `map`, using this view's engines.
This is equivalent to map(...block=True)
See `self.map` for details.
"""
if 'block' in kwargs:
raise TypeError("map_sync doesn't take a `block` keyword argument.")
kwargs['block'] = True
return self.map(f,*sequences,**kwargs)
def imap(self, f, *sequences, **kwargs):
"""Parallel version of `itertools.imap`.
See `self.map` for details.
"""
return iter(self.map_async(f,*sequences, **kwargs))
#-------------------------------------------------------------------
# Decorators
#-------------------------------------------------------------------
def remote(self, block=True, **flags):
"""Decorator for making a RemoteFunction"""
block = self.block if block is None else block
return remote(self, block=block, **flags)
def parallel(self, dist='b', block=None, **flags):
"""Decorator for making a ParallelFunction"""
block = self.block if block is None else block
return parallel(self, dist=dist, block=block, **flags)
@skip_doctest
class DirectView(View):
"""Direct Multiplexer View of one or more engines.
These are created via indexed access to a client:
>>> dv_1 = client[1]
>>> dv_all = client[:]
>>> dv_even = client[::2]
>>> dv_some = client[1:3]
This object provides dictionary access to engine namespaces:
# push a=5:
>>> dv['a'] = 5
# pull 'foo':
>>> db['foo']
"""
def __init__(self, client=None, socket=None, targets=None):
super(DirectView, self).__init__(client=client, socket=socket, targets=targets)
@property
def importer(self):
"""sync_imports(local=True) as a property.
See sync_imports for details.
"""
return self.sync_imports(True)
@contextmanager
def sync_imports(self, local=True, quiet=False):
"""Context Manager for performing simultaneous local and remote imports.
'import x as y' will *not* work. The 'as y' part will simply be ignored.
If `local=True`, then the package will also be imported locally.
If `quiet=True`, no output will be produced when attempting remote
imports.
Note that remote-only (`local=False`) imports have not been implemented.
>>> with view.sync_imports():
... from numpy import recarray
importing recarray from numpy on engine(s)
"""
import __builtin__
local_import = __builtin__.__import__
modules = set()
results = []
@util.interactive
def remote_import(name, fromlist, level):
"""the function to be passed to apply, that actually performs the import
on the engine, and loads up the user namespace.
"""
import sys
user_ns = globals()
mod = __import__(name, fromlist=fromlist, level=level)
if fromlist:
for key in fromlist:
user_ns[key] = getattr(mod, key)
else:
user_ns[name] = sys.modules[name]
def view_import(name, globals={}, locals={}, fromlist=[], level=-1):
"""the drop-in replacement for __import__, that optionally imports
locally as well.
"""
# don't override nested imports
save_import = __builtin__.__import__
__builtin__.__import__ = local_import
if imp.lock_held():
# this is a side-effect import, don't do it remotely, or even
# ignore the local effects
return local_import(name, globals, locals, fromlist, level)
imp.acquire_lock()
if local:
mod = local_import(name, globals, locals, fromlist, level)
else:
raise NotImplementedError("remote-only imports not yet implemented")
imp.release_lock()
key = name+':'+','.join(fromlist or [])
if level == -1 and key not in modules:
modules.add(key)
if not quiet:
if fromlist:
print "importing %s from %s on engine(s)"%(','.join(fromlist), name)
else:
print "importing %s on engine(s)"%name
results.append(self.apply_async(remote_import, name, fromlist, level))
# restore override
__builtin__.__import__ = save_import
return mod
# override __import__
__builtin__.__import__ = view_import
try:
# enter the block
yield
except ImportError:
if local:
raise
else:
# ignore import errors if not doing local imports
pass
finally:
# always restore __import__
__builtin__.__import__ = local_import
for r in results:
# raise possible remote ImportErrors here
r.get()
@sync_results
@save_ids
def _really_apply(self, f, args=None, kwargs=None, targets=None, block=None, track=None):
"""calls f(*args, **kwargs) on remote engines, returning the result.
