|
|
"""AsyncResult objects for the client
|
|
|
|
|
|
Authors:
|
|
|
|
|
|
* MinRK
|
|
|
"""
|
|
|
#-----------------------------------------------------------------------------
|
|
|
# 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 print_function
|
|
|
|
|
|
import sys
|
|
|
import time
|
|
|
from datetime import datetime
|
|
|
|
|
|
from zmq import MessageTracker
|
|
|
|
|
|
from IPython.core.display import clear_output, display, display_pretty
|
|
|
from IPython.external.decorator import decorator
|
|
|
from IPython.parallel import error
|
|
|
|
|
|
#-----------------------------------------------------------------------------
|
|
|
# Functions
|
|
|
#-----------------------------------------------------------------------------
|
|
|
|
|
|
def _raw_text(s):
|
|
|
display_pretty(s, raw=True)
|
|
|
|
|
|
#-----------------------------------------------------------------------------
|
|
|
# Classes
|
|
|
#-----------------------------------------------------------------------------
|
|
|
|
|
|
# global empty tracker that's always done:
|
|
|
finished_tracker = MessageTracker()
|
|
|
|
|
|
@decorator
|
|
|
def check_ready(f, self, *args, **kwargs):
|
|
|
"""Call spin() to sync state prior to calling the method."""
|
|
|
self.wait(0)
|
|
|
if not self._ready:
|
|
|
raise error.TimeoutError("result not ready")
|
|
|
return f(self, *args, **kwargs)
|
|
|
|
|
|
class AsyncResult(object):
|
|
|
"""Class for representing results of non-blocking calls.
|
|
|
|
|
|
Provides the same interface as :py:class:`multiprocessing.pool.AsyncResult`.
|
|
|
"""
|
|
|
|
|
|
msg_ids = None
|
|
|
_targets = None
|
|
|
_tracker = None
|
|
|
_single_result = False
|
|
|
|
|
|
def __init__(self, client, msg_ids, fname='unknown', targets=None, tracker=None):
|
|
|
if isinstance(msg_ids, basestring):
|
|
|
# always a list
|
|
|
msg_ids = [msg_ids]
|
|
|
self._single_result = True
|
|
|
else:
|
|
|
self._single_result = False
|
|
|
if tracker is None:
|
|
|
# default to always done
|
|
|
tracker = finished_tracker
|
|
|
self._client = client
|
|
|
self.msg_ids = msg_ids
|
|
|
self._fname=fname
|
|
|
self._targets = targets
|
|
|
self._tracker = tracker
|
|
|
|
|
|
self._ready = False
|
|
|
self._outputs_ready = False
|
|
|
self._success = None
|
|
|
self._metadata = [ self._client.metadata.get(id) for id in self.msg_ids ]
|
|
|
|
|
|
def __repr__(self):
|
|
|
if self._ready:
|
|
|
return "<%s: finished>"%(self.__class__.__name__)
|
|
|
else:
|
|
|
return "<%s: %s>"%(self.__class__.__name__,self._fname)
|
|
|
|
|
|
|
|
|
def _reconstruct_result(self, res):
|
|
|
"""Reconstruct our result from actual result list (always a list)
|
|
|
|
|
|
Override me in subclasses for turning a list of results
|
|
|
into the expected form.
|
|
|
"""
|
|
|
if self._single_result:
|
|
|
return res[0]
|
|
|
else:
|
|
|
return res
|
|
|
|
|
|
def get(self, timeout=-1):
|
|
|
"""Return the result when it arrives.
|
|
|
|
|
|
If `timeout` is not ``None`` and the result does not arrive within
|
|
|
`timeout` seconds then ``TimeoutError`` is raised. If the
|
|
|
remote call raised an exception then that exception will be reraised
|
|
|
by get() inside a `RemoteError`.
|
|
|
"""
|
|
|
if not self.ready():
|
|
|
self.wait(timeout)
|
|
|
|
|
|
if self._ready:
|
|
|
if self._success:
|
|
|
return self._result
|
|
|
else:
|
|
|
raise self._exception
|
|
|
else:
|
|
|
raise error.TimeoutError("Result not ready.")
