/usr/lib/python3/dist-packages/async/task.py is in python3-async 0.6.2-2.
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#
# This module is part of async and is released under
# the New BSD License: http://www.opensource.org/licenses/bsd-license.php
from .graph import Node
from .util import ReadOnly
from .channel import IteratorReader
import threading
import weakref
__all__ = ('Task', 'ThreadTaskBase', 'IteratorTaskBase',
'IteratorThreadTask', 'ChannelThreadTask')
class Task(Node):
"""
Abstracts a named task, which contains
additional information on how the task should be queued and processed.
Results of the item processing are sent to a writer, which is to be
set by the creator using the ``set_writer`` method.
Items are read using the internal ``_read`` callable, subclasses are meant to
set this to a callable that supports the Reader interface's read function.
* **min_count** assures that not less than min_count items will be processed per call.
* **max_chunksize** assures that multi-threading is happening in smaller chunks. If
someone wants all items to be processed, using read(0), the whole task would go to
one worker, as well as dependent tasks. If you want finer granularity , you can
specify this here, causing chunks to be no larger than max_chunksize
* **apply_single** if True, default True, individual items will be given to the
worker function. If False, a list of possibly multiple items will be passed
instead.
"""
__slots__ = ( '_read', # method to yield items to process
'_out_writer', # output write channel
'_exc', # exception caught
'_done', # True if we are done
'_num_writers', # number of concurrent writers
'_wlock', # lock for the above
'fun', # function to call with items read
'min_count', # minimum amount of items to produce, None means no override
'max_chunksize', # maximium amount of items to process per process call
'apply_single' # apply single items even if multiple where read
)
def __init__(self, id, fun, apply_single=True, min_count=None, max_chunksize=0,
writer=None):
Node.__init__(self, id)
self._read = None # to be set by subclasss
self._out_writer = writer
self._exc = None
self._done = False
self._num_writers = 0
self._wlock = threading.Lock()
self.fun = fun
self.min_count = None
self.max_chunksize = 0 # not set
self.apply_single = apply_single
def is_done(self):
""":return: True if we are finished processing"""
return self._done
def set_done(self):
"""Set ourselves to being done, has we have completed the processing"""
self._done = True
def set_writer(self, writer):
"""Set the write channel to the given one"""
self._out_writer = writer
def writer(self):
"""
:return: a proxy to our write channel or None if non is set
:note: you must not hold a reference to our write channel when the
task is being processed. This would cause the write channel never
to be closed as the task will think there is still another instance
being processed which can close the channel once it is done.
In the worst case, this will block your reads."""
if self._out_writer is None:
return None
return self._out_writer
def close(self):
"""A closed task will close its channel to assure the readers will wake up
:note: its safe to call this method multiple times"""
self._out_writer.close()
def is_closed(self):
""":return: True if the task's write channel is closed"""
return self._out_writer.closed()
def error(self):
""":return: Exception caught during last processing or None"""
return self._exc
def process(self, count=0):
"""Process count items and send the result individually to the output channel"""
# first thing: increment the writer count - other tasks must be able
# to respond properly ( even if it turns out we don't need it later )
self._wlock.acquire()
self._num_writers += 1
self._wlock.release()
items = self._read(count)
try:
try:
if items:
write = self._out_writer.write
if self.apply_single:
for item in items:
rval = self.fun(item)
write(rval)
# END for each item
else:
# shouldn't apply single be the default anyway ?
# The task designers should chunk them up in advance
rvals = self.fun(items)
for rval in rvals:
write(rval)
# END handle single apply
# END if there is anything to do
finally:
self._wlock.acquire()
self._num_writers -= 1
self._wlock.release()
# END handle writer count
except Exception as e:
# be sure our task is not scheduled again
self.set_done()
# PROBLEM: We have failed to create at least one item, hence its not
# garantueed that enough items will be produced for a possibly blocking
# client on the other end. This is why we have no other choice but
# to close the channel, preventing the possibility of blocking.
# This implies that dependent tasks will go down with us, but that is
# just the right thing to do of course - one loose link in the chain ...
# Other chunks of our kind currently being processed will then
# fail to write to the channel and fail as well
self.close()
# If some other chunk of our Task had an error, the channel will be closed
# This is not an issue, just be sure we don't overwrite the original
# exception with the ReadOnly error that would be emitted in that case.
# We imply that ReadOnly is exclusive to us, as it won't be an error
# if the user emits it
if not isinstance(e, ReadOnly):
self._exc = e
# END set error flag
# END exception handling
# if we didn't get all demanded items, which is also the case if count is 0
# we have depleted the input channel and are done
# We could check our output channel for how many items we have and put that
# into the equation, but whats important is that we were asked to produce
# count items.
if not items or len(items) != count:
self.set_done()
# END handle done state
# If we appear to be the only one left with our output channel, and are
# done ( this could have been set in another thread as well ), make
# sure to close the output channel.
# Waiting with this to be the last one helps to keep the
# write-channel writable longer
# The count is: 1 = wc itself, 2 = first reader channel, + x for every
# thread having its copy on the stack
# + 1 for the instance we provide to refcount
# Soft close, so others can continue writing their results
if self.is_done():
self._wlock.acquire()
try:
if self._num_writers == 0:
self.close()
# END handle writers
finally:
self._wlock.release()
# END assure lock release
# END handle channel closure
#{ Configuration
class ThreadTaskBase(object):
"""Describes tasks which can be used with theaded pools"""
pass
class IteratorTaskBase(Task):
"""Implements a task which processes items from an iterable in a multi-processing
safe manner"""
__slots__ = tuple()
def __init__(self, iterator, *args, **kwargs):
Task.__init__(self, *args, **kwargs)
self._read = IteratorReader(iterator).read
# defaults to returning our items unchanged
if self.fun is None:
self.fun = lambda item: item
class IteratorThreadTask(IteratorTaskBase, ThreadTaskBase):
"""An input iterator for threaded pools"""
lock_type = threading.Lock
class ChannelThreadTask(Task, ThreadTaskBase):
"""Uses an input channel as source for reading items
For instantiation, it takes all arguments of its base, the first one needs
to be the input channel to read from though."""
__slots__ = "_pool_ref"
def __init__(self, in_reader, *args, **kwargs):
Task.__init__(self, *args, **kwargs)
self._read = in_reader.read
self._pool_ref = None
#{ Internal Interface
def reader(self):
""":return: input channel from which we read"""
# the instance is bound in its instance method - lets use this to keep
# the refcount at one ( per consumer )
return self._read.__self__
def set_read(self, read):
"""Adjust the read method to the given one"""
self._read = read
def set_pool(self, pool):
self._pool_ref = weakref.ref(pool)
def pool(self):
""":return: pool we are attached to, or None"""
if self._pool_ref is None:
return None
return self._pool_ref()
#} END intenral interface
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