This method sets all of `apply`'s flags via this View's attributes.
Parameters
----------
f : callable
args : list [default: empty]
kwargs : dict [default: empty]
targets : target list [default: self.targets]
where to run
block : bool [default: self.block]
whether to block
track : bool [default: self.track]
whether to ask zmq to track the message, for safe non-copying sends
Returns
-------
if self.block is False:
returns AsyncResult
else:
returns actual result of f(*args, **kwargs) on the engine(s)
This will be a list of self.targets is also a list (even length 1), or
the single result if self.targets is an integer engine id
"""
args = [] if args is None else args
kwargs = {} if kwargs is None else kwargs
block = self.block if block is None else block
track = self.track if track is None else track
targets = self.targets if targets is None else targets
_idents = self.client._build_targets(targets)[0]
msg_ids = []
trackers = []
for ident in _idents:
msg = self.client.send_apply_request(self._socket, f, args, kwargs, track=track,
ident=ident)
if track:
trackers.append(msg['tracker'])
msg_ids.append(msg['header']['msg_id'])
tracker = None if track is False else zmq.MessageTracker(*trackers)
ar = AsyncResult(self.client, msg_ids, fname=getname(f), targets=targets, tracker=tracker)
if block:
try:
return ar.get()
except KeyboardInterrupt:
pass
return ar
@spin_after
def map(self, f, *sequences, **kwargs):
"""view.map(f, *sequences, block=self.block) => list|AsyncMapResult
Parallel version of builtin `map`, using this View's `targets`.
There will be one task per target, so work will be chunked
if the sequences are longer than `targets`.
Results can be iterated as they are ready, but will become available in chunks.
Parameters
----------
f : callable
function to be mapped
*sequences: one or more sequences of matching length
the sequences to be distributed and passed to `f`
block : bool
whether to wait for the result or not [default self.block]
Returns
-------
if block=False:
AsyncMapResult
An object like AsyncResult, but which reassembles the sequence of results
into a single list. AsyncMapResults can be iterated through before all
results are complete.
else:
list
the result of map(f,*sequences)
"""
block = kwargs.pop('block', self.block)
for k in kwargs.keys():
if k not in ['block', 'track']:
raise TypeError("invalid keyword arg, %r"%k)
assert len(sequences) > 0, "must have some sequences to map onto!"
pf = ParallelFunction(self, f, block=block, **kwargs)
return pf.map(*sequences)
@sync_results
@save_ids
def execute(self, code, silent=True, targets=None, block=None):
"""Executes `code` on `targets` in blocking or nonblocking manner.
``execute`` is always `bound` (affects engine namespace)
Parameters
----------
code : str
the code string to be executed
block : bool
whether or not to wait until done to return
default: self.block
"""
block = self.block if block is None else block
targets = self.targets if targets is None else targets
_idents = self.client._build_targets(targets)[0]
msg_ids = []
trackers = []
for ident in _idents:
msg = self.client.send_execute_request(self._socket, code, silent=silent, ident=ident)
msg_ids.append(msg['header']['msg_id'])
ar = AsyncResult(self.client, msg_ids, fname='execute', targets=targets)
if block:
try:
ar.get()
except KeyboardInterrupt:
pass
return ar
def run(self, filename, targets=None, block=None):
"""Execute contents of `filename` on my engine(s).
This simply reads the contents of the file and calls `execute`.
Parameters
----------
filename : str
The path to the file
targets : int/str/list of ints/strs
the engines on which to execute
default : all
block : bool
whether or not to wait until done
default: self.block
"""
with open(filename, 'r') as f:
# add newline in case of trailing indented whitespace
# which will cause SyntaxError
code = f.read()+'\n'
return self.execute(code, block=block, targets=targets)
def update(self, ns):
"""update remote namespace with dict `ns`
See `push` for details.