|
|
|
|
|
|
def _check_ready(self):
|
|
|
if not self.ready():
|
|
|
raise error.TimeoutError("Result not ready.")
|
|
|
|
|
|
def ready(self):
|
|
|
"""Return whether the call has completed."""
|
|
|
if not self._ready:
|
|
|
self.wait(0)
|
|
|
elif not self._outputs_ready:
|
|
|
self._wait_for_outputs(0)
|
|
|
|
|
|
return self._ready
|
|
|
|
|
|
def wait(self, timeout=-1):
|
|
|
"""Wait until the result is available or until `timeout` seconds pass.
|
|
|
|
|
|
This method always returns None.
|
|
|
"""
|
|
|
if self._ready:
|
|
|
self._wait_for_outputs(timeout)
|
|
|
return
|
|
|
self._ready = self._client.wait(self.msg_ids, timeout)
|
|
|
if self._ready:
|
|
|
try:
|
|
|
results = map(self._client.results.get, self.msg_ids)
|
|
|
self._result = results
|
|
|
if self._single_result:
|
|
|
r = results[0]
|
|
|
if isinstance(r, Exception):
|
|
|
raise r
|
|
|
else:
|
|
|
results = error.collect_exceptions(results, self._fname)
|
|
|
self._result = self._reconstruct_result(results)
|
|
|
except Exception as e:
|
|
|
self._exception = e
|
|
|
self._success = False
|
|
|
else:
|
|
|
self._success = True
|
|
|
finally:
|
|
|
if timeout is None or timeout < 0:
|
|
|
# cutoff infinite wait at 10s
|
|
|
timeout = 10
|
|
|
self._wait_for_outputs(timeout)
|
|
|
|
|
|
|
|
|
def successful(self):
|
|
|
"""Return whether the call completed without raising an exception.
|
|
|
|
|
|
Will raise ``AssertionError`` if the result is not ready.
|
|
|
"""
|
|
|
assert self.ready()
|
|
|
return self._success
|
|
|
|
|
|
#----------------------------------------------------------------
|
|
|
# Extra methods not in mp.pool.AsyncResult
|
|
|
#----------------------------------------------------------------
|
|
|
|
|
|
def get_dict(self, timeout=-1):
|
|
|
"""Get the results as a dict, keyed by engine_id.
|
|
|
|
|
|
timeout behavior is described in `get()`.
|
|
|
"""
|
|
|
|
|
|
results = self.get(timeout)
|
|
|
if self._single_result:
|
|
|
results = [results]
|
|
|
engine_ids = [ md['engine_id'] for md in self._metadata ]
|
|
|
|
|
|
|
|
|
rdict = {}
|
|
|
for engine_id, result in zip(engine_ids, results):
|
|
|
if engine_id in rdict:
|
|
|
raise ValueError("Cannot build dict, %i jobs ran on engine #%i" % (
|
|
|
engine_ids.count(engine_id), engine_id)
|
|
|
)
|
|
|
else:
|
|
|
rdict[engine_id] = result
|
|
|
|
|
|
return rdict
|
|
|
|
|
|
@property
|
|
|
def result(self):
|
|
|
"""result property wrapper for `get(timeout=-1)`."""
|
|
|
return self.get()
|
|
|
|
|
|
# abbreviated alias:
|
|
|
r = result
|
|
|
|
|
|
@property
|
|
|
def metadata(self):
|
|
|
"""property for accessing execution metadata."""
|
|
|
if self._single_result:
|
|
|
return self._metadata[0]
|
|
|
else:
|
|
|
return self._metadata
|
|
|
|
|
|
@property
|
|
|
def result_dict(self):
|
|
|
"""result property as a dict."""
|
|
|
return self.get_dict()
|
|
|
|
|
|
def __dict__(self):
|
|
|
return self.get_dict(0)
|
|
|
|
|
|
def abort(self):
|
|
|
"""abort my tasks."""
