##// END OF EJS Templates
refactor to improve cell switching in edit mode...
refactor to improve cell switching in edit mode This code was repeated in both CodeCell and TextCell, both of which are extensions of Cell, so this just unifies the logic in Cell. TextCell had logic here to check if the cell was rendered or not, but I don't believe it is possible to end up triggering such a code path. (Should that be required, I can always just add back these methods to TextCell, performing the .rendered==True check, and calling the Cell prior to this, code mirror at_top would only return true on if the cursor was at the first character of the top line. Now, pressing up arrow on any character on the top line will take you to the cell above. The same applies for the bottom line. Pressing down arrow would only go to the next cell if the cursor was at a location *after* the last character (something that is only possible to achieve in vim mode if the last line is empty, for example). Now, down arrow on any character of the last line will go to the next cell.

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view.py
1125 lines | 38.0 KiB | text/x-python | PythonLexer
"""Views of remote engines.
Authors:
* Min RK
"""
from __future__ import print_function
#-----------------------------------------------------------------------------
# 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 import pickleutil
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 IPython.utils.py3compat import string_types, iteritems, PY3
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)
self.outstanding.update(msg_ids)
return ret
@decorator
def sync_results(f, self, *args, **kwargs):
"""sync relevant results from self.client to our results attribute."""
if self._in_sync_results:
return f(self, *args, **kwargs)
self._in_sync_results = True
try:
ret = f(self, *args, **kwargs)
finally:
self._in_sync_results = False
self._sync_results()
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'])
_in_sync_results = Bool(False)
_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 iteritems(kwargs):
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
#----------------------------------------------------------------
def _sync_results(self):
"""to be called by @sync_results decorator
after submitting any tasks.
"""
delta = self.outstanding.difference(self.client.outstanding)
completed = self.outstanding.intersection(delta)
self.outstanding = self.outstanding.difference(completed)
@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.
Returns :class:`~IPython.parallel.client.asyncresult.AsyncResult`
instance if ``self.block`` is False, otherwise the return value 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 :class:`~IPython.parallel.client.asyncresult.AsyncResult` instance.
"""
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.
"""
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 :meth:`IPython.parallel.client.client.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
#-------------------------------------------------------------------
@sync_results
def map(self, f, *sequences, **kwargs):
"""override in subclasses"""
raise NotImplementedError
def map_async(self, f, *sequences, **kwargs):
"""Parallel version of builtin :func:`python: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 :func:`python: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 :func:`itertools.imap`.
See `self.map` for details.
"""
return iter(self.map_async(f,*sequences, **kwargs))
#-------------------------------------------------------------------
# Decorators
#-------------------------------------------------------------------
def remote(self, block=None, **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':
>>> dv['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)
"""
from IPython.utils.py3compat import builtin_mod
local_import = builtin_mod.__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=0):
"""the drop-in replacement for __import__, that optionally imports
locally as well.
"""
# don't override nested imports
save_import = builtin_mod.__import__
builtin_mod.__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 <= 0 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_mod.__import__ = save_import
return mod
# override __import__
builtin_mod.__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_mod.__import__ = local_import
for r in results:
# raise possible remote ImportErrors here
r.get()
def use_dill(self):
"""Expand serialization support with dill
adds support for closures, etc.
This calls IPython.utils.pickleutil.use_dill() here and on each engine.
"""
pickleutil.use_dill()
return self.apply(pickleutil.use_dill)
@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, _targets = self.client._build_targets(targets)
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'])
if isinstance(targets, int):
msg_ids = msg_ids[0]
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
@sync_results
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
An :class:`~IPython.parallel.client.asyncresult.AsyncMapResult` instance.
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
A 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, _targets = self.client._build_targets(targets)
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'])
if isinstance(targets, int):
msg_ids = msg_ids[0]
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, string_types):
pass
elif isinstance(names, (list,tuple,set)):
for key in names:
if not isinstance(key, string_types):
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=None):
"""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)
#----------------------------------------
# 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, string_types + (AsyncResult, Dependency)):
return True
elif isinstance(dep, (list,set, tuple)):
for d in dep:
if not isinstance(d, string_types + (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, string_types):
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, float, type(None))):
if (not PY3) and (not isinstance(t, long)):
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)
metadata = dict(after=after, follow=follow, timeout=timeout, targets=idents, retries=retries)
msg = self.client.send_apply_request(self._socket, f, args, kwargs, track=track,
metadata=metadata)
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
@sync_results
@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
An :class:`~IPython.parallel.client.asyncresult.AsyncMapResult` instance.
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
A list, 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']