aigc-test/download_videos_task.py

import traceback
import datetime
import os
import oss2
import multiprocessing
from threading import Timer
from utils import data_check, get_feature_data
from config import set_config
from log import Log
import ODPSQueryUtil
from ReadXlsxFile import getVideoInfoInXlxs
config_ = set_config()
log_ = Log()
features = ['videoid', 'title', 'video_path']


def download_video_from_oss(video_id, video_path, download_folder):
    """从oss下载视频"""
    try:
        pid = int(os.getpid() % 2)
        print(f"{video_id} download start ...")
        download_folder = f"{download_folder}_{pid}"
        if not os.path.exists(download_folder):
            os.makedirs(download_folder)
        video_local_dir = os.path.join(download_folder, str(video_id))
        os.makedirs(video_local_dir)
        video_filename = video_path.split('/')[-1]
        video_local_path = os.path.join(video_local_dir, video_filename)
        # 阿里云账号AccessKey拥有所有API的访问权限，风险很高。强烈建议您创建并使用RAM用户进行API访问或日常运维，请登录RAM控制台创建RAM用户。
        # auth = oss2.Auth(access_key_id=config_.ODPS_CONFIG['ACCESSID'], access_key_secret=config_.ODPS_CONFIG['ACCESSKEY'])
        auth = oss2.Auth(access_key_id=config_.OSS_CONFIG['accessKeyId'],
                         access_key_secret=config_.OSS_CONFIG['accessKeySecret'])
        # Endpoint以杭州为例，其它Region请按实际情况填写。
        bucket = oss2.Bucket(
            auth, endpoint=config_.OSS_CONFIG['endpoint'], bucket_name='art-pubbucket')
        # 下载OSS文件到本地文件。
        # <yourObjectName>由包含文件后缀，不包含Bucket名称组成的Object完整路径，例如abc/efg/123.jpg。
        # <yourLocalFile>由本地文件路径加文件名包括后缀组成，例如/users/local/myfile.txt。
        bucket.get_object_to_file(video_path, video_local_path)

        # m3u8文件，需下载所有ts文件
        if video_filename.split('.')[-1] == 'm3u8':
            root_path = '/'.join(video_path.split('/')[:-1])
            with open(video_local_path, 'r') as rf:
                lines = rf.readlines()
                for line in lines:
                    line = line.strip()
                    print(line)
                    if line[-3:] == '.ts':
                        ts_path = os.path.join(root_path, line)
                        ts_local_path = os.path.join(video_local_dir, line)
                        bucket.get_object_to_file(ts_path, ts_local_path)
        print(f"{video_id} download end!")
    except:
        print(f"{video_id} download fail!")
        print(traceback.format_exc())


def download_videos(project, table, dt):
    # 获取特征数据
    feature_df = get_feature_data(
        project=project, table=table, dt=dt, features=features)
    download_folder = 'videos'
    video_id_list = feature_df['videoid'].to_list()
    pool = multiprocessing.Pool(processes=6)
    for video_id in video_id_list:
        video_path = feature_df[feature_df['videoid']
                                == video_id]['video_path'].values[0].strip()
        video_path = video_path.replace(' ', '')
        print(video_id, video_path)
        pool.apply_async(
            func=download_video_from_oss,
            args=(video_id, video_path, download_folder)
        )
    pool.close()
    pool.join()


def timer_check():
    try:
        project = config_.DAILY_VIDEO['project']
        table = config_.DAILY_VIDEO['table']
        # 昨天
        now_date = datetime.datetime.today()
        print(f"now_date: {datetime.datetime.strftime(now_date, '%Y%m%d')}")
        dt = datetime.datetime.strftime(
            now_date-datetime.timedelta(days=1), '%Y%m%d')
        # 查看数据是否已准备好
        data_count = data_check(project=project, table=table, dt=dt)
        if data_count > 0:
            print(f'videos count = {data_count}')
            # 数据准备好，进行视频下载
            download_videos(project=project, table=table, dt=dt)
            print(f"videos download end!")

        else:
            # 数据没准备好，1分钟后重新检查
            Timer(60, timer_check).start()
    except Exception as e:
        print(f"视频下载失败, exception: {e}, traceback: {traceback.format_exc()}")


if __name__ == '__main__':
    # timer_check()
    feature_df = getVideoInfoInXlxs('past_videos.xlsx')
    download_folder = 'videos'
    video_id_list = feature_df['videoid'].to_list()
    pool = multiprocessing.Pool(processes=6)
    for video_id in video_id_list:
        video_path = feature_df[feature_df['videoid']
                                == video_id]['video_path'].values[0].strip()
        video_path = video_path.replace(' ', '')
        print(video_id, video_path)
        pool.apply_async(
            func=download_video_from_oss,
            args=(video_id, video_path, download_folder)
        )
    pool.close()
    pool.join()