|
|
|
assert not self.ready(), "Can't abort, I am already done!"
|
|
|
return self._client.abort(self.msg_ids, targets=self._targets, block=True)
|
|
|
|
|
|
@property
|
|
|
def sent(self):
|
|
|
"""check whether my messages have been sent."""
|
|
|
return self._tracker.done
|
|
|
|
|
|
def wait_for_send(self, timeout=-1):
|
|
|
"""wait for pyzmq send to complete.
|
|
|
|
|
|
This is necessary when sending arrays that you intend to edit in-place.
|
|
|
`timeout` is in seconds, and will raise TimeoutError if it is reached
|
|
|
before the send completes.
|
|
|
"""
|
|
|
return self._tracker.wait(timeout)
|
|
|
|
|
|
#-------------------------------------
|
|
|
# dict-access
|
|
|
#-------------------------------------
|
|
|
|
|
|
def __getitem__(self, key):
|
|
|
"""getitem returns result value(s) if keyed by int/slice, or metadata if key is str.
|
|
|
"""
|
|
|
if isinstance(key, int):
|
|
|
self._check_ready()
|
|
|
return error.collect_exceptions([self._result[key]], self._fname)[0]
|
|
|
elif isinstance(key, slice):
|
|
|
self._check_ready()
|
|
|
return error.collect_exceptions(self._result[key], self._fname)
|
|
|
elif isinstance(key, basestring):
|
|
|
# metadata proxy *does not* require that results are done
|
|
|
self.wait(0)
|
|
|
values = [ md[key] for md in self._metadata ]
|
|
|
if self._single_result:
|
|
|
return values[0]
|
|
|
else:
|
|
|
return values
|
|
|
else:
|
|
|
raise TypeError("Invalid key type %r, must be 'int','slice', or 'str'"%type(key))
|
|
|
|
|
|
def __getattr__(self, key):
|
|
|
"""getattr maps to getitem for convenient attr access to metadata."""
|
|
|
try:
|
|
|
return self.__getitem__(key)
|
|
|
except (error.TimeoutError, KeyError):
|
|
|
raise AttributeError("%r object has no attribute %r"%(
|
|
|
self.__class__.__name__, key))
|
|
|
|
|
|
# asynchronous iterator:
|
|
|
def __iter__(self):
|
|
|
if self._single_result:
|
|
|
raise TypeError("AsyncResults with a single result are not iterable.")
|
|
|
try:
|
|
|
rlist = self.get(0)
|
|
|
except error.TimeoutError:
|
|
|
# wait for each result individually
|
|
|
for msg_id in self.msg_ids:
|
|
|
ar = AsyncResult(self._client, msg_id, self._fname)
|
|
|
yield ar.get()
|
|
|
else:
|
|
|
# already done
|
|
|
for r in rlist:
|
|
|
yield r
|
|
|
|
|
|
def __len__(self):
|
|
|
return len(self.msg_ids)
|
|
|
|
|
|
#-------------------------------------
|
|
|
# Sugar methods and attributes
|
|
|
#-------------------------------------
|
|
|
|
|
|
def timedelta(self, start, end, start_key=min, end_key=max):
|
|
|
"""compute the difference between two sets of timestamps
|
|
|
|
|
|
The default behavior is to use the earliest of the first
|
|
|
and the latest of the second list, but this can be changed
|
|
|
by passing a different
|
|
|
|
|
|
Parameters
|
|
|
----------
|
|
|
|
|
|
start : one or more datetime objects (e.g. ar.submitted)
|
|
|
end : one or more datetime objects (e.g. ar.received)
|
|
|
start_key : callable
|
|
|
Function to call on `start` to extract the relevant
|
|
|
entry [defalt: min]
|
|
|
end_key : callable
|
|
|
Function to call on `end` to extract the relevant
|
|
|
entry [default: max]
|
|
|
|
|
|
Returns
|
|
|
-------
|
|
|
|
|
|
dt : float
|
|
|
The time elapsed (in seconds) between the two selected timestamps.
