Flask - flask-pika 操作 Rabbit

目录

一、flask-pika

二、基于 Flask 框架的初步使用

2-1 生产者的队列堵塞问题

---

 

一、flask-pika

官方 github

安装

二、基于 Flask 框架的初步使用

生产者包装成API调用，消费者使用其他进程监听执行

'''配置文件 dev.py'''
FLASK_PIKA_PARAMS = {
    'host': 'localhost',  # amqp.server.com
    'username': 'test',  # convenience param for username
    'password': '123',  # convenience param for password
    'port': 5672,  # amqp server port
    #'virtual_host': 'vhost'  # amqp vhost
}

# optional pooling params
FLASK_PIKA_POOL_PARAMS = {
    'pool_size': 8,
    'pool_recycle': 600
}

'''app.py'''
import os
from flask import Flask
from extensions import fpika

_default_instance_path = '%(instance_path)s/instance' % \
                         {'instance_path': os.path.dirname(os.path.realpath(__file__))}


def create_app():
    app = Flask(__name__, instance_relative_config=True, instance_path=_default_instance_path)
    configure_app(app)
    configure_blueprint(app)
    configure_redis(app)
    configure_rabbitmq(app)
    return app


def configure_app(app):
    app.config.from_pyfile('dev.py')


def configure_blueprint(app):
    app.register_blueprint(rabbit.rabbit_blueprint, url_prefix='/rabbit')



def configure_rabbitmq(app):
    fpika.init_app(app)

''' extensions.py '''
from flask_pika import Pika

fpika = Pika()

'''视图函数 - rabbit.py'''
from flask import Blueprint
from flask_restful import Resource

from extensions import fpika
from tasks import task0

from . import Api

rabbit_blueprint = Blueprint('rabbit', __name__)
rabbit_api = Api(rabbit_blueprint)


class Producer(Resource):
    def get(self):
        print('Producer')
        channel = fpika.channel()
        channel.queue_declare(queue='test')
        channel.basic_publish(exchange='', routing_key='test', body='hello pika')
        # 将通道还给池
        # return_broken_channel 在该框架下使用解决队列堵塞问题，详见下方分析
        fpika.return_broken_channel(channel)
        fpika.return_channel(channel)
        return 'Producer'


rabbit_api.add_resource(Producer, '/Producer')

 

'''消费者'''
import pika

# 证书创建
credentials = pika.PlainCredentials('test', '123')
# 本地连接
conn = pika.BlockingConnection(pika.ConnectionParameters(host="localhost", credentials=credentials))
# 远程连接
# connection = pika.BlockingConnection(pika.ConnectionParameters(
# '192.168.56.19',5672,'/',credentials))
channel = conn.channel()

# 再次创建队列，防止队列不存在的情况出现，和生产者队列同名
channel.queue_declare(queue='test')


# 回调函数，用于队列任务结束后的回调，用于将数据返回发送端，表明是否执行完毕
def callback(ch, method, properties, body):
    print("[x] Received ")
    print(ch)
    print(method)
    print(properties)
    print(body)


# no_ack 表名是否告知发送端是否接受消息，True - 接收
channel.basic_consume(callback, queue="test", no_ack=True)

# 开启监听，进程夯住，等待消息
print('waiting for message To exit   press CTRL+C')
channel.start_consuming()

2-1 生产者的队列堵塞问题

问题分析：设置'pool_size'，若超过'pool_size'的设置数量，则无法将任务推入 RabbitMQ 中

初步问题分析：框架兼容问题（不确定）

暂时处理方式：

1. FLASK_PIKA_POOL_PARAMS = None 不使用 pika 池
2. 添加 return_broken_channel ，问题暂时未出现

# 将通道还给池
fpika.return_broken_channel(channel)
fpika.return_channel(channel)

正常批量推送