| import datasets | |
| import json | |
| import xml.etree.ElementTree as ET | |
| from datasets import BuilderConfig, DatasetInfo, DownloadManager, GeneratorBasedBuilder, Features, SplitGenerator, Value | |
| from typing import Any, Dict, Iterator, List, Tuple, Union | |
| class KakologArchivesConfig(BuilderConfig): | |
| def __init__(self, channel_id: Union[str, None] = None, year: Union[int, None] = None, number_of_files: Union[int, None] = None, **kwargs): | |
| super(KakologArchivesConfig, self).__init__(**kwargs) | |
| self.channel_id = channel_id | |
| self.year = year | |
| self.number_of_files = number_of_files | |
| class KakologArchivesDatasetBuilder(GeneratorBasedBuilder): | |
| VERSION = '1.0.0' | |
| BUILDER_CONFIGS = [ | |
| KakologArchivesConfig( | |
| name = 'all', | |
| version = VERSION, | |
| description = '全チャンネル/全期間のすべての過去ログコメントを取得します。180GB 近くあるため注意してください。', | |
| ), | |
| KakologArchivesConfig( | |
| name='sample', | |
| version = VERSION, | |
| description = 'サンプルとして、2022年中に投稿された TOKYO MX (実況チャンネル ID: jk9) のすべての過去ログコメントを取得します。1GB ほどあります。', | |
| channel_id = 'jk9', | |
| year = 2022, | |
| ), | |
| ] | |
| DEFAULT_CONFIG_NAME = "all" | |
| def _info(self) -> DatasetInfo: | |
| return DatasetInfo( | |
| description = 'ニコニコ実況のサービス開始から現在までのすべての過去ログコメントのデータセットです。', | |
| homepage = 'https://jikkyo.tsukumijima.net/', | |
| features = Features({ | |
| 'thread': Value('string'), | |
| 'no': Value('int64'), | |
| 'vpos': Value('int64'), | |
| 'date': Value('int64'), | |
| 'date_usec': Value('int64'), | |
| 'user_id': Value('string'), | |
| 'mail': Value('string', id=None), | |
| 'premium': Value('bool'), | |
| 'anonymity': Value('bool'), | |
| 'content': Value('string'), | |
| }), | |
| ) | |
| def _split_generators(self, dl_manager: DownloadManager) -> List[SplitGenerator]: | |
| def create_relative_paths(json_data: dict[str, Any], current_path: str = "") -> List[str]: | |
| relative_paths = [] | |
| for key, value in json_data.items(): | |
| new_path = f"{current_path}/{key}" if current_path else key | |
| if value is None: | |
| relative_paths.append(new_path) | |
| elif isinstance(value, dict): | |
| relative_paths.extend(create_relative_paths(value, new_path)) | |
| return relative_paths | |
| json_file = dl_manager.download('dataset_structure.json') | |
| with open(json_file, 'r', encoding='utf-8') as f: | |
| relative_paths = create_relative_paths(json.load(f)) | |
| if self.config.channel_id is not None: | |
| relative_paths = [path for path in relative_paths if f"{self.config.channel_id}/" in path] | |
| if self.config.year is not None: | |
| relative_paths = [path for path in relative_paths if f"/{self.config.year}/" in path] | |
| if self.config.number_of_files is not None: | |
| relative_paths = relative_paths[:min(self.config.number_of_files, len(relative_paths))] | |
| downloaded_files = dl_manager.download(relative_paths) | |
| return [SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"files": downloaded_files})] | |
| def _generate_examples(self, files: List[str]) -> Iterator[Tuple[int, Dict[str, Any]]]: | |
| for idx_parent, file in enumerate(files): | |
| with open(file, 'r', encoding='utf-8') as f: | |
| contents = '<?xml version="1.0" encoding="UTF-8"?><packet>' + f.read() + '</packet>' | |
| root = ET.fromstring(contents) | |
| for idx, chat in enumerate(root.iter('chat')): | |
| if 'deleted' in chat.attrib: | |
| continue | |
| chat_attrib = { | |
| 'thread': chat.attrib.get('thread', 'unknown'), | |
| 'no': int(chat.attrib.get('no', 0)), | |
| 'vpos': int(chat.attrib.get('vpos', 0)), | |
| 'date': int(chat.attrib.get('date', 0)), | |
| 'date_usec': int(chat.attrib.get('date_usec', 0)), | |
| 'user_id': chat.attrib.get('user_id', 'unknown'), | |
| 'mail': chat.attrib.get('mail', None), | |
| 'premium': chat.attrib.get('premium', '0') == '1', | |
| 'anonymity': chat.attrib.get('anonymity', '0') == '1', | |
| } | |
| yield idx_parent * 1000000 + idx, {**chat_attrib, 'content': chat.text} | |