Current File : //proc/thread-self/root/usr/lib/python3.12/multiprocessing/pool.py
#
# Module providing the `Pool` class for managing a process pool
#
# multiprocessing/pool.py
#
# Copyright (c) 2006-2008, R Oudkerk
# Licensed to PSF under a Contributor Agreement.
#

__all__ = ['Pool', 'ThreadPool']

#
# Imports
#

import collections
import itertools
import os
import queue
import threading
import time
import traceback
import types
import warnings

# If threading is available then ThreadPool should be provided.  Therefore
# we avoid top-level imports which are liable to fail on some systems.
from . import util
from . import get_context, TimeoutError
from .connection import wait

#
# Constants representing the state of a pool
#

INIT = "INIT"
RUN = "RUN"
CLOSE = "CLOSE"
TERMINATE = "TERMINATE"

#
# Miscellaneous
#

job_counter = itertools.count()

def mapstar(args):
    return list(map(*args))

def starmapstar(args):
    return list(itertools.starmap(args[0], args[1]))

#
# Hack to embed stringification of remote traceback in local traceback
#

class RemoteTraceback(Exception):
    def __init__(self, tb):
        self.tb = tb
    def __str__(self):
        return self.tb

class ExceptionWithTraceback:
    def __init__(self, exc, tb):
        tb = traceback.format_exception(type(exc), exc, tb)
        tb = ''.join(tb)
        self.exc = exc
        self.tb = '\n"""\n%s"""' % tb
    def __reduce__(self):
        return rebuild_exc, (self.exc, self.tb)

def rebuild_exc(exc, tb):
    exc.__cause__ = RemoteTraceback(tb)
    return exc

#
# Code run by worker processes
#

class MaybeEncodingError(Exception):
    """Wraps possible unpickleable errors, so they can be
    safely sent through the socket."""

    def __init__(self, exc, value):
        self.exc = repr(exc)
        self.value = repr(value)
        super(MaybeEncodingError, self).__init__(self.exc, self.value)

    def __str__(self):
        return "Error sending result: '%s'. Reason: '%s'" % (self.value,
                                                             self.exc)

    def __repr__(self):
        return "<%s: %s>" % (self.__class__.__name__, self)


def worker(inqueue, outqueue, initializer=None, initargs=(), maxtasks=None,
           wrap_exception=False):
    if (maxtasks is not None) and not (isinstance(maxtasks, int)
                                       and maxtasks >= 1):
        raise AssertionError("Maxtasks {!r} is not valid".format(maxtasks))
    put = outqueue.put
    get = inqueue.get
    if hasattr(inqueue, '_writer'):
        inqueue._writer.close()
        outqueue._reader.close()

    if initializer is not None:
        initializer(*initargs)

    completed = 0
    while maxtasks is None or (maxtasks and completed < maxtasks):
        try:
            task = get()
        except (EOFError, OSError):
            util.debug('worker got EOFError or OSError -- exiting')
            break

        if task is None:
            util.debug('worker got sentinel -- exiting')
            break

        job, i, func, args, kwds = task
        try:
            result = (True, func(*args, **kwds))
        except Exception as e:
            if wrap_exception and func is not _helper_reraises_exception:
                e = ExceptionWithTraceback(e, e.__traceback__)
            result = (False, e)
        try:
            put((job, i, result))
        except Exception as e:
            wrapped = MaybeEncodingError(e, result[1])
            util.debug("Possible encoding error while sending result: %s" % (
                wrapped))
            put((job, i, (False, wrapped)))

        task = job = result = func = args = kwds = None
        completed += 1
    util.debug('worker exiting after %d tasks' % completed)

def _helper_reraises_exception(ex):
    'Pickle-able helper function for use by _guarded_task_generation.'
    raise ex

#
# Class representing a process pool
#

class _PoolCache(dict):
    """
    Class that implements a cache for the Pool class that will notify
    the pool management threads every time the cache is emptied. The
    notification is done by the use of a queue that is provided when
    instantiating the cache.
    """
    def __init__(self, /, *args, notifier=None, **kwds):
        self.notifier = notifier
        super().__init__(*args, **kwds)

    def __delitem__(self, item):
        super().__delitem__(item)

