1. Kafka与Odoo结合的场景
在某些业务场景下，我们希望将Odoo中的数据变更（如新订单、新用户注册等）实时发送到Kafka，以便其他业务系统自定义consumer进行处理。
2. 实现Kafka消费者（Consumer）
下面的代码展示了如何实现一个Kafka消费者，它会监听Kafka中的特定主题（如odoo_topic），并将消息处理后存储到Odoo中：
import threading
import time
from kafka import KafkaConsumer, KafkaProducer
import json
from odoo import api, registry, SUPERUSER_ID
class KafkaConsumerWrapper(threading.Thread):
def __init__(self, db_name, env):
threading.Thread.__init__(self)
self.db_name = db_name
self.env = env
self.consumer = KafkaConsumer(
'odoo_topic',
bootstrap_servers=['localhost:9092'],
enable_auto_commit=False,
group_id='my_group',
auto_offset_reset='earliest',
value_deserializer=lambda m: json.loads(m.decode('utf-8'))
)
self.producer = KafkaProducer(
bootstrap_servers=['localhost:9092'],
value_serializer=lambda m: json.dumps(m).encode('utf-8')
)
self.max_retries = 3
self.dlq_topic = 'dead_letter_queue' # 死信队列的主题
def run(self):
with api.Environment.manage():
registry_obj = registry(self.db_name)
with registry_obj.cursor() as cr:
env = api.Environment(cr, SUPERUSER_ID, {})
for message in self.consumer:
data = message.value
self.process_message(env, data)
# 手动提交位移
self.consumer.commit()
def process_message(self, env, data):
try:
success = False
retry_count = 0
while not success and retry_count < self.max_retries:
try:
if data.get('name') == 'error':
raise Exception("Simulated processing error")
env
['message.model'].create({'name': data.get('name'), 'status': 'Received'})
env.cr.commit()
self.consumer.commit()
success = True # 成功处理后退出循环
except Exception as e:
retry_count += 1
print(f"Error processing message: {e}")
partitions = self.consumer.assignment()
offsets = {tp: self.consumer.position(tp) for tp in partitions}
for tp, offset in offsets.items():
self.consumer.seek(tp, offset)
time.sleep(1)
if not success:
print(f"Failed to process message after {self.max_retries} retries, sending to DLQ")
self.send_to_dlq(data)
except KeyboardInterrupt:
print("Consumer interrupted by user")
def send_to_dlq(self, data):
try:
self.producer.send(self.dlq_topic, data)
self.producer.flush()
except Exception as e:
print(f"Failed to send message to DLQ: {e}")
def start_kafka_consumer_service(env):
db_name = env.cr.dbname
consumer_service = KafkaConsumerWrapper(db_name, env)
consumer_service.start()该消费者类通过继承threading.Thread实现了一个多线程的Kafka消费者，它会监听odoo_topic主题，并将消息内容存储到Odoo数据库中。在处理过程中，如果遇到错误，该消费者还会尝试重试，并在多次失败后将消息发送到死信队列（DLQ）。
3.如何启动消费者（consumer）
使用钩子函数，在odoo启动过程中启动kfaka消费者
def post_load():
# 在Odoo加载后启动Kafka消费者服务
with odoo.api.Environment.manage():
registry = odoo.registry(config['db_name'])
with registry.cursor() as cr:
uid = odoo.SUPERUSER_ID
env = odoo.api.Environment(cr, uid, {})
start_kafka_consumer_service(env)4. 实现Kafka生产者（Producer）
生产者负责将Odoo中的数据发送到Kafka。下面的代码展示了一个简单的Kafka生产者实现：
from kafka import KafkaProducer
import json
class KafkaProducerWrapper:
def __init__(self, server='localhost:9092'):
self.producer = KafkaProducer(
bootstrap_servers=server,
value_serializer=lambda v: json.dumps(v).encode('utf-8')
)
def send_message(self, topic, message):
self.producer.send(topic, message)
self.producer.flush()
def send_kafka_message(self):
producer = KafkaProducerWrapper()
for record in self:
producer.send_message('odoo_topic', {'name': record.name})这个生产者类提供了一个简单的方法send_message，可以将数据发送到指定的Kafka主题。在实际应用中，我们可以在Odoo的业务逻辑中调用这个方法，将重要的业务事件推送到Kafka，供其他系统消费。
