增加收藏数据库解析
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xaoyaoo
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@ -6,6 +6,8 @@
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# Date: 2024/05/18
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# -------------------------------------------------------------------------------
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from .dbbase import DatabaseBase
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from .utils import timestamp2str, xml2dict
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# * FavItems：收藏的消息条目列表
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# * FavDataItem：收藏的具体数据。大概可以确定以下两点
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@ -13,17 +15,135 @@ from .dbbase import DatabaseBase
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# * 对于收藏的合并转发类型的消息，合并转发中的每一条消息在 FavDataItem 中都是一个独立的记录
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# * FavTags：为收藏内容添加的标签
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def FavoriteTypeId2Name(Type):
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TypeNameDict = {
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1: "文本", # 文本 已测试
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2: "图片", # 图片 已测试
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3: "语音", # 语音
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4: "视频", # 视频 已测试
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5: "链接", # 链接 已测试
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6: "位置", # 位置
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7: "小程序", # 小程序
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8: "文件", # 文件 已测试
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14: "聊天记录", # 聊天记录 已测试
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16: "群聊视频", # 群聊中的视频 可能
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18: "笔记" # 笔记 已测试
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}
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return TypeNameDict.get(Type, "未知")
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class ParsingFavorite(DatabaseBase):
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_class_name = "Favorite"
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def __init__(self, db_path):
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super().__init__(db_path)
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def get_tags(self):
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"""
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return: {LocalID: TagName}
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"""
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sql = "select LocalID, TagName from FavTagDatas order by ServerSeq"
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tags = self.execute_sql(sql) # [(1, 797940830, '程序语言类'), (2, 806153863, '账单')]
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# 转换为字典
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tags = {tag[0]: tag[1] for tag in tags}
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return tags
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def get_FavBindTags(self):
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"""
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return: [(FavLocalID, TagName)]
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"""
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sql = "select A.FavLocalID, B.TagName from FavBindTagDatas A, FavTagDatas B where A.TagLocalID = B.LocalID"
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FavBindTags = self.execute_sql(sql)
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return FavBindTags
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def get_favorite(self):
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sql1 = "select * from FavItems"
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sql2 = "select * from FavDataItem"
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sql3 = "select * from FavTags"
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DBdata1 = self.execute_sql(sql1)
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DBdata2 = self.execute_sql(sql2)
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DBdata3 = self.execute_sql(sql3)
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return DBdata1, DBdata2, DBdata3
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"""
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return: [{FavItemsFields}, {FavItemsFields}]
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"""
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FavItemsFields = {
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"FavLocalID": "本地收藏ID",
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"SvrFavId": "服务器收藏ID",
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"SourceId": "源ID",
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"Type": "类型",
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"SourceType": "源类型",
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"LocalStatus": "本地状态",
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"Flag": "标记",
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"Status": "状态",
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"FromUser": "源用户",
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"RealChatName": "实际聊天名称",
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"SearchKey": "搜索关键字",
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"UpdateTime": "更新时间",
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"reseverd0": "预留字段0",
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"XmlBuf": "XML缓冲区"
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}
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FavDataItemFields = {
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"FavLocalID": "本地收藏ID",
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"Type": "类型",
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"DataId": "数据ID",
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"HtmlId": "HTML ID",
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"Datasourceid": "数据源ID",
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"Datastatus": "数据状态",
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"Datafmt": "数据格式",
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"Datatitle": "数据标题",
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"Datadesc": "数据描述",
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"Thumbfullmd5": "缩略图全MD5",
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"Thumbhead256md5": "缩略图头256MD5",
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"Thumbfullsize": "缩略图全尺寸",
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"fullmd5": "全MD5",
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"head256md5": "头256MD5",
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"fullsize": "全尺寸",
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"cdn_thumburl": "CDN缩略图URL",
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"cdn_thumbkey": "CDN缩略图KEY",
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"thumb_width": "缩略图宽度",
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"thumb_height": "缩略图高度",
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"cdn_dataurl": "CDN数据URL",
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"cdn_datakey": "CDN数据KEY",
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"cdn_encryver": "CDN加密版本",
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"duration": "时长",
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"stream_weburl": "流媒体WEB URL",
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"stream_dataurl": "流媒体数据URL",
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"stream_lowbandurl": "流媒体低带宽URL",
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"sourcethumbpath": "源缩略图路径",
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"sourcedatapath": "源数据路径",
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"stream_videoid": "流媒体视频ID",
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"Rerserved1": "保留字段1",
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"Rerserved2": "保留字段2",
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"Rerserved3": "保留字段3",
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"Rerserved4": "保留字段4",
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"Rerserved5": "保留字段5",
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"Rerserved6": "保留字段6",
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"Rerserved7": "保留字段7"
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}
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sql1 = "select " + ",".join(FavItemsFields.keys()) + " from FavItems order by UpdateTime desc"
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sql2 = "select " + ",".join(FavDataItemFields.keys()) + " from FavDataItem B order by B.RecId asc"
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FavItemsList = self.execute_sql(sql1)
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FavDataItemList = self.execute_sql(sql2)
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if FavItemsList is None or len(FavItemsList) == 0:
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return False
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FavDataDict = {}
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if FavDataItemList and len(FavDataItemList) >= 0:
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for item in FavDataItemList:
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data_dict = {}
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for i, key in enumerate(FavDataItemFields.keys()):
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data_dict[key] = item[i]
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FavDataDict[item[0]] = FavDataDict.get(item[0], []) + [data_dict]
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# 获取标签
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FavTags = self.get_FavBindTags()
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FavTagsDict = {}
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for FavLocalID, TagName in FavTags:
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FavTagsDict[FavLocalID] = FavTagsDict.get(FavLocalID, []) + [TagName]
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pf = pd.DataFrame(FavItemsList)
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pf.columns = FavItemsFields.keys() # set column names
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pf["UpdateTime"] = pf["UpdateTime"].apply(timestamp2str) # 处理时间
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pf["XmlBuf"] = pf["XmlBuf"].apply(xml2dict) # 处理xml
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pf["TypeName"] = pf["Type"].apply(FavoriteTypeId2Name) # 添加类型名称列
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pf["FavData"] = pf["FavLocalID"].apply(lambda x: FavDataDict.get(x, [])) # 添加数据列
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pf["Tags"] = pf["FavLocalID"].apply(lambda x: FavTagsDict.get(x, [])) # 添加标签列
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pf = pf.fillna("") # 去掉Nan
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rdata = pf.to_dict(orient="records")
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return rdata
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