"""
return self.push(ns, block=self.block, track=self.track)
def push(self, ns, targets=None, block=None, track=None):
"""update remote namespace with dict `ns`
Parameters
----------
ns : dict
dict of keys with which to update engine namespace(s)
block : bool [default : self.block]
whether to wait to be notified of engine receipt
"""
block = block if block is not None else self.block
track = track if track is not None else self.track
targets = targets if targets is not None else self.targets
# applier = self.apply_sync if block else self.apply_async
if not isinstance(ns, dict):
raise TypeError("Must be a dict, not %s"%type(ns))
return self._really_apply(util._push, kwargs=ns, block=block, track=track, targets=targets)
def get(self, key_s):
"""get object(s) by `key_s` from remote namespace
see `pull` for details.
"""
# block = block if block is not None else self.block
return self.pull(key_s, block=True)
def pull(self, names, targets=None, block=None):
"""get object(s) by `name` from remote namespace
will return one object if it is a key.
can also take a list of keys, in which case it will return a list of objects.
"""
block = block if block is not None else self.block
targets = targets if targets is not None else self.targets
applier = self.apply_sync if block else self.apply_async
if isinstance(names, basestring):
pass
elif isinstance(names, (list,tuple,set)):
for key in names:
if not isinstance(key, basestring):
raise TypeError("keys must be str, not type %r"%type(key))
else:
raise TypeError("names must be strs, not %r"%names)
return self._really_apply(util._pull, (names,), block=block, targets=targets)
def scatter(self, key, seq, dist='b', flatten=False, targets=None, block=None, track=None):
"""
Partition a Python sequence and send the partitions to a set of engines.
"""
block = block if block is not None else self.block
track = track if track is not None else self.track
targets = targets if targets is not None else self.targets
# construct integer ID list:
targets = self.client._build_targets(targets)[1]
mapObject = Map.dists[dist]()
nparts = len(targets)
msg_ids = []
trackers = []
for index, engineid in enumerate(targets):
partition = mapObject.getPartition(seq, index, nparts)
if flatten and len(partition) == 1:
ns = {key: partition[0]}
else:
ns = {key: partition}
r = self.push(ns, block=False, track=track, targets=engineid)
msg_ids.extend(r.msg_ids)
if track:
trackers.append(r._tracker)
if track:
tracker = zmq.MessageTracker(*trackers)
else:
tracker = None
r = AsyncResult(self.client, msg_ids, fname='scatter', targets=targets, tracker=tracker)
if block:
r.wait()
else:
return r
@sync_results
@save_ids
def gather(self, key, dist='b', targets=None, block=None):
"""
Gather a partitioned sequence on a set of engines as a single local seq.
"""
block = block if block is not None else self.block
targets = targets if targets is not None else self.targets
mapObject = Map.dists[dist]()
msg_ids = []
# construct integer ID list:
targets = self.client._build_targets(targets)[1]
for index, engineid in enumerate(targets):
msg_ids.extend(self.pull(key, block=False, targets=engineid).msg_ids)
r = AsyncMapResult(self.client, msg_ids, mapObject, fname='gather')
if block:
try:
return r.get()
except KeyboardInterrupt:
pass
return r
def __getitem__(self, key):
return self.get(key)
def __setitem__(self,key, value):
self.update({key:value})
def clear(self, targets=None, block=False):
"""Clear the remote namespaces on my engines."""
block = block if block is not None else self.block
targets = targets if targets is not None else self.targets
return self.client.clear(targets=targets, block=block)
def kill(self, targets=None, block=True):
"""Kill my engines."""
block = block if block is not None else self.block
targets = targets if targets is not None else self.targets
return self.client.kill(targets=targets, block=block)
#----------------------------------------
# activate for %px, %autopx, etc. magics
#----------------------------------------
def activate(self, suffix=''):
"""Activate IPython magics associated with this View
Defines the magics `%px, %autopx, %pxresult, %%px, %pxconfig`
Parameters
----------
suffix: str [default: '']
The suffix, if any, for the magics. This allows you to have
multiple views associated with parallel magics at the same time.
e.g. ``rc[::2].activate(suffix='_even')`` will give you
the magics ``%px_even``, ``%pxresult_even``, etc. for running magics
on the even engines.