        # Notify that the cache is empty. This is important because the
        # pool keeps maintaining workers until the cache gets drained. This
        # eliminates a race condition in which a task is finished after the
        # the pool's _handle_workers method has enter another iteration of the
        # loop. In this situation, the only event that can wake up the pool
        # is the cache to be emptied (no more tasks available).
        if not self:
            self.notifier.put(None)

class Pool(object):
    '''
    Class which supports an async version of applying functions to arguments.
    '''
    _wrap_exception = True

    @staticmethod
    def Process(ctx, *args, **kwds):
        return ctx.Process(*args, **kwds)

    def __init__(self, processes=None, initializer=None, initargs=(),
                 maxtasksperchild=None, context=None):
        # Attributes initialized early to make sure that they exist in
        # __del__() if __init__() raises an exception
        self._pool = []
        self._state = INIT

        self._ctx = context or get_context()
        self._setup_queues()
        self._taskqueue = queue.SimpleQueue()
        # The _change_notifier queue exist to wake up self._handle_workers()
        # when the cache (self._cache) is empty or when there is a change in
        # the _state variable of the thread that runs _handle_workers.
        self._change_notifier = self._ctx.SimpleQueue()
        self._cache = _PoolCache(notifier=self._change_notifier)
        self._maxtasksperchild = maxtasksperchild
        self._initializer = initializer
        self._initargs = initargs

        if processes is None:
            processes = os.cpu_count() or 1
        if processes < 1:
            raise ValueError("Number of processes must be at least 1")
        if maxtasksperchild is not None:
            if not isinstance(maxtasksperchild, int) or maxtasksperchild <= 0:
                raise ValueError("maxtasksperchild must be a positive int or None")

        if initializer is not None and not callable(initializer):
            raise TypeError('initializer must be a callable')

        self._processes = processes
        try:
            self._repopulate_pool()
        except Exception:
            for p in self._pool:
                if p.exitcode is None:
                    p.terminate()
            for p in self._pool:
                p.join()
            raise

        sentinels = self._get_sentinels()

        self._worker_handler = threading.Thread(
            target=Pool._handle_workers,
            args=(self._cache, self._taskqueue, self._ctx, self.Process,
                  self._processes, self._pool, self._inqueue, self._outqueue,
                  self._initializer, self._initargs, self._maxtasksperchild,
                  self._wrap_exception, sentinels, self._change_notifier)
            )
        self._worker_handler.daemon = True
        self._worker_handler._state = RUN
        self._worker_handler.start()


        self._task_handler = threading.Thread(
            target=Pool._handle_tasks,
            args=(self._taskqueue, self._quick_put, self._outqueue,
                  self._pool, self._cache)
            )
        self._task_handler.daemon = True
        self._task_handler._state = RUN
        self._task_handler.start()

        self._result_handler = threading.Thread(
            target=Pool._handle_results,
            args=(self._outqueue, self._quick_get, self._cache)
            )
        self._result_handler.daemon = True
        self._result_handler._state = RUN
        self._result_handler.start()

        self._terminate = util.Finalize(
            self, self._terminate_pool,
            args=(self._taskqueue, self._inqueue, self._outqueue, self._pool,
                  self._change_notifier, self._worker_handler, self._task_handler,
                  self._result_handler, self._cache),
            exitpriority=15
            )
        self._state = RUN

    # Copy globals as function locals to make sure that they are available
    # during Python shutdown when the Pool is destroyed.
    def __del__(self, _warn=warnings.warn, RUN=RUN):
        if self._state == RUN:
            _warn(f"unclosed running multiprocessing pool {self!r}",
                  ResourceWarning, source=self)
            if getattr(self, '_change_notifier', None) is not None:
                self._change_notifier.put(None)

    def __repr__(self):
        cls = self.__class__
        return (f'<{cls.__module__}.{cls.__qualname__} '
                f'state={self._state} '
                f'pool_size={len(self._pool)}>')

    def _get_sentinels(self):
        task_queue_sentinels = [self._outqueue._reader]
        self_notifier_sentinels = [self._change_notifier._reader]
        return [*task_queue_sentinels, *self_notifier_sentinels]

    @staticmethod
    def _get_worker_sentinels(workers):
        return [worker.sentinel for worker in
                workers if hasattr(worker, "sentinel")]

