import json
import os
import datasets

_DESCRIPTION = "Tweet eval stance subset"
_SUBSETS = ["stance_abortion", "stance_atheism", "stance_climate", "stance_feminist", "stance_hillary"]

URL = "" #https://huggingface.co/datasets/SetFit/tweet_eval_stance/resolve/main/"
_URLs = {split: {"train": URL + f"{split}/train.jsonl", "test": URL + f"{split}/test.jsonl"} for split in _SUBSETS}



class TweetEval(datasets.GeneratorBasedBuilder):
    """TweetEval Dataset."""

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(
            name=name,
            description=f"This part of my dataset covers {name} part of TweetEval Dataset.",
        ) for name in _SUBSETS
    ]

    def _info(self):
        names = ["none", "against", "favor"]
        
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                "text": datasets.Value("string"), 
                "label": datasets.Value("int32"),
                "label_text": datasets.Value("string"), 
                }
            ),
            supervised_keys=None,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        my_urls = _URLs[self.config.name]
        data_dir = dl_manager.download_and_extract(my_urls)
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                # These kwargs will be passed to _generate_examples
                gen_kwargs={"text_path": data_dir["train"]},
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                # These kwargs will be passed to _generate_examples
                gen_kwargs={"text_path": data_dir["test"]},
            ),
        ]

    def _generate_examples(self, text_path):
        """Yields examples."""
        with open(text_path, encoding="utf-8") as f:
            texts = f.readlines()
        for i, text in enumerate(texts):
            yield i, json.loads(text)