google_ai_studio/job_video_processing.py

import time
from concurrent.futures import ThreadPoolExecutor, wait
from common.redis import install_video_data
from video_processing.video_processing import VideoProcessing


max_workers = 10

def video_ai_task_start():
    with ThreadPoolExecutor( max_workers=max_workers) as executor:
        while True:
            try:
                redis_task_list = ['task:video_ai_top']
                futures = []
                start_time = time.time()  # 记录开始时间

                for redis_task in redis_task_list:
                    futures.append(executor.submit( process_video_ai, redis_task))
                    time.sleep(1)  # 每秒提交一个任务
                wait( futures )  # 等待所有任务完成
                end_time = time.time()  # 记录结束时间

                total_time = end_time - start_time  # 计算总耗时
                print( f"6个线程完成任务总耗时：{total_time:.2f}秒" )
            except Exception as e:
                print(f"异常信息{e}")
                time.sleep(3)
                continue

def process_video_ai(redis_task):
    try:

        print(f"开始执行任务{redis_task}")
        video_processor = VideoProcessing()
        video_processor.get_video(redis_task)
        print(f"执行完成{redis_task}")
        time.sleep(5)
    except Exception as e:
        print("处理任务时出现异常:", e)
        time.sleep(5)
if __name__ == '__main__':
    video_ai_task_start()