import json
import datasets
from sklearn.model_selection import train_test_split
import pandas as pd
import os

logger = datasets.logging.get_logger(__name__)

_CITATION = """\
@article{2016arXiv160605250R,
       author = {{Rajpurkar}, Pranav and {Zhang}, Jian and {Lopyrev},
                 Konstantin and {Liang}, Percy},
        title = "{SQuAD: 100,000+ Questions for Machine Comprehension of Text}",
      journal = {arXiv e-prints},
         year = 2016,
          eid = {arXiv:1606.05250},
        pages = {arXiv:1606.05250},
archivePrefix = {arXiv},
       eprint = {1606.05250},
}
"""

_DESCRIPTION = """\
解析維基百科打包好的 bz2 檔案，解析出所需內容，利用 wikitextparser 移除 Wiki 標記。\
本資料檔是解析自維基百科 20230701 繁體中文版打包檔的內容。\
解析後保留的欄位有兩個：條目名稱（title），條目內容（page article）。\

原始的打包檔內容簡繁交雜，所以有利用 OpenCC 進行簡轉繁處理。\

原始總條目數: 4,296,654 條目。\
全部 4,296,249 個條目標題。\
全部 4,296,249 個條目內容。\
無法自動去標記的條目數: 5,415\
有內容的條目數: 4,296,249
"""

_URL = "https://huggingface.co/datasets/jslin09/wikipedia_tw"
#_URLS = {
#    "train": _URL + "train-v1.1.json",
#    "dev": _URL + "dev-v1.1.json",
#}

class WikipediaConfig(datasets.BuilderConfig):
    """BuilderConfig for Wikipedia_tw."""
    def __init__(self, **kwargs):
        """BuilderConfig for Wikipedia_tw.
        Args:
          **kwargs: keyword arguments forwarded to super.
        """
        super(WikipediaConfig, self).__init__(**kwargs)

class Wikipedia_tw(datasets.GeneratorBasedBuilder):
    """Wikipedia_tw: The Wekipedia Dataset in Traditional Chinese plain text. Version 1.0."""

    BUILDER_CONFIGS = [
        WikipediaConfig(
            name="plain_text",
            version=datasets.Version("1.0.0", ""),
            description="The Wekipedia in Traditional Chinese plain text.",
        ),
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "title": datasets.Value("string"),
                    "article": datasets.Value("string")
                }
            ),
            # No default supervised_keys (as we have to pass both question
            # and context as input).
            supervised_keys=None,
            homepage="https://huggingface.co/datasets/jslin09/wikipedia_tw",
    #        citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        downloaded_files = dl_manager.download_and_extract(_URL)

        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files}),
#            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
        ]

    def _generate_examples(self, filepath):
        logger.info("generating examples from = %s", filepath)
        key = 0
        with open(filepath, 'r', encoding='UTF-8') as f:
            wikipedia = json.load(f, strict=False,)
            for page_index in len(wikipedia):
                title = wikipedia[page_index]["title"]
                article = wikipedia[page_index]["article"]
                yield key, {
                    "title": title,
                    "article": article,
                }
            key=key+1