    @staticmethod
    def _join_exited_workers(pool):
        """Cleanup after any worker processes which have exited due to reaching
        their specified lifetime.  Returns True if any workers were cleaned up.
        """
        cleaned = False
        for i in reversed(range(len(pool))):
            worker = pool[i]
            if worker.exitcode is not None:
                # worker exited
                util.debug('cleaning up worker %d' % i)
                worker.join()
                cleaned = True
                del pool[i]
        return cleaned

    def _repopulate_pool(self):
        return self._repopulate_pool_static(self._ctx, self.Process,
                                            self._processes,
                                            self._pool, self._inqueue,
                                            self._outqueue, self._initializer,
                                            self._initargs,
                                            self._maxtasksperchild,
                                            self._wrap_exception)

    @staticmethod
    def _repopulate_pool_static(ctx, Process, processes, pool, inqueue,
                                outqueue, initializer, initargs,
                                maxtasksperchild, wrap_exception):
        """Bring the number of pool processes up to the specified number,
        for use after reaping workers which have exited.
        """
        for i in range(processes - len(pool)):
            w = Process(ctx, target=worker,
                        args=(inqueue, outqueue,
                              initializer,
                              initargs, maxtasksperchild,
                              wrap_exception))
            w.name = w.name.replace('Process', 'PoolWorker')
            w.daemon = True
            w.start()
            pool.append(w)
            util.debug('added worker')

    @staticmethod
    def _maintain_pool(ctx, Process, processes, pool, inqueue, outqueue,
                       initializer, initargs, maxtasksperchild,
                       wrap_exception):
        """Clean up any exited workers and start replacements for them.
        """
        if Pool._join_exited_workers(pool):
            Pool._repopulate_pool_static(ctx, Process, processes, pool,
                                         inqueue, outqueue, initializer,
                                         initargs, maxtasksperchild,
                                         wrap_exception)

    def _setup_queues(self):
        self._inqueue = self._ctx.SimpleQueue()
        self._outqueue = self._ctx.SimpleQueue()
        self._quick_put = self._inqueue._writer.send
        self._quick_get = self._outqueue._reader.recv

    def _check_running(self):
        if self._state != RUN:
            raise ValueError("Pool not running")

    def apply(self, func, args=(), kwds={}):
        '''
        Equivalent of `func(*args, **kwds)`.
        Pool must be running.
        '''
        return self.apply_async(func, args, kwds).get()

    def map(self, func, iterable, chunksize=None):
        '''
        Apply `func` to each element in `iterable`, collecting the results
        in a list that is returned.
        '''
        return self._map_async(func, iterable, mapstar, chunksize).get()

    def starmap(self, func, iterable, chunksize=None):
        '''
        Like `map()` method but the elements of the `iterable` are expected to
        be iterables as well and will be unpacked as arguments. Hence
        `func` and (a, b) becomes func(a, b).
        '''
        return self._map_async(func, iterable, starmapstar, chunksize).get()

    def starmap_async(self, func, iterable, chunksize=None, callback=None,
            error_callback=None):
        '''
        Asynchronous version of `starmap()` method.
        '''
        return self._map_async(func, iterable, starmapstar, chunksize,
                               callback, error_callback)

    def _guarded_task_generation(self, result_job, func, iterable):
        '''Provides a generator of tasks for imap and imap_unordered with
        appropriate handling for iterables which throw exceptions during
        iteration.'''
        try:
            i = -1
            for i, x in enumerate(iterable):
                yield (result_job, i, func, (x,), {})
        except Exception as e:
            yield (result_job, i+1, _helper_reraises_exception, (e,), {})

    def imap(self, func, iterable, chunksize=1):
        '''
        Equivalent of `map()` -- can be MUCH slower than `Pool.map()`.
        '''
        self._check_running()
        if chunksize == 1:
            result = IMapIterator(self)
            self._taskqueue.put(
                (
                    self._guarded_task_generation(result._job, func, iterable),
                    result._set_length
                ))
            return result
        else:
            if chunksize < 1:
                raise ValueError(
                    "Chunksize must be 1+, not {0:n}".format(
                        chunksize))
            task_batches = Pool._get_tasks(func, iterable, chunksize)
            result = IMapIterator(self)
            self._taskqueue.put(
                (
                    self._guarded_task_generation(result._job,
                                                  mapstar,
                                                  task_batches),
                    result._set_length
                ))
            return (item for chunk in result for item in chunk)

