Luke在以下位置找到了一种解决方法：https://github.com/lukebakken/pika-1402/blob/lukebakken/pika-1402/test_pika_blockthread.py
他用以下代码更改了示例代码：

• 通过删除“通过队列进行批处理”代码进行了一些简化，因为它与当前问题无关
• 已将Pika连接移动到其自己的线程
• 不使用消费回调，而是转到生成器样式的for循环，该循环允许检查是否请求退出。这也可以通过SelectConnection和计时器来完成。

通过Queue添加回批处理的示例代码，与原始代码匹配的代码如下：

# from https://github.com/lukebakken/pika-1402/blob/lukebakken/pika-1402/test_pika_blockthread.py
# import packages
# connect to Rabbit MQ
import pika
import pika.credentials
import pika.spec
# intercept stop signal
import signal
# print exception
# import traceback
# threading
import functools
import threading
from queue import Queue

# logs time
import datetime
import time

# PARAMETERS
RabbitMQ_host = "192.168.1.190"
RabbitMQ_port = 5672
RabbitMQ_queue = "test_ctrlC"
RabbitMQ_cred_un = "xxxx"
RabbitMQ_cred_pd = "xxxx"

nbTest = 100000
nbBatch = 1000
nbPrefetch = 10000
# note, prefecth always >= nbBatch
timerSec = 60 # timer wait
workSec = 5 # nbr of sec for simulating batch work

# init variables for batch process
init_time = time.time()
exiting = False
work_threads = list()
event = None
list_Boby_Tag = Queue()

# Function Message Acknowledgement
def ack_message(ch, delivery_tag):
    """Note that `ch` must be the same pika channel instance via which
    the message being ACKed was retrieved (AMQP protocol constraint).
    """
    if ch.is_open:
        ch.basic_ack(delivery_tag)
        #print(datetime.datetime.now(),str(datetime.timedelta(seconds=time.time() - init_time)),f"DEBUG ack_message : begining of ack_message function, tag: {delivery_tag}")
    else:
        # Channel is already closed, so we can't ACK this message;
        # log and/or do something that makes sense for your app in this case.
        print(datetime.datetime.now(),str(datetime.timedelta(seconds=time.time() - init_time)),"Channel Closed when trying to Acknowledge")
        pass
    return

# Function Process multiple messages in separate thread
def do_work(channel, list_Boby_Tag):
    # init local variables
    body_list = list()
    tag_list = list()

    # cancel the timer if exist, as we will proces all elements in the queue here
    if event and event.is_alive():
        event.cancel()

    # extract all queued messages fom internal python queue and rebuild individual listes body and tag from tupple
    for i in range(list_Boby_Tag.qsize()):
        myTuppleBodyTag = list_Boby_Tag.get()
        body_list += [myTuppleBodyTag[0]]
        tag_list += [myTuppleBodyTag[1]]
    # that also empty the queue

    # do something that take time with the block of nessage in body_list
    time.sleep(workSec)

    for body in body_list:
        body_str = body.decode()
        #print(datetime.datetime.now(),str(datetime.timedelta(seconds=time.time() - init_time)),f'DEBUG block_process : message processed is {body_str}')

    # acknowledging all tags in tag_list by using the channel thread safe function .connection.add_callback_threadsafe
    for tag in tag_list:
        cb = functools.partial(ack_message, channel, tag)
        channel.connection.add_callback_threadsafe(cb)

    return

# Function Process message by message and call thread by block or timer
def process_message(ch, method, body):
    global work_threads
    global list_Boby_Tag
    global event

    # cancel the timer if exist as we are going to process a block or restart a new timer
    if event and event.is_alive():
        event.cancel()

