video_rewriting/job_wxk.py

import os
import concurrent.futures
import time
import threading
from common import Material
from video_rewriting.video_processor import VideoProcessor

# 控制读写速度的参数
MAX_BPS = 120 * 1024 * 1024  # 120MB/s
MAX_WORKERS = os.cpu_count() * 2  # 线程池最大工作线程数量
READ_WRITE_CHUNK_SIZE = 1024 * 1024  # 每次读写的块大小 (1MB)
SLEEP_INTERVAL = READ_WRITE_CHUNK_SIZE / MAX_BPS  # 控制每次读写的延迟时间

# 全局锁，用于同步读写操作
lock = threading.Lock()

def video_task_start(data):
    """处理视频任务，返回用户名并根据结果决定延迟时间"""
    try:
        mark = VideoProcessor.main(data)
        print(f"返回用户名: {mark}")
        time.sleep(10 if mark else 120)  # 根据 mark 是否为空设置延迟
        return mark
    except Exception as e:
        print("处理任务时出现异常:", e)
        return None

def controlled_io_operation(data):
    """同步控制IO操作并执行视频任务"""
    with lock:
        time.sleep(SLEEP_INTERVAL)
    return video_task_start(data)

def video_start():
    """启动视频生成任务"""
    print("开始执行生成视频脚本.")
    data = Material.feishu_list()[0]
    with concurrent.futures.ThreadPoolExecutor(max_workers=MAX_WORKERS) as executor:
        futures = [executor.submit(controlled_io_operation, data) for _ in range(MAX_WORKERS)]
        for future in concurrent.futures.as_completed(futures):
            try:
                result = future.result()
                print(f"处理结果: 成功, 用户名: {result}")
            except Exception as e:
                print("处理任务时出现异常:", e)
    print("执行生成视频脚本结束.")

while True:
    video_start()