google_ai_studio/job_video_processing.py

import time
from video_processing.video_processing import VideoProcessing
from concurrent.futures import ThreadPoolExecutor, wait, as_completed


max_workers = 6

def video_ai_task_start():
    redis_task_list = ['task:video_ai_top', 'task:video_ai_recommend'] * 3  # 模拟任务列表

    with ThreadPoolExecutor( max_workers=max_workers ) as executor:
        futures = []
        task_index = 0
        total_tasks = len( redis_task_list )

        while True:
            try:
                while len( futures ) < max_workers and task_index < total_tasks:
                    redis_task = redis_task_list[task_index]
                    futures.append( executor.submit( process_video_ai, redis_task ) )
                    print( f"提交任务: {redis_task}" )
                    task_index += 1
                    time.sleep( 1 )

                for future in as_completed( futures ):
                    futures.remove( future )
                    print( f"完成一个任务，当前运行中的任务数：{len( futures )}" )

                    if task_index < total_tasks:
                        redis_task = redis_task_list[task_index]
                        futures.append( executor.submit( process_video_ai, redis_task ) )
                        print( f"补充新任务: {redis_task}" )
                        task_index += 1
                        time.sleep( 1 )

            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()