|
|
|
"""
|
|
|
if not isinstance(start, datetime):
|
|
|
# handle single_result AsyncResults, where ar.stamp is single object,
|
|
|
# not a list
|
|
|
start = start_key(start)
|
|
|
if not isinstance(end, datetime):
|
|
|
# handle single_result AsyncResults, where ar.stamp is single object,
|
|
|
# not a list
|
|
|
end = end_key(end)
|
|
|
return (end - start).total_seconds()
|
|
|
|
|
|
@property
|
|
|
def progress(self):
|
|
|
"""the number of tasks which have been completed at this point.
|
|
|
|
|
|
Fractional progress would be given by 1.0 * ar.progress / len(ar)
|
|
|
"""
|
|
|
self.wait(0)
|
|
|
return len(self) - len(set(self.msg_ids).intersection(self._client.outstanding))
|
|
|
|
|
|
@property
|
|
|
def elapsed(self):
|
|
|
"""elapsed time since initial submission"""
|
|
|
if self.ready():
|
|
|
return self.wall_time
|
|
|
|
|
|
now = submitted = datetime.now()
|
|
|
for msg_id in self.msg_ids:
|
|
|
if msg_id in self._client.metadata:
|
|
|
stamp = self._client.metadata[msg_id]['submitted']
|
|
|
if stamp and stamp < submitted:
|
|
|
submitted = stamp
|
|
|
return (now-submitted).total_seconds()
|
|
|
|
|
|
@property
|
|
|
@check_ready
|
|
|
def serial_time(self):
|
|
|
"""serial computation time of a parallel calculation
|
|
|
|
|
|
Computed as the sum of (completed-started) of each task
|
|
|
"""
|
|
|
t = 0
|
|
|
for md in self._metadata:
|
|
|
t += (md['completed'] - md['started']).total_seconds()
|
|
|
return t
|
|
|
|
|
|
@property
|
|
|
@check_ready
|
|
|
def wall_time(self):
|
|
|
"""actual computation time of a parallel calculation
|
|
|
|
|
|
Computed as the time between the latest `received` stamp
|
|
|
and the earliest `submitted`.
|
|
|
|
|
|
Only reliable if Client was spinning/waiting when the task finished, because
|
|
|
the `received` timestamp is created when a result is pulled off of the zmq queue,
|
|
|
which happens as a result of `client.spin()`.
|
|
|
|
|
|
For similar comparison of other timestamp pairs, check out AsyncResult.timedelta.
|
|
|
|
|
|
"""
|
|
|
return self.timedelta(self.submitted, self.received)
|
|
|
|
|
|
def wait_interactive(self, interval=1., timeout=-1):
|
|
|
"""interactive wait, printing progress at regular intervals"""
|
|
|
if timeout is None:
|
|
|
timeout = -1
|
|
|
N = len(self)
|
|
|
tic = time.time()
|
|
|
while not self.ready() and (timeout < 0 or time.time() - tic <= timeout):
|
|
|
self.wait(interval)
|
|
|
clear_output()
|
|
|
print("%4i/%i tasks finished after %4i s" % (self.progress, N, self.elapsed), end="")
|
|
|
sys.stdout.flush()
|
|
|
print()
|
|
|
print("done")
|
|
|
|
|
|
def _republish_displaypub(self, content, eid):
|
|
|
