data-clean/JobMain.py

# -*- coding: utf-8 -*-
# @Time : 2023/7/20 16:13
# @Author : XuJiakai
# @File : JobMain
# @Software: PyCharm
import asyncio
import json
from functools import partial

import aio_pika
from aio_pika import IncomingMessage
from environs import Env

from data_clean.task_distributor import task_distribute
from data_clean.utils import get_log
from data_clean.utils.async_client import get_aio_kafka_consumer, get_aio_kafka_producer, get_rabbitmq_connection
from data_clean.utils.asyncio_pool import AsyncPool

json.dumps = partial(json.dumps, ensure_ascii=False)

env = Env()

base_topic = env.str("base_topic", "rt_other_dim")

source_topic = env.str("source_topic", base_topic)  # "rt_company_dim"
target_topic = env.str("target_topic", base_topic)  # "rt_company_dim"

max_concurrency = env.int("concurrency", 1)
log = get_log("JobMain")


async def handle(producer, data: dict):
    result = await task_distribute(data)

    # print("send : ", result)

    if result is not None:
        await producer.send_and_wait(target_topic, json.dumps(result).encode())
        pass
    pass


async def on_message_received(producer, msg: IncomingMessage):
    data: dict = json.loads(msg.body)
    await handle(producer, data)
    await msg.ack()
    pass


async def main_for_rabbitmq():
    log.info("start job. Listening queue : %s , send topic: %s , max concurrency: %s", source_topic, target_topic,
             max_concurrency)

    pool = AsyncPool(max_concurrency)

    producer = get_aio_kafka_producer()
    await producer.start()

    queue_name = source_topic  # 只需要配置这个

    connection = await get_rabbitmq_connection()
    async with connection:
        channel: aio_pika.abc.AbstractChannel = await connection.channel()
        await channel.set_qos(prefetch_count=max_concurrency)

        # Declaring queue
        queue: aio_pika.abc.AbstractQueue = await channel.declare_queue(
            name=queue_name,
            durable=True,
            auto_delete=False
        )

        async with queue.iterator(no_ack=False) as queue_iter:
            # Cancel consuming after __aexit__
            async for message in queue_iter:
                message: IncomingMessage = message
                await pool.create_task(on_message_received(producer, message))
                # async with message.process(ignore_processed=True):
                #     await pool.create_task(on_message_received(producer, message))
                #     pass
        pass
    pass


async def main_for_kafka():
    pool = AsyncPool(max_concurrency)
    consumer = get_aio_kafka_consumer(source_topic)
    producer = get_aio_kafka_producer()
    await producer.start()
    await consumer.start()
    try:
        # Consume messages
        async for msg in consumer:
            print("consumed: ", msg.topic, msg.partition, msg.offset,
                  msg.key, msg.value, msg.timestamp)
            data: dict = json.loads(msg.value)
            await pool.create_task(handle(producer, data))

    finally:
        # Will leave consumer group; perform autocommit if enabled.
        await consumer.stop()

    pass


if __name__ == '__main__':
    asyncio.run(main_for_rabbitmq())
    pass