    def imap_unordered(self, func, iterable, chunksize=1):
        '''
        Like `imap()` method but ordering of results is arbitrary.
        '''
        self._check_running()
        if chunksize == 1:
            result = IMapUnorderedIterator(self)
            self._taskqueue.put(
                (
                    self._guarded_task_generation(result._job, func, iterable),
                    result._set_length
                ))
            return result
        else:
            if chunksize < 1:
                raise ValueError(
                    "Chunksize must be 1+, not {0!r}".format(chunksize))
            task_batches = Pool._get_tasks(func, iterable, chunksize)
            result = IMapUnorderedIterator(self)
            self._taskqueue.put(
                (
                    self._guarded_task_generation(result._job,
                                                  mapstar,
                                                  task_batches),
                    result._set_length
                ))
            return (item for chunk in result for item in chunk)

    def apply_async(self, func, args=(), kwds={}, callback=None,
            error_callback=None):
        '''
        Asynchronous version of `apply()` method.
        '''
        self._check_running()
        result = ApplyResult(self, callback, error_callback)
        self._taskqueue.put(([(result._job, 0, func, args, kwds)], None))
        return result

    def map_async(self, func, iterable, chunksize=None, callback=None,
            error_callback=None):
        '''
        Asynchronous version of `map()` method.
        '''
        return self._map_async(func, iterable, mapstar, chunksize, callback,
            error_callback)

    def _map_async(self, func, iterable, mapper, chunksize=None, callback=None,
            error_callback=None):
        '''
        Helper function to implement map, starmap and their async counterparts.
        '''
        self._check_running()
        if not hasattr(iterable, '__len__'):
            iterable = list(iterable)

        if chunksize is None:
            chunksize, extra = divmod(len(iterable), len(self._pool) * 4)
            if extra:
                chunksize += 1
        if len(iterable) == 0:
            chunksize = 0

        task_batches = Pool._get_tasks(func, iterable, chunksize)
        result = MapResult(self, chunksize, len(iterable), callback,
                           error_callback=error_callback)
        self._taskqueue.put(
            (
                self._guarded_task_generation(result._job,
                                              mapper,
                                              task_batches),
                None
            )
        )
        return result

    @staticmethod
    def _wait_for_updates(sentinels, change_notifier, timeout=None):
        wait(sentinels, timeout=timeout)
        while not change_notifier.empty():
            change_notifier.get()

    @classmethod
    def _handle_workers(cls, cache, taskqueue, ctx, Process, processes,
                        pool, inqueue, outqueue, initializer, initargs,
                        maxtasksperchild, wrap_exception, sentinels,
                        change_notifier):
        thread = threading.current_thread()

        # Keep maintaining workers until the cache gets drained, unless the pool
        # is terminated.
        while thread._state == RUN or (cache and thread._state != TERMINATE):
            cls._maintain_pool(ctx, Process, processes, pool, inqueue,
                               outqueue, initializer, initargs,
                               maxtasksperchild, wrap_exception)

            current_sentinels = [*cls._get_worker_sentinels(pool), *sentinels]

            cls._wait_for_updates(current_sentinels, change_notifier)
        # send sentinel to stop workers
        taskqueue.put(None)
        util.debug('worker handler exiting')

    @staticmethod
    def _handle_tasks(taskqueue, put, outqueue, pool, cache):
        thread = threading.current_thread()

        for taskseq, set_length in iter(taskqueue.get, None):
            task = None
            try:
                # iterating taskseq cannot fail
                for task in taskseq:
                    if thread._state != RUN:
                        util.debug('task handler found thread._state != RUN')
                        break
                    try:
                        put(task)
                    except Exception as e:
                        job, idx = task[:2]
                        try:
                            cache[job]._set(idx, (False, e))
                        except KeyError:
                            pass
                else:
                    if set_length:
                        util.debug('doing set_length()')
                        idx = task[1] if task else -1
                        set_length(idx + 1)
                    continue
                break
            finally:
                task = taskseq = job = None
        else:
            util.debug('task handler got sentinel')

        try:
            # tell result handler to finish when cache is empty
            util.debug('task handler sending sentinel to result handler')
            outqueue.put(None)