"""
from IPython.parallel.client.magics import ParallelMagics
try:
# This is injected into __builtins__.
ip = get_ipython()
except NameError:
print "The IPython parallel magics (%px, etc.) only work within IPython."
return
M = ParallelMagics(ip, self, suffix)
ip.magics_manager.register(M)
@skip_doctest
class LoadBalancedView(View):
"""An load-balancing View that only executes via the Task scheduler.
Load-balanced views can be created with the client's `view` method:
>>> v = client.load_balanced_view()
or targets can be specified, to restrict the potential destinations:
>>> v = client.client.load_balanced_view([1,3])
which would restrict loadbalancing to between engines 1 and 3.
"""
follow=Any()
after=Any()
timeout=CFloat()
retries = Integer(0)
_task_scheme = Any()
_flag_names = List(['targets', 'block', 'track', 'follow', 'after', 'timeout', 'retries'])
def __init__(self, client=None, socket=None, **flags):
super(LoadBalancedView, self).__init__(client=client, socket=socket, **flags)
self._task_scheme=client._task_scheme
def _validate_dependency(self, dep):
"""validate a dependency.
For use in `set_flags`.
"""
if dep is None or isinstance(dep, (basestring, AsyncResult, Dependency)):
return True
elif isinstance(dep, (list,set, tuple)):
for d in dep:
if not isinstance(d, (basestring, AsyncResult)):
return False
elif isinstance(dep, dict):
if set(dep.keys()) != set(Dependency().as_dict().keys()):
return False
if not isinstance(dep['msg_ids'], list):
return False
for d in dep['msg_ids']:
if not isinstance(d, basestring):
return False
else:
return False
return True
def _render_dependency(self, dep):
"""helper for building jsonable dependencies from various input forms."""
if isinstance(dep, Dependency):
return dep.as_dict()
elif isinstance(dep, AsyncResult):
return dep.msg_ids
elif dep is None:
return []
else:
# pass to Dependency constructor
return list(Dependency(dep))
def set_flags(self, **kwargs):
"""set my attribute flags by keyword.
A View is a wrapper for the Client's apply method, but with attributes
that specify keyword arguments, those attributes can be set by keyword
argument with this method.
Parameters
----------
block : bool
whether to wait for results
track : bool
whether to create a MessageTracker to allow the user to
safely edit after arrays and buffers during non-copying
sends.
after : Dependency or collection of msg_ids
Only for load-balanced execution (targets=None)
Specify a list of msg_ids as a time-based dependency.
This job will only be run *after* the dependencies
have been met.
follow : Dependency or collection of msg_ids
Only for load-balanced execution (targets=None)
Specify a list of msg_ids as a location-based dependency.
This job will only be run on an engine where this dependency
is met.
timeout : float/int or None
Only for load-balanced execution (targets=None)
Specify an amount of time (in seconds) for the scheduler to
wait for dependencies to be met before failing with a
DependencyTimeout.
retries : int
Number of times a task will be retried on failure.
"""
super(LoadBalancedView, self).set_flags(**kwargs)
for name in ('follow', 'after'):
if name in kwargs:
value = kwargs[name]
if self._validate_dependency(value):
setattr(self, name, value)
else:
raise ValueError("Invalid dependency: %r"%value)
if 'timeout' in kwargs:
t = kwargs['timeout']
if not isinstance(t, (int, long, float, type(None))):
raise TypeError("Invalid type for timeout: %r"%type(t))
if t is not None:
if t < 0:
raise ValueError("Invalid timeout: %s"%t)
self.timeout = t
@sync_results
@save_ids
def _really_apply(self, f, args=None, kwargs=None, block=None, track=None,
after=None, follow=None, timeout=None,
targets=None, retries=None):
"""calls f(*args, **kwargs) on a remote engine, returning the result.
This method temporarily sets all of `apply`'s flags for a single call.