    # put in the queue the data from the body and tag as tupple
    list_Boby_Tag.put((body,method.delivery_tag))

    # if a max queue size is reached (here 500), immmediately launch a new thread to process the queue
    if list_Boby_Tag.qsize() == nbBatch :
        #print(f'DEBUG thread count before {len(threads)}')
        # keep in the threads list only the thread still running
        work_threads = [x for x in work_threads if x.is_alive()]
        #print(f'DEBUG thread count after {len(threads)}')
        # start the inference in a separated thread
        t = threading.Thread(target=do_work, args=(ch, list_Boby_Tag))
        t.start()
        # keep trace of the thread so it can be waited at the end if still running
        work_threads.append(t)
        #print(f'DEBUG thread count after add {len(threads)}')
    elif list_Boby_Tag.qsize() > 0 :
        # if the queue is not full create a thread with a timer to do the process after sometime, here 10 seconds for test purpose
        event = threading.Timer(interval=timerSec, function=do_work, args=(ch, list_Boby_Tag))
        event.start()
        # also add this thread to the list of threads
        work_threads.append(event)
    return

# Function to start pika channel and stopping it
def pika_runner():
    # connect to RabbitMQ via Pika
    cred = pika.credentials.PlainCredentials(RabbitMQ_cred_un, RabbitMQ_cred_pd)
    connection = pika.BlockingConnection(
        pika.ConnectionParameters(
            host=RabbitMQ_host, port=RabbitMQ_port, credentials=cred
        )
    )
    channel = connection.channel()
    channel.queue_declare(queue=RabbitMQ_queue, durable=True)
    # tell rabbitMQ to don't dispatch a new message to a worker until it has processed and acknowledged the previous one :
    channel.basic_qos(prefetch_count=nbPrefetch)

    # empty queue and generate test data
    channel.queue_purge(queue=RabbitMQ_queue)
    # wait few second so the purge can be check in the RabbitMQ ui
    print(datetime.datetime.now(),str(datetime.timedelta(seconds=time.time() - init_time)),f"DEBUG main : queue {RabbitMQ_queue} purged, sleeping 5 seconds")
    connection.sleep(5)
    # generate test messages
    for msgId in range(nbTest):
        channel.basic_publish(
            exchange="",
            routing_key=RabbitMQ_queue,
            body=f"message-{msgId+1}",
            properties=pika.BasicProperties(
                delivery_mode=pika.spec.PERSISTENT_DELIVERY_MODE
            ),
        )
    print(datetime.datetime.now(),str(datetime.timedelta(seconds=time.time() - init_time)),f"DEBUG main : test messages created in {RabbitMQ_queue}")

    # loop forever to retrieve messahes
    for method_frame, properties, body in channel.consume(
        queue=RabbitMQ_queue, inactivity_timeout=1, auto_ack=False
    ):
        if exiting:
            print(datetime.datetime.now(),str(datetime.timedelta(seconds=time.time() - init_time)),f"DEBUG : stopping consuming")
            #channel.stop_consuming()
            channel.cancel()
            print(datetime.datetime.now(),str(datetime.timedelta(seconds=time.time() - init_time)),f"DEBUG : joining work threads")
            for thread in work_threads:
                thread.join()
            print(datetime.datetime.now(),str(datetime.timedelta(seconds=time.time() - init_time)),f"DEBUG : all work threads done, sleeping 5 seconds to let acks be delivered")
            connection.sleep(5)
            print(datetime.datetime.now(),str(datetime.timedelta(seconds=time.time() - init_time)),f"DEBUG : closing connections and channels")
            channel.close()
            connection.close()
        else:
            if method_frame is not None:
                process_message(channel, method_frame, body)

    return

# Function handle exit signals
def exit_handler(signum, _):
    global exiting
    if exiting:
        return
    exiting = True
    print(datetime.datetime.now(),str(datetime.timedelta(seconds=time.time() - init_time)),"Exit signal received")
    pika_thread.join()
    exit(0)

# launch the thread that will connect and listen to Pika
pika_thread = threading.Thread(target=pika_runner)
pika_thread.start()

# catch interuption signal to exit gracefully
signal.signal(signal.SIGINT, exit_handler)  # send by a CTRL+C or modified Docker Stop
print(" [*] Waiting for messages. To exit press CTRL+C")

# wait for all threads to finish
for thread in work_threads:
    thread.join()
pika_thread.join()