import datasets
import json
import jsonlines

logger = datasets.logging.get_logger(__name__)

_URL = "data/"
_URLS = {
    "train": _URL + "train.jsonl",
    "dev": _URL + "val.jsonl",
    "test": _URL + "test.jsonl",
    "html": _URL + "src_docs.json"
}
_VERSION = "0.0.1"
_DATASETNAME = "CroCoSum"

class SolidotSumConfig(datasets.BuilderConfig):
    """BuilderConfig for SolidotSum."""

    def __init__(self, **kwargs):
        """BuilderConfig for SolidotSum.
        Args:
          **kwargs: keyword arguments forwarded to super.
        """
        super(SolidotSumConfig, self).__init__(**kwargs)
        

class SolidotSum(datasets.GeneratorBasedBuilder):
    """SolidotSum: Summarization dataset from Solidot. """

    BUILDER_CONFIGS = [
        SolidotSumConfig(
            name="plain_text",
            version=datasets.Version(_VERSION, ""),
            description="Dataset for Chinese-English Crosslingual Code-switched Summarization",
        ),
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DATASETNAME,
            features=datasets.Features(
                {
                    "post_id": datasets.Value("string"),
                    "post_url": datasets.Value("string"),
                    "post_title": datasets.Value("string"),
                    "post_body": datasets.Value("string"),
                    "links": datasets.features.Sequence(
                        {
                            "link_id": datasets.Value("string"),
                            "link_url": datasets.Value("string"),
                            "link_title": datasets.Value("string"),
                            "link_body":datasets.Value("string")
                        }
                    ),
                }
            ),

        )

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

        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"], "html_path": downloaded_files['html']}),
            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"], "html_path": downloaded_files['html']}),
            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"], "html_path": downloaded_files['html']}),
        ]

    def _generate_examples(self, filepath, html_path):
        """This function returns the examples in the raw (text) form."""
        logger.info("generating examples from = %s", filepath)
        key = 0
        with open(html_path) as f:
            html_id_body_text_url = json.load(f)
        with jsonlines.open(filepath) as f:
            for post in f:
                post_id = post['post_id']
                post_title = post['post_title']
                post_url = post['post_url']
                post_body = post['post_text']
                link_id = post['links']
                link_urls = []
                link_title = []
                link_body = []
                
                for link in post["links"]:
                    html_content = html_id_body_text_url[str(link)]
                    link_urls.append(html_content['url'])
                    link_title.append(html_content['title'])
                    link_body.append(html_content['body'])
                    
                yield key, {
                    "post_id": post_id,
                    "post_url": post_url,
                    "post_title": post_title,
                    "post_body":post_body,
                    "links": {
                        "link_id": link_id,
                        "link_url": link_urls,
                        "link_title": link_title,
                        "link_body": link_body
                    },
                }
                key += 1