            # tell workers there is no more work
            util.debug('task handler sending sentinel to workers')
            for p in pool:
                put(None)
        except OSError:
            util.debug('task handler got OSError when sending sentinels')

        util.debug('task handler exiting')

    @staticmethod
    def _handle_results(outqueue, get, cache):
        thread = threading.current_thread()

        while 1:
            try:
                task = get()
            except (OSError, EOFError):
                util.debug('result handler got EOFError/OSError -- exiting')
                return

            if thread._state != RUN:
                assert thread._state == TERMINATE, "Thread not in TERMINATE"
                util.debug('result handler found thread._state=TERMINATE')
                break

            if task is None:
                util.debug('result handler got sentinel')
                break

            job, i, obj = task
            try:
                cache[job]._set(i, obj)
            except KeyError:
                pass
            task = job = obj = None

        while cache and thread._state != TERMINATE:
            try:
                task = get()
            except (OSError, EOFError):
                util.debug('result handler got EOFError/OSError -- exiting')
                return

            if task is None:
                util.debug('result handler ignoring extra sentinel')
                continue
            job, i, obj = task
            try:
                cache[job]._set(i, obj)
            except KeyError:
                pass
            task = job = obj = None

        if hasattr(outqueue, '_reader'):
            util.debug('ensuring that outqueue is not full')
            # If we don't make room available in outqueue then
            # attempts to add the sentinel (None) to outqueue may
            # block.  There is guaranteed to be no more than 2 sentinels.
            try:
                for i in range(10):
                    if not outqueue._reader.poll():
                        break
                    get()
            except (OSError, EOFError):
                pass

        util.debug('result handler exiting: len(cache)=%s, thread._state=%s',
              len(cache), thread._state)

    @staticmethod
    def _get_tasks(func, it, size):
        it = iter(it)
        while 1:
            x = tuple(itertools.islice(it, size))
            if not x:
                return
            yield (func, x)

    def __reduce__(self):
        raise NotImplementedError(
              'pool objects cannot be passed between processes or pickled'
              )

    def close(self):
        util.debug('closing pool')
        if self._state == RUN:
            self._state = CLOSE
            self._worker_handler._state = CLOSE
            self._change_notifier.put(None)

    def terminate(self):
        util.debug('terminating pool')
        self._state = TERMINATE
        self._terminate()

    def join(self):
        util.debug('joining pool')
        if self._state == RUN:
            raise ValueError("Pool is still running")
        elif self._state not in (CLOSE, TERMINATE):
            raise ValueError("In unknown state")
        self._worker_handler.join()
        self._task_handler.join()
        self._result_handler.join()
        for p in self._pool:
            p.join()

    @staticmethod
    def _help_stuff_finish(inqueue, task_handler, size):
        # task_handler may be blocked trying to put items on inqueue
        util.debug('removing tasks from inqueue until task handler finished')
        inqueue._rlock.acquire()
        while task_handler.is_alive() and inqueue._reader.poll():
            inqueue._reader.recv()
            time.sleep(0)

    @classmethod
    def _terminate_pool(cls, taskqueue, inqueue, outqueue, pool, change_notifier,
                        worker_handler, task_handler, result_handler, cache):
        # this is guaranteed to only be called once
        util.debug('finalizing pool')

        # Notify that the worker_handler state has been changed so the
        # _handle_workers loop can be unblocked (and exited) in order to
        # send the finalization sentinel all the workers.
        worker_handler._state = TERMINATE
        change_notifier.put(None)

        task_handler._state = TERMINATE

        util.debug('helping task handler/workers to finish')
        cls._help_stuff_finish(inqueue, task_handler, len(pool))

        if (not result_handler.is_alive()) and (len(cache) != 0):
            raise AssertionError(
                "Cannot have cache with result_handler not alive")

        result_handler._state = TERMINATE
        change_notifier.put(None)
        outqueue.put(None)                  # sentinel

        # We must wait for the worker handler to exit before terminating
        # workers because we don't want workers to be restarted behind our back.
        util.debug('joining worker handler')
        if threading.current_thread() is not worker_handler:
            worker_handler.join()