Parameters
----------
f : callable
args : list [default: empty]
kwargs : dict [default: empty]
block : bool [default: self.block]
whether to block
track : bool [default: self.track]
whether to ask zmq to track the message, for safe non-copying sends
!!!!!! TODO: THE REST HERE !!!!
Returns
-------
if self.block is False:
returns AsyncResult
else:
returns actual result of f(*args, **kwargs) on the engine(s)
This will be a list of self.targets is also a list (even length 1), or
the single result if self.targets is an integer engine id
"""
# validate whether we can run
if self._socket.closed:
msg = "Task farming is disabled"
if self._task_scheme == 'pure':
msg += " because the pure ZMQ scheduler cannot handle"
msg += " disappearing engines."
raise RuntimeError(msg)
if self._task_scheme == 'pure':
# pure zmq scheme doesn't support extra features
msg = "Pure ZMQ scheduler doesn't support the following flags:"
"follow, after, retries, targets, timeout"
if (follow or after or retries or targets or timeout):
# hard fail on Scheduler flags
raise RuntimeError(msg)
if isinstance(f, dependent):
# soft warn on functional dependencies
warnings.warn(msg, RuntimeWarning)
# build args
args = [] if args is None else args
kwargs = {} if kwargs is None else kwargs
block = self.block if block is None else block
track = self.track if track is None else track
after = self.after if after is None else after
retries = self.retries if retries is None else retries
follow = self.follow if follow is None else follow
timeout = self.timeout if timeout is None else timeout
targets = self.targets if targets is None else targets
if not isinstance(retries, int):
raise TypeError('retries must be int, not %r'%type(retries))
if targets is None:
idents = []
else:
idents = self.client._build_targets(targets)[0]
# ensure *not* bytes
idents = [ ident.decode() for ident in idents ]
after = self._render_dependency(after)
follow = self._render_dependency(follow)
subheader = dict(after=after, follow=follow, timeout=timeout, targets=idents, retries=retries)
msg = self.client.send_apply_request(self._socket, f, args, kwargs, track=track,
subheader=subheader)
tracker = None if track is False else msg['tracker']
ar = AsyncResult(self.client, msg['header']['msg_id'], fname=getname(f), targets=None, tracker=tracker)
if block:
try:
return ar.get()
except KeyboardInterrupt:
pass
return ar
@spin_after
@save_ids
def map(self, f, *sequences, **kwargs):
"""view.map(f, *sequences, block=self.block, chunksize=1, ordered=True) => list|AsyncMapResult
Parallel version of builtin `map`, load-balanced by this View.
`block`, and `chunksize` can be specified by keyword only.
Each `chunksize` elements will be a separate task, and will be
load-balanced. This lets individual elements be available for iteration
as soon as they arrive.
Parameters
----------
f : callable
function to be mapped
*sequences: one or more sequences of matching length
the sequences to be distributed and passed to `f`
block : bool [default self.block]
whether to wait for the result or not
track : bool
whether to create a MessageTracker to allow the user to
safely edit after arrays and buffers during non-copying
sends.
chunksize : int [default 1]
how many elements should be in each task.
ordered : bool [default True]
Whether the results should be gathered as they arrive, or enforce
the order of submission.
Only applies when iterating through AsyncMapResult as results arrive.
Has no effect when block=True.
Returns
-------
if block=False:
AsyncMapResult
An object like AsyncResult, but which reassembles the sequence of results
into a single list. AsyncMapResults can be iterated through before all
results are complete.
else:
the result of map(f,*sequences)
"""
# default
block = kwargs.get('block', self.block)
chunksize = kwargs.get('chunksize', 1)
ordered = kwargs.get('ordered', True)
keyset = set(kwargs.keys())
extra_keys = keyset.difference_update(set(['block', 'chunksize']))
if extra_keys:
raise TypeError("Invalid kwargs: %s"%list(extra_keys))
assert len(sequences) > 0, "must have some sequences to map onto!"
pf = ParallelFunction(self, f, block=block, chunksize=chunksize, ordered=ordered)
return pf.map(*sequences)
__all__ = ['LoadBalancedView', 'DirectView']
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