"""republish individual displaypub content dicts"""
|
|
|
try:
|
|
|
ip = get_ipython()
|
|
|
except NameError:
|
|
|
# displaypub is meaningless outside IPython
|
|
|
return
|
|
|
md = content['metadata'] or {}
|
|
|
md['engine'] = eid
|
|
|
ip.display_pub.publish(content['source'], content['data'], md)
|
|
|
|
|
|
def _display_stream(self, text, prefix='', file=None):
|
|
|
if not text:
|
|
|
# nothing to display
|
|
|
return
|
|
|
if file is None:
|
|
|
file = sys.stdout
|
|
|
end = '' if text.endswith('\n') else '\n'
|
|
|
|
|
|
multiline = text.count('\n') > int(text.endswith('\n'))
|
|
|
if prefix and multiline and not text.startswith('\n'):
|
|
|
prefix = prefix + '\n'
|
|
|
print("%s%s" % (prefix, text), file=file, end=end)
|
|
|
|
|
|
|
|
|
def _display_single_result(self):
|
|
|
self._display_stream(self.stdout)
|
|
|
self._display_stream(self.stderr, file=sys.stderr)
|
|
|
|
|
|
try:
|
|
|
get_ipython()
|
|
|
except NameError:
|
|
|
# displaypub is meaningless outside IPython
|
|
|
return
|
|
|
|
|
|
for output in self.outputs:
|
|
|
self._republish_displaypub(output, self.engine_id)
|
|
|
|
|
|
if self.pyout is not None:
|
|
|
display(self.get())
|
|
|
|
|
|
def _wait_for_outputs(self, timeout=-1):
|
|
|
"""wait for the 'status=idle' message that indicates we have all outputs
|
|
|
"""
|
|
|
if self._outputs_ready or not self._success:
|
|
|
# don't wait on errors
|
|
|
return
|
|
|
|
|
|
# cast None to -1 for infinite timeout
|
|
|
if timeout is None:
|
|
|
timeout = -1
|
|
|
|
|
|
tic = time.time()
|
|
|
while True:
|
|
|
self._client._flush_iopub(self._client._iopub_socket)
|
|
|
self._outputs_ready = all(md['outputs_ready']
|
|
|
for md in self._metadata)
|
|
|
if self._outputs_ready or \
|
|
|
(timeout >= 0 and time.time() > tic + timeout):
|
|
|
break
|
|
|
time.sleep(0.01)
|
|
|
|
|
|
@check_ready
|
|
|
def display_outputs(self, groupby="type"):
|
|
|
"""republish the outputs of the computation
|
|
|
|
|
|
Parameters
|
|
|
----------
|
|
|
|
|
|
groupby : str [default: type]
|
|
|
if 'type':
|
|
|
Group outputs by type (show all stdout, then all stderr, etc.):
|
|
|
|
|
|
[stdout:1] foo
|
|
|
[stdout:2] foo
|
|
|
[stderr:1] bar
|
|
|
[stderr:2] bar
|
|
|
if 'engine':
|
|
|
Display outputs for each engine before moving on to the next:
|
|
|
|
|
|
[stdout:1] foo
|
|
|
[stderr:1] bar
|
|
|
[stdout:2] foo
|
|
|
[stderr:2] bar
|
|
|
|
|
|
if 'order':
|
|
|
Like 'type', but further collate individual displaypub
|
|
|
outputs. This is meant for cases of each command producing
|
|
|
several plots, and you would like to see all of the first
|
|
|
plots together, then all of the second plots, and so on.
