import os
import datasets
logger = datasets.logging.get_logger(__name__)
datasets.logging.set_verbosity(20)


class ParsiGoo(datasets.GeneratorBasedBuilder):
    VERSION = datasets.Version("1.0.0")

    def _info(self):
        features = datasets.Features(
            {
                "text": datasets.Value("string"),
                "audio_file": datasets.Value("string"),
                "speaker_name": datasets.Value("string"),
                "root_path": datasets.Value("string")
            }
        )
        return datasets.DatasetInfo(
            description="ParsiGoo dataset",
            features=features,
            homepage="https://example.com",
            citation="",
        )

    def _split_generators(self, dl_manager):
        logger.info("| >  ")
        print("4544444")
        print(dl_manager.manual_dir)
        # logger.info(os.path.join(os.path.dirname(os.path.abspath(__file__)), "datasets"))
        data_dir = dl_manager.download_and_extract("https://huggingface.co/datasets/Kamtera/ParsiGoo/resolve/main/datasets.zip")
        # data_dir="datasets"
        data_dir = os.path.join(data_dir, "datasets")
        print("| >  data_dir =",data_dir)
        meta_files = []
        speaker_names = os.listdir(data_dir)
        root_path = ""
        print("| >  listdir =",os.listdir(data_dir))
        for speaker_name in os.listdir(data_dir):
            # if not os.path.isdir(os.path.join(data_dir, speaker_name)):
                # continue
            root_path = os.path.join(data_dir, speaker_name)
            meta_files.append(os.path.join(root_path, "metadata.csv"))
 
        return [datasets.SplitGenerator(
                    name="train",
                    gen_kwargs={
                        "txt_files": meta_files,
                        "speaker_names": speaker_names,
                        "root_path": root_path
                    }
                )]

    def _generate_examples(self, txt_files, speaker_names, root_path):
        print(txt_files)
        id=-1
        for ind,txt_file in enumerate(txt_files):
          with open(txt_file, "r", encoding="utf-8") as ttf:
            for i, line in enumerate(ttf):
                cols = line.split("|")
                wav_file = cols[1].strip()
                text = cols[0].strip()
                wav_file = os.path.join(root_path, "wavs", wav_file)
                id+=1
                yield id, {"text": text, "audio_file": wav_file, "speaker_name": speaker_names[ind], "root_path": root_path}