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Merge pull request #1779 from takluyver/i1778...
Merge pull request #1779 from takluyver/i1778 Tidy up error raising in magic decorators, change a few exceptions for more appropriate kinds in new magics code. Closes gh-1778.

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asyncresult.py
516 lines | 17.6 KiB | text/x-python | PythonLexer
"""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
#-----------------------------------------------------------------------------
import sys
import time
from datetime import datetime
from zmq import MessageTracker
from IPython.core.display import clear_output
from IPython.external.decorator import decorator
from IPython.parallel import error
#-----------------------------------------------------------------------------
# Functions
#-----------------------------------------------------------------------------
def _total_seconds(td):
"""timedelta.total_seconds was added in 2.7"""
try:
# Python >= 2.7
return td.total_seconds()
except AttributeError:
# Python 2.6
return 1e-6 * (td.microseconds + (td.seconds + td.days * 24 * 3600) * 10**6)
#-----------------------------------------------------------------------------
# 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]
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._success = None
self._metadata = None
if len(msg_ids) == 1:
self._single_result = not isinstance(targets, (list, tuple))
else:
self._single_result = False
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 ready(self):
"""Return whether the call has completed."""
if not self._ready:
self.wait(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:
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, e:
self._exception = e
self._success = False
else:
self._success = True
finally:
self._metadata = map(self._client.metadata.get, self.msg_ids)
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)
engine_ids = [ md['engine_id'] for md in self._metadata ]
bycount = sorted(engine_ids, key=lambda k: engine_ids.count(k))
maxcount = bycount.count(bycount[-1])
if maxcount > 1:
raise ValueError("Cannot build dict, %i jobs ran on engine #%i"%(
maxcount, bycount[-1]))
return dict(zip(engine_ids,results))
@property
def result(self):
"""result property wrapper for `get(timeout=0)`."""
return self.get()
# abbreviated alias:
r = result
@property
@check_ready
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
#-------------------------------------
@check_ready
def __getitem__(self, key):
"""getitem returns result value(s) if keyed by int/slice, or metadata if key is str.
"""
if isinstance(key, int):
return error.collect_exceptions([self._result[key]], self._fname)[0]
elif isinstance(key, slice):
return error.collect_exceptions(self._result[key], self._fname)
elif isinstance(key, basestring):
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 _total_seconds(end - start)
@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 _total_seconds(now-submitted)
@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 += _total_seconds(md['completed'] - md['started'])
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=None):
"""interactive wait, printing progress at regular intervals"""
N = len(self)
tic = time.time()
while not self.ready() and (timeout is None or time.time() - tic <= timeout):
self.wait(interval)
clear_output()
print "%4i/%i tasks finished after %4i s" % (self.progress, N, self.elapsed),
sys.stdout.flush()
print
print "done"
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(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, 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']