|
|
|
"""
|
|
|
if self._single_result:
|
|
|
self._display_single_result()
|
|
|
return
|
|
|
|
|
|
stdouts = self.stdout
|
|
|
stderrs = self.stderr
|
|
|
pyouts = self.pyout
|
|
|
output_lists = self.outputs
|
|
|
results = self.get()
|
|
|
|
|
|
targets = self.engine_id
|
|
|
|
|
|
if groupby == "engine":
|
|
|
for eid,stdout,stderr,outputs,r,pyout in zip(
|
|
|
targets, stdouts, stderrs, output_lists, results, pyouts
|
|
|
):
|
|
|
self._display_stream(stdout, '[stdout:%i] ' % eid)
|
|
|
self._display_stream(stderr, '[stderr:%i] ' % eid, file=sys.stderr)
|
|
|
|
|
|
try:
|
|
|
get_ipython()
|
|
|
except NameError:
|
|
|
# displaypub is meaningless outside IPython
|
|
|
return
|
|
|
|
|
|
if outputs or pyout is not None:
|
|
|
_raw_text('[output:%i]' % eid)
|
|
|
|
|
|
for output in outputs:
|
|
|
self._republish_displaypub(output, eid)
|
|
|
|
|
|
if pyout is not None:
|
|
|
display(r)
|
|
|
|
|
|
elif groupby in ('type', 'order'):
|
|
|
# republish stdout:
|
|
|
for eid,stdout in zip(targets, stdouts):
|
|
|
self._display_stream(stdout, '[stdout:%i] ' % eid)
|
|
|
|
|
|
# republish stderr:
|
|
|
for eid,stderr in zip(targets, stderrs):
|
|
|
self._display_stream(stderr, '[stderr:%i] ' % eid, file=sys.stderr)
|
|
|
|
|
|
try:
|
|
|
get_ipython()
|
|
|
except NameError:
|
|
|
# displaypub is meaningless outside IPython
|
|
|
return
|
|
|
|
|
|
if groupby == 'order':
|
|
|
output_dict = dict((eid, outputs) for eid,outputs in zip(targets, output_lists))
|
|
|
N = max(len(outputs) for outputs in output_lists)
|
|
|
for i in range(N):
|
|
|
for eid in targets:
|
|
|
outputs = output_dict[eid]
|
|
|
if len(outputs) >= N:
|
|
|
_raw_text('[output:%i]' % eid)
|
|
|
self._republish_displaypub(outputs[i], eid)
|
|
|
else:
|
|
|
# republish displaypub output
|
|
|
for eid,outputs in zip(targets, output_lists):
|
|
|
if outputs:
|
|
|
_raw_text('[output:%i]' % eid)
|
|
|
for output in outputs:
|
|
|
self._republish_displaypub(output, eid)
|
|
|
|
|
|
# finally, add pyout:
|
|
|
for eid,r,pyout in zip(targets, results, pyouts):
|
|
|
if pyout is not None:
|
|
|
display(r)
|
|
|
|
|
|
else:
|
|
|
raise ValueError("groupby must be one of 'type', 'engine', 'collate', not %r" % groupby)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
class AsyncMapResult(AsyncResult):
|
|
|
"""Class for representing results of non-blocking gathers.
|
|
|
|
|
|
This will properly reconstruct the gather.
|
|
|
|
|
|
This class is iterable at any time, and will wait on results as they come.
|
|
|
|
|
|
If ordered=False, then the first results to arrive will come first, otherwise
|
|
|
results will be yielded in the order they were submitted.
|
|
|
|
|
|
"""
|
|
|
|
|
|
def __init__(self, client, msg_ids, mapObject, fname='', ordered=True):
|
|
|
AsyncResult.__init__(self, client, msg_ids, fname=fname)
|
|
|
self._mapObject = mapObject
|
|
|
self._single_result = False
|
|
|
self.ordered = ordered
|
|
|
|
|
|
def _reconstruct_result(self, res):
|
|
|
"""Perform the gather on the actual results."""
|
|
|
return self._mapObject.joinPartitions(res)
|
|
|
|
|
|
# asynchronous iterator:
|
|
|
def __iter__(self):
|
|
|
it = self._ordered_iter if self.ordered else self._unordered_iter
|
|
|
for r in it():
|
|
|
yield r
|
|
|
|
|
|
# asynchronous ordered iterator:
|
|
|
def _ordered_iter(self):
|
|
|
"""iterator for results *as they arrive*, preserving submission order."""
|
|
|
try:
|
|
|
rlist = self.get(0)
|
|
|
except error.TimeoutError:
|
|
|
# wait for each result individually
|
|
|
for msg_id in self.msg_ids:
|
|
|
ar = AsyncResult(self._client, msg_id, self._fname)
|
|
|
rlist = ar.get()
|
|
|
try:
|
|
|
for r in rlist:
|
|
|
yield r
|
|
|
except TypeError:
|
|
|
# flattened, not a list
|
|
|
# this could get broken by flattened data that returns iterables
|
|
|
# but most calls to map do not expose the `flatten` argument
|
|
|
yield rlist
|
|
|
else:
|
|
|
# already done
|
|
|
for r in rlist:
|
|
|
yield r
|
|
|
|
|
|
# asynchronous unordered iterator:
|
|
|
def _unordered_iter(self):
|
|
|
"""iterator for results *as they arrive*, on FCFS basis, ignoring submission order."""