        # Terminate workers which haven't already finished.
        if pool and hasattr(pool[0], 'terminate'):
            util.debug('terminating workers')
            for p in pool:
                if p.exitcode is None:
                    p.terminate()

        util.debug('joining task handler')
        if threading.current_thread() is not task_handler:
            task_handler.join()

        util.debug('joining result handler')
        if threading.current_thread() is not result_handler:
            result_handler.join()

        if pool and hasattr(pool[0], 'terminate'):
            util.debug('joining pool workers')
            for p in pool:
                if p.is_alive():
                    # worker has not yet exited
                    util.debug('cleaning up worker %d' % p.pid)
                    p.join()

    def __enter__(self):
        self._check_running()
        return self

    def __exit__(self, exc_type, exc_val, exc_tb):
        self.terminate()

#
# Class whose instances are returned by `Pool.apply_async()`
#

class ApplyResult(object):

    def __init__(self, pool, callback, error_callback):
        self._pool = pool
        self._event = threading.Event()
        self._job = next(job_counter)
        self._cache = pool._cache
        self._callback = callback
        self._error_callback = error_callback
        self._cache[self._job] = self

    def ready(self):
        return self._event.is_set()

    def successful(self):
        if not self.ready():
            raise ValueError("{0!r} not ready".format(self))
        return self._success

    def wait(self, timeout=None):
        self._event.wait(timeout)

    def get(self, timeout=None):
        self.wait(timeout)
        if not self.ready():
            raise TimeoutError
        if self._success:
            return self._value
        else:
            raise self._value

    def _set(self, i, obj):
        self._success, self._value = obj
        if self._callback and self._success:
            self._callback(self._value)
        if self._error_callback and not self._success:
            self._error_callback(self._value)
        self._event.set()
        del self._cache[self._job]
        self._pool = None

    __class_getitem__ = classmethod(types.GenericAlias)

AsyncResult = ApplyResult       # create alias -- see #17805

#
# Class whose instances are returned by `Pool.map_async()`
#

class MapResult(ApplyResult):

    def __init__(self, pool, chunksize, length, callback, error_callback):
        ApplyResult.__init__(self, pool, callback,
                             error_callback=error_callback)
        self._success = True
        self._value = [None] * length
        self._chunksize = chunksize
        if chunksize <= 0:
            self._number_left = 0
            self._event.set()
            del self._cache[self._job]
        else:
            self._number_left = length//chunksize + bool(length % chunksize)

    def _set(self, i, success_result):
        self._number_left -= 1
        success, result = success_result
        if success and self._success:
            self._value[i*self._chunksize:(i+1)*self._chunksize] = result
            if self._number_left == 0:
                if self._callback:
                    self._callback(self._value)
                del self._cache[self._job]
                self._event.set()
                self._pool = None
        else:
            if not success and self._success:
                # only store first exception
                self._success = False
                self._value = result
            if self._number_left == 0:
                # only consider the result ready once all jobs are done
                if self._error_callback:
                    self._error_callback(self._value)
                del self._cache[self._job]
                self._event.set()
                self._pool = None

#
# Class whose instances are returned by `Pool.imap()`
#

class IMapIterator(object):

    def __init__(self, pool):
        self._pool = pool
        self._cond = threading.Condition(threading.Lock())
        self._job = next(job_counter)
        self._cache = pool._cache
        self._items = collections.deque()
        self._index = 0
        self._length = None
        self._unsorted = {}
        self._cache[self._job] = self

    def __iter__(self):
        return self

    def next(self, timeout=None):
        with self._cond:
            try:
                item = self._items.popleft()
            except IndexError:
                if self._index == self._length:
                    self._pool = None
                    raise StopIteration from None
                self._cond.wait(timeout)
                try:
                    item = self._items.popleft()
                except IndexError:
                    if self._index == self._length:
                        self._pool = None
                        raise StopIteration from None
                    raise TimeoutError from None

        success, value = item
        if success:
            return value
        raise value

    __next__ = next                    # XXX

    def _set(self, i, obj):
        with self._cond:
            if self._index == i:
                self._items.append(obj)
                self._index += 1
                while self._index in self._unsorted:
                    obj = self._unsorted.pop(self._index)
                    self._items.append(obj)
                    self._index += 1
                self._cond.notify()
            else:
                self._unsorted[i] = obj

            if self._index == self._length:
                del self._cache[self._job]
                self._pool = None

    def _set_length(self, length):
        with self._cond:
            self._length = length
            if self._index == self._length:
                self._cond.notify()
                del self._cache[self._job]
                self._pool = None

