import os
import tarfile
import pandas as pd
import datasets
from datasets import Audio, Value, Features
import logging
from typing import Dict, Generator, Tuple

logger = logging.getLogger(__name__)


_DESCRIPTION = """
This dataset consists of various Youtube videos in Persian language.

Note: This dataset contains raw, unvalidated transcriptions. Users are advised to:
1. Perform their own quality assessment
2. Create their own train/validation/test splits based on their specific needs
3. Validate a subset of the data if needed for their use case
"""

_CITATION = """
Use this repo info/link for citation.
"""

_LICENSE = "MIT"

_DATA_URL = [
    "clips/clips_001.tar",
    "clips/clips_002.tar",
    "clips/clips_003.tar",
    "clips/clips_004.tar",
    "clips/clips_005.tar",
    "clips/clips_006.tar",
    "clips/clips_007.tar",
    "clips/clips_008.tar",
    "clips/clips_009.tar",
    "clips/clips_010.tar",
    "clips/clips_011.tar",
    "clips/clips_012.tar",
    "clips/clips_013.tar",
    "clips/clips_014.tar",
    "clips/clips_015.tar",
    "clips/clips_016.tar",
    "clips/clips_017.tar",
    "clips/clips_018.tar",
    "clips/clips_019.tar",
    "clips/clips_020.tar",
    "clips/clips_021.tar",
]
#_DATA_URL = ["ytDataset/" + x for x in _DATA_URL][:2]

_PROMPTS_URLS = {
    #"train": "ytDataset/clips/metadata.csv"
    "train": "clips/metadata.csv"
}

class ASRDataset(datasets.GeneratorBasedBuilder):
    """ASR dataset with audio files stored in tar archives."""

    VERSION = datasets.Version("1.0.0")

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features({
                "file_name": datasets.Value("string"),
                "audio": datasets.Audio(sampling_rate=16000),
                "sentence": datasets.Value("string"),
                #"tar_file": datasets.Value("string"),
            }),
            supervised_keys=None,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators with added error handling."""

        prompts_paths = dl_manager.download_and_extract(_PROMPTS_URLS)
        archive = dl_manager.download(_DATA_URL)
        train_dir = "clips"

        try:
            return [
                datasets.SplitGenerator(
                    name=datasets.Split.TRAIN,
                    gen_kwargs={
                        #"split": "train",
                        #"data_dir": self.config.data_dir,
                        "prompts_path": prompts_paths["train"],
                        "path_to_clips": train_dir,
                        "audio_files": dl_manager.iter_archive(archive)
                    },
                ),
            ]
        except Exception as e:
            logger.error(f"Error in _split_generators: {e}")
            logger.error(traceback.format_exc())
            raise

    def _generate_examples(self, prompts_path, path_to_clips, audio_files):
        """Yields examples as (key, example) tuples."""

        sentence_map  = {}
        with open(prompts_path, encoding="utf-8") as f:
            for row in f:
                data = row.strip().split("\t", 1)
                file_name = data[0].strip()
                sentence_map[audio_path] = sentence

        id_ = 0

        tar_files = [
            "clips/clips_001.tar",
            "clips/clips_002.tar",
            "clips/clips_003.tar",
            "clips/clips_004.tar",
            "clips/clips_005.tar",
            "clips/clips_006.tar",
            "clips/clips_007.tar",
            "clips/clips_008.tar",
            "clips/clips_009.tar",
            "clips/clips_010.tar",
            "clips/clips_011.tar",
            "clips/clips_012.tar",
            "clips/clips_013.tar",
            "clips/clips_014.tar",
            "clips/clips_015.tar",
            "clips/clips_016.tar",
            "clips/clips_017.tar",
            "clips/clips_018.tar",
            "clips/clips_019.tar",
            "clips/clips_020.tar",
            "clips/clips_021.tar",
        ]
        for tar_file in tar_files:
            with tarfile.open(tar_file, 'r') as tar:
                for member in tar.getmembers():
                    file_name = member.name #"/".join([path_to_clips, member.name])

                    sentence = sentence_map.get(file_name, "")

                    audio_file =tar.extractfile(member)
                    audio = {"path": file_name, "bytes": audio_file.read()}
                    yield id_, {
                        "file_name": file_name,
                        "audio": audio,
                        "sentence": sentence
                    }
                    id_ += 1