|
|
|
try:
|
|
|
rlist = self.get(0)
|
|
|
except error.TimeoutError:
|
|
|
pending = set(self.msg_ids)
|
|
|
while pending:
|
|
|
try:
|
|
|
self._client.wait(pending, 1e-3)
|
|
|
except error.TimeoutError:
|
|
|
# ignore timeout error, because that only means
|
|
|
# *some* jobs are outstanding
|
|
|
pass
|
|
|
# update ready set with those no longer outstanding:
|
|
|
ready = pending.difference(self._client.outstanding)
|
|
|
# update pending to exclude those that are finished
|
|
|
pending = pending.difference(ready)
|
|
|
while ready:
|
|
|
msg_id = ready.pop()
|
|
|
ar = AsyncResult(self._client, msg_id, self._fname)
|
|
|
rlist = ar.get()
|
|
|
try:
|
|
|
for r in rlist:
|
|
|
yield r
|
|
|
except TypeError:
|
|
|
# flattened, not a list
|
|
|
# this could get broken by flattened data that returns iterables
|
|
|
# but most calls to map do not expose the `flatten` argument
|
|
|
yield rlist
|
|
|
else:
|
|
|
# already done
|
|
|
for r in rlist:
|
|
|
yield r
|
|
|
|
|
|
|
|
|
class AsyncHubResult(AsyncResult):
|
|
|
"""Class to wrap pending results that must be requested from the Hub.
|
|
|
|
|
|
Note that waiting/polling on these objects requires polling the Hubover the network,
|
|
|
so use `AsyncHubResult.wait()` sparingly.
|
|
|
"""
|
|
|
|
|
|
def _wait_for_outputs(self, timeout=-1):
|
|
|
"""no-op, because HubResults are never incomplete"""
|
|
|
self._outputs_ready = True
|
|
|
|
|
|
def wait(self, timeout=-1):
|
|
|
"""wait for result to complete."""
|
|
|
start = time.time()
|
|
|
if self._ready:
|
|
|
return
|
|
|
local_ids = filter(lambda msg_id: msg_id in self._client.outstanding, self.msg_ids)
|
|
|
local_ready = self._client.wait(local_ids, timeout)
|
|
|
if local_ready:
|
|
|
remote_ids = filter(lambda msg_id: msg_id not in self._client.results, self.msg_ids)
|
|
|
if not remote_ids:
|
|
|
self._ready = True
|
|
|
else:
|
|
|
rdict = self._client.result_status(remote_ids, status_only=False)
|
|
|
pending = rdict['pending']
|
|
|
while pending and (timeout < 0 or time.time() < start+timeout):
|
|
|
rdict = self._client.result_status(remote_ids, status_only=False)
|
|
|
pending = rdict['pending']
|
|
|
if pending:
|
|
|
time.sleep(0.1)
|
|
|
if not pending:
|
|
|
self._ready = True
|
|
|
if self._ready:
|
|
|
try:
|
|
|
results = map(self._client.results.get, self.msg_ids)
|
|
|
self._result = results
|
|
|
if self._single_result:
|
|
|
r = results[0]
|
|
|
if isinstance(r, Exception):
|
|
|
raise r
|
|
|
else:
|
|
|
results = error.collect_exceptions(results, self._fname)
|
|
|
self._result = self._reconstruct_result(results)
|
|
|
except Exception as e:
|
|
|
self._exception = e
|
|
|
self._success = False
|
|
|
else:
|
|
|
self._success = True
|
|
|
finally:
|
|
|
self._metadata = map(self._client.metadata.get, self.msg_ids)
|
|
|
|
|
|
__all__ = ['AsyncResult', 'AsyncMapResult', 'AsyncHubResult']
|
|
|
|