#
# Class whose instances are returned by `Pool.imap_unordered()`
#

class IMapUnorderedIterator(IMapIterator):

    def _set(self, i, obj):
        with self._cond:
            self._items.append(obj)
            self._index += 1
            self._cond.notify()
            if self._index == self._length:
                del self._cache[self._job]
                self._pool = None

#
#
#

class ThreadPool(Pool):
    _wrap_exception = False

    @staticmethod
    def Process(ctx, *args, **kwds):
        from .dummy import Process
        return Process(*args, **kwds)

    def __init__(self, processes=None, initializer=None, initargs=()):
        Pool.__init__(self, processes, initializer, initargs)

    def _setup_queues(self):
        self._inqueue = queue.SimpleQueue()
        self._outqueue = queue.SimpleQueue()
        self._quick_put = self._inqueue.put
        self._quick_get = self._outqueue.get

    def _get_sentinels(self):
        return [self._change_notifier._reader]

    @staticmethod
    def _get_worker_sentinels(workers):
        return []

    @staticmethod
    def _help_stuff_finish(inqueue, task_handler, size):
        # drain inqueue, and put sentinels at its head to make workers finish
        try:
            while True:
                inqueue.get(block=False)
        except queue.Empty:
            pass
        for i in range(size):
            inqueue.put(None)

    def _wait_for_updates(self, sentinels, change_notifier, timeout):
        time.sleep(timeout)
¿Qué es la limpieza dental de perros? - Clínica veterinaria


Es la eliminación del sarro y la placa adherida a la superficie de los dientes mediante un equipo de ultrasonidos que garantiza la integridad de las piezas dentales a la vez que elimina en profundidad cualquier resto de suciedad.

A continuación se procede al pulido de los dientes mediante una fresa especial que elimina la placa bacteriana y devuelve a los dientes el aspecto sano que deben tener.

Una vez terminado todo el proceso, se mantiene al perro en observación hasta que se despierta de la anestesia, bajo la atenta supervisión de un veterinario.

¿Cada cuánto tiempo tengo que hacerle una limpieza dental a mi perro?

A partir de cierta edad, los perros pueden necesitar una limpieza dental anual o bianual. Depende de cada caso. En líneas generales, puede decirse que los perros de razas pequeñas suelen acumular más sarro y suelen necesitar una atención mayor en cuanto a higiene dental.


Riesgos de una mala higiene


Los riesgos más evidentes de una mala higiene dental en los perros son los siguientes:

  • Cuando la acumulación de sarro no se trata, se puede producir una inflamación y retracción de las encías que puede descalzar el diente y provocar caídas.
  • Mal aliento (halitosis).
  • Sarro perros
  • Puede ir a más
  • Las bacterias de la placa pueden trasladarse a través del torrente circulatorio a órganos vitales como el corazón ocasionando problemas de endocarditis en las válvulas. Las bacterias pueden incluso acantonarse en huesos (La osteomielitis es la infección ósea, tanto cortical como medular) provocando mucho dolor y una artritis séptica).

¿Cómo se forma el sarro?

El sarro es la calcificación de la placa dental. Los restos de alimentos, junto con las bacterias presentes en la boca, van a formar la placa bacteriana o placa dental. Si la placa no se retira, al mezclarse con la saliva y los minerales presentes en ella, reaccionará formando una costra. La placa se calcifica y se forma el sarro.

El sarro, cuando se forma, es de color blanquecino pero a medida que pasa el tiempo se va poniendo amarillo y luego marrón.

Síntomas de una pobre higiene dental
La señal más obvia de una mala salud dental canina es el mal aliento.

Sin embargo, a veces no es tan fácil de detectar
Y hay perros que no se dejan abrir la boca por su dueño. Por ejemplo…

Recientemente nos trajeron a la clínica a un perro que parpadeaba de un ojo y decía su dueño que le picaba un lado de la cara. Tenía molestias y dificultad para comer, lo que había llevado a sus dueños a comprarle comida blanda (que suele ser un poco más cara y llevar más contenido en grasa) durante medio año. Después de una exploración oftalmológica, nos dimos cuenta de que el ojo tenía una úlcera en la córnea probablemente de rascarse . Además, el canto lateral del ojo estaba inflamado. Tenía lo que en humanos llamamos flemón pero como era un perro de pelo largo, no se le notaba a simple vista. Al abrirle la boca nos llamó la atención el ver una muela llena de sarro. Le realizamos una radiografía y encontramos una fístula que llegaba hasta la parte inferior del ojo.

