# -*- coding: utf-8 -*-
# pylint: disable=C0111,C0103,R0205

import functools
import logging
import threading
import time
import pika
from pika.exchange_type import ExchangeType

LOG_FORMAT = ('%(levelname) -10s %(asctime)s %(name) -30s %(funcName) '
              '-35s %(lineno) -5d: %(message)s')
LOGGER = logging.getLogger(__name__)

logging.basicConfig(level=logging.DEBUG, format=LOG_FORMAT)


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)
    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.
        pass


def do_work(conn, ch, delivery_tag, body):
    thread_id = threading.get_ident()
    LOGGER.info('Thread id: %s Delivery tag: %s Message body: %s', thread_id,
                delivery_tag, body)
    # Sleeping to simulate 10 seconds of work
    time.sleep(10)
    cb = functools.partial(ack_message, ch, delivery_tag)
    conn.add_callback_threadsafe(cb)


def on_message(ch, method_frame, _header_frame, body, args):
    (conn, thrds) = args
    delivery_tag = method_frame.delivery_tag
    t = threading.Thread(target=do_work, args=(conn, ch, delivery_tag, body))
    t.start()
    thrds.append(t)


credentials = pika.PlainCredentials('guest', 'guest')
# Note: sending a short heartbeat to prove that heartbeats are still
# sent even though the worker simulates long-running work
parameters = pika.ConnectionParameters(
    'localhost', credentials=credentials, heartbeat=5)
connection = pika.BlockingConnection(parameters)

channel = connection.channel()
channel.exchange_declare(
    exchange="test_exchange",
    exchange_type=ExchangeType.direct,
    passive=False,
    durable=True,
    auto_delete=False)
channel.queue_declare(queue="standard", auto_delete=True)
channel.queue_bind(
    queue="standard", exchange="test_exchange", routing_key="standard_key")
# Note: prefetch is set to 1 here as an example only and to keep the number of threads created
# to a reasonable amount. In production you will want to test with different prefetch values
# to find which one provides the best performance and usability for your solution
channel.basic_qos(prefetch_count=1)

threads = []
on_message_callback = functools.partial(on_message, args=(connection, threads))
channel.basic_consume('standard', on_message_callback)

try:
    channel.start_consuming()
except KeyboardInterrupt:
    channel.stop_consuming()

# Wait for all to complete
for thread in threads:
    thread.join()

connection.close()

# -*- coding: utf-8 -*-
# pylint: disable=C0111,C0103,R0205

import functools
import logging
import threading
import time
import pika
from pika.exchange_type import ExchangeType

LOG_FORMAT = ('%(levelname) -10s %(asctime)s %(name) -30s %(funcName) '
              '-35s %(lineno) -5d: %(message)s')
LOGGER = logging.getLogger(__name__)

logging.basicConfig(level=logging.DEBUG, format=LOG_FORMAT)


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)
    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.
        pass


def do_work(conn, ch, delivery_tag, body):
    thread_id = threading.get_ident()
    LOGGER.info('Thread id: %s Delivery tag: %s Message body: %s', thread_id,
                delivery_tag, body)
    # Sleeping to simulate 10 seconds of work
    time.sleep(10)
    cb = functools.partial(ack_message, ch, delivery_tag)
    conn.add_callback_threadsafe(cb)


def on_message(ch, method_frame, _header_frame, body, args):
    (conn, thrds) = args
    delivery_tag = method_frame.delivery_tag
    t = threading.Thread(target=do_work, args=(conn, ch, delivery_tag, body))
    t.start()
    thrds.append(t)


credentials = pika.PlainCredentials('guest', 'guest')
# Note: sending a short heartbeat to prove that heartbeats are still
# sent even though the worker simulates long-running work
parameters = pika.ConnectionParameters(
    'localhost', credentials=credentials, heartbeat=5)
connection = pika.BlockingConnection(parameters)

channel = connection.channel()
channel.exchange_declare(
    exchange="test_exchange",
    exchange_type=ExchangeType.direct,
    passive=False,
    durable=True,
    auto_delete=False)
channel.queue_declare(queue="standard", auto_delete=True)
channel.queue_bind(
    queue="standard", exchange="test_exchange", routing_key="standard_key")
# Note: prefetch is set to 1 here as an example only and to keep the number of threads created
# to a reasonable amount. In production you will want to test with different prefetch values
# to find which one provides the best performance and usability for your solution
channel.basic_qos(prefetch_count=1)

threads = []
on_message_callback = functools.partial(on_message, args=(connection, threads))
channel.basic_consume('standard', on_message_callback)

try:
    channel.start_consuming()
except KeyboardInterrupt:
    channel.stop_consuming()

# Wait for all to complete
for thread in threads:
    thread.join()

connection.close()

# -*- coding: utf-8 -*- # pylint: disable=C0111,C0103,R0205 Note that `ch` must be the same pika channel instance via which     the message being ACKed was retrieved (AMQP protocol constraint). # 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. # Sleeping to simulate 10 seconds of work # Note: sending a short heartbeat to prove that heartbeats are still # sent even though the worker simulates long-running work # Note: prefetch is set to 1 here as an example only and to keep the number of threads created # to a reasonable amount. In production you will want to test with different prefetch values # to find which one provides the best performance and usability for your solution # Wait for all to complete