# -*- coding: utf-8 -*-
import json
import os
import sys
import random
import itertools


sys.path.append(os.getcwd())

from collections import defaultdict
from utils.feishu_utils import Feishu
class Material:
    """
        获取对应固定字幕
        """

    @classmethod
    def get_pzsrt_data(cls, feishu_id, feishu_sheet, video_share_name):
        data = Feishu.get_values_batch(feishu_id, feishu_sheet)

        for row in data[1:]:
            pz_mark = row[0]
            pz_zm = row[1]
            if pz_zm != 'None' and pz_zm != '' and pz_zm != None:
                if pz_mark == video_share_name:
                    return pz_zm
        return "温馨提示：\n点击下方按钮，传递好运"

    """获取去重天数"""
    @classmethod
    def get_count_restrict(cls, channel):
        count_channel = Feishu.get_values_batch("KsoMsyP2ghleM9tzBfmcEEXBnXg", "dQriSJ")
        for row in count_channel[1:]:
            sheet_channel = row[0]
            if sheet_channel == channel:
                return row[1]

    """
    list 重新排序
    """
    @classmethod
    def sort_keyword_data(cls, data):
        # 解析 JSON 数据
        data = [json.loads(item) for item in data]

        # 根据 keyword_name 进行分组
        groups = defaultdict(list)
        for item in data:
            groups[item['keyword_name']].append(item)

        # 获取所有唯一的 keyword_name
        priority_names = list(groups.keys())

        # 对每个分组内的数据按 first_category 进行随机打乱
        for name in priority_names:
            random.shuffle(groups[name])  # 打乱每个分组内的数据顺序

        # 轮流排序每个分组的数据，保持 keyword_name 的顺序
        result = []
        max_length = max(len(groups[name]) for name in priority_names)

        for i in range(max_length):
            for name in priority_names:
                if i < len(groups[name]):
                    result.append(groups[name][i])

        # 将结果转回 JSON 字符串列表
        sorted_list = [json.dumps(item, ensure_ascii=False) for item in result]
        return sorted_list

    """
    获取品类对应负责人任务明细
    """
    @classmethod
    def get_carry_data(cls, fs_id, fs_sheet):
        data = Feishu.get_values_batch( fs_id, fs_sheet )
        processed_list = []
        try:
            for row in data[1:]:
                channel = row[1]  # 渠道
                channel_url = row[2]  #账号信息
                tag = row[3]  #标签
                pd_id = row[4] #票圈id
                latest_count = row[5]  # 最新视频 条数
                totality_count = row[6]  # 任务总条数
                video_share = row[7]  # 片中分享文案
                video_share_ending = row[8]  # 片尾分享
                voice = row[9]  # 片尾音色
                crop_tool = row[10] # 画面裁剪
                gg_duration = row[11] #广告时间剪裁
                ai_title = row[12] # AI标题
                hottest_count = row[13]  # 最热视频 条数
                first_category = row[14]  # 一级品类
                secondary_category = row[15]  # 二级品类（搜索词）/ 负责人（品类）
                keyword_sort = row[16]  # 排序条件（搜索词条件筛选）
                keyword_time = row[17]  # 发布时间（搜索词件筛选）
                keyword_duration = row[18]  # 视频时长（搜索词件筛选）
                keyword_name = row[19]  # 负责人（搜索词件筛选）
                if not channel:
                    continue
                if ',' in channel_url:
                    channel_url = channel_url.split(',')
                else:
                    channel_url = [channel_url]
                if "搜索" not in channel :
                    for user in channel_url:
                        number_dict = {
                            "task_mark" : f"{channel}-{first_category}",
                            "channel": channel,
                            "channel_url": user,
                            "tag": tag,
                            "pd_id": pd_id,
                            "count": latest_count,
                            "totality_count": totality_count,
                            "video_share": video_share,
                            "video_share_ending": video_share_ending,
                            "voice": voice,
                            "crop_tool": crop_tool,
                            "gg_duration": gg_duration,
                            "ai_title": ai_title,
                            "first_category": first_category,
                            "keyword_name": secondary_category
                        }
                        processed_list.append(json.dumps(number_dict, ensure_ascii=False))
                    if hottest_count:
                        for user in channel_url:
                            number_dict = {
                                "task_mark" :f"历史{channel}-{first_category}",
                                "channel": f"历史{channel}",
                                "channel_url": user,
                                "tag": tag,
                                "pd_id": pd_id,
                                "count": hottest_count,
                                "totality_count": totality_count,
                                "video_share": video_share,
                                "video_share_ending": video_share_ending,
                                "voice": voice,
                                "crop_tool": crop_tool,
                                "gg_duration": gg_duration,
                                "ai_title": ai_title,
                                "first_category": first_category,
                                "keyword_name": secondary_category
                            }
                            processed_list.append(json.dumps(number_dict, ensure_ascii=False))

                else:
                    keyword_sort_list = keyword_sort.split(',')
                    keyword_duration_list = keyword_duration.split(',')
                    keyword_time_list = keyword_time.split(',')
                    combinations = list(itertools.product(keyword_sort_list, keyword_time_list, keyword_duration_list))
                    for user in channel_url:
                        for combo in combinations:
                            number_dict = {
                                "task_mark" : f"{channel}-{first_category}",
                                "channel": channel,
                                "channel_url": user,
                                "tag": tag,
                                "pd_id": pd_id,
                                "count": latest_count,
                                "totality_count": totality_count,
                                "video_share": video_share,
                                "video_share_ending": video_share_ending,
                                "voice": voice,
                                "crop_tool": crop_tool,
                                "gg_duration": gg_duration,
                                "ai_title": ai_title,
                                "first_category": first_category,
                                "secondary_category": secondary_category,
                                "combo": combo ,
                                "keyword_name": keyword_name,
                            }
                            processed_list.append(json.dumps(number_dict, ensure_ascii=False))

            processed_list = cls.sort_keyword_data(processed_list)
            return  processed_list
        except:
            processed_list = cls.sort_keyword_data(processed_list)
            return processed_list