Le tuvimos que extraer la muela. Tras esto, el ojo se curó completamente con unos colirios y una lentilla protectora de úlcera. Afortunadamente, la úlcera no profundizó y no perforó el ojo. Ahora el perro come perfectamente a pesar de haber perdido una muela.

¿Cómo mantener la higiene dental de tu perro?
Hay varias maneras de prevenir problemas derivados de la salud dental de tu perro.

Limpiezas de dientes en casa
Es recomendable limpiar los dientes de tu perro semanal o diariamente si se puede. Existe una gran variedad de productos que se pueden utilizar:

Pastas de dientes.
Cepillos de dientes o dedales para el dedo índice, que hacen más fácil la limpieza.
Colutorios para echar en agua de bebida o directamente sobre el diente en líquido o en spray.

En la Clínica Tus Veterinarios enseñamos a nuestros clientes a tomar el hábito de limpiar los dientes de sus perros desde que son cachorros. Esto responde a nuestro compromiso con la prevención de enfermedades caninas.

Hoy en día tenemos muchos clientes que limpian los dientes todos los días a su mascota, y como resultado, se ahorran el dinero de hacer limpiezas dentales profesionales y consiguen una mejor salud de su perro.


Limpiezas dentales profesionales de perros y gatos

Recomendamos hacer una limpieza dental especializada anualmente. La realizamos con un aparato de ultrasonidos que utiliza agua para quitar el sarro. Después, procedemos a pulir los dientes con un cepillo de alta velocidad y una pasta especial. Hacemos esto para proteger el esmalte.

La frecuencia de limpiezas dentales necesaria varía mucho entre razas. En general, las razas grandes tienen buena calidad de esmalte, por lo que no necesitan hacerlo tan a menudo e incluso pueden pasarse la vida sin requerir una limpieza. Sin embargo, razas pequeñas como el Yorkshire o el Maltés, deben hacérselas todos los años desde cachorros si se quiere conservar sus piezas dentales.

Otro factor fundamental es la calidad del pienso. Algunas marcas han diseñado croquetas que limpian la superficie del diente y de la muela al masticarse.

Ultrasonido para perros

¿Se necesita anestesia para las limpiezas dentales de perros y gatos?

La limpieza dental en perros no es una técnica que pueda practicarse sin anestesia general , aunque hay veces que los propietarios no quieren anestesiar y si tiene poco sarro y el perro es muy bueno se puede intentar…… , pero no se va a poder pulir ni acceder a todas la zona de la boca …. Además los limpiadores dentales van a irrigar agua y hay riesgo de aspiración a vías respiratorias si no se realiza una anestesia correcta con intubación traqueal . En resumen , sin anestesia no se va hacer una correcta limpieza dental.

Tampoco sirve la sedación ya que necesitamos que el animal esté totalmente quieto, y el veterinario tenga un acceso completo a todas sus piezas dentales y encías.

Alimentos para la limpieza dental

Hay que tener cierto cuidado a la hora de comprar determinados alimentos porque no todos son saludables. Algunos tienen demasiado contenido graso, que en exceso puede causar problemas cardiovasculares y obesidad.

Los mejores alimentos para los dientes son aquellos que están elaborados por empresas farmacéuticas y llevan componentes químicos con tratamientos específicos para el diente del perro. Esto implica no solo limpieza a través de la acción mecánica de morder sino también un tratamiento antibacteriano para prevenir el sarro.

Conclusión

Si eres como la mayoría de dueños, por falta de tiempo , es probable que no estés prestando la suficiente atención a la limpieza dental de tu perro. Por eso te animamos a que comiences a limpiar los dientes de tu perro y consideres atender a su higiene bucal con frecuencia.

Estas simples medidas pueden conllevar a que tu perro tenga una vida más larga y mucho más saludable.

Si te resulta imposible introducir un cepillo de dientes a tu perro en la boca, pásate con él por clínica Tus Veterinarios y te explicamos cómo hacerlo.

Necesitas hacer una limpieza dental profesional a tu mascota?
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