# coding=utf-8

"""IRMAS dataset."""

import os
import re
import textwrap
import datasets
import itertools
import typing as tp
from pathlib import Path

SAMPLE_RATE = 44_100

_IRMAS_TRAIN_SET_URL = 'https://zenodo.org/record/1290750/files/IRMAS-TrainingData.zip'
_IRMAS_TEST_SET_PART1_URL = 'https://zenodo.org/record/1290750/files/IRMAS-TestingData-Part1.zip'
_IRMAS_TEST_SET_PART2_URL = 'https://zenodo.org/record/1290750/files/IRMAS-TestingData-Part2.zip'
_IRMAS_TEST_SET_PART3_URL = 'https://zenodo.org/record/1290750/files/IRMAS-TestingData-Part3.zip'


INSTRUMENTS = [
    'cel', 'cla', 'flu', 'gac', 'gel', 'org', 'pia', 'sax', 'tru', 'vio', 'voi'
]


class IRMASConfig(datasets.BuilderConfig):
    """BuilderConfig for IRMAS."""
    
    def __init__(self, features, **kwargs):
        super(IRMASConfig, self).__init__(version=datasets.Version("0.0.1", ""), **kwargs)
        self.features = features


class IRMAS(datasets.GeneratorBasedBuilder):

    BUILDER_CONFIGS = [
        IRMASConfig(
            features=datasets.Features(
                {
                    "file": datasets.Value("string"),
                    "audio": datasets.Audio(sampling_rate=SAMPLE_RATE),
                    "instrument": datasets.Sequence(datasets.Value("string")),
                    "label": datasets.Sequence(datasets.ClassLabel(names=INSTRUMENTS)),
                }
            ),
            name="irmas", 
            description=textwrap.dedent(
                """\
                IRMAS is intended to be used for training and testing methods for the automatic recognition of predominant instruments in musical audio. 
                The instruments considered are: cello, clarinet, flute, acoustic guitar, electric guitar, organ, piano, saxophone, trumpet, violin, and human singing voice.
                """
            ),
        ), 
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description="",
            features=self.config.features,
            supervised_keys=None,
            homepage="https://zenodo.org/records/1290750",
            citation="""
                @inproceedings{bosch2012comparison,
                  title={A Comparison of Sound Segregation Techniques for Predominant Instrument Recognition in Musical Audio Signals.},
                  author={Bosch, Juan J and Janer, Jordi and Fuhrmann, Ferdinand and Herrera, Perfecto},
                  booktitle={ISMIR},
                  pages={559--564},
                  year={2012}
                }
            """,
            task_templates=None,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        train_archive_path = dl_manager.download_and_extract(_IRMAS_TRAIN_SET_URL)
        test_archive_part1_path = dl_manager.download_and_extract(_IRMAS_TEST_SET_PART1_URL)
        test_archive_part2_path = dl_manager.download_and_extract(_IRMAS_TEST_SET_PART2_URL)
        test_archive_part3_path = dl_manager.download_and_extract(_IRMAS_TEST_SET_PART3_URL)

        extensions = ['.wav']
        _, _train_walker = fast_scandir(train_archive_path, extensions, recursive=True)
        _test_walker = []
        for part in [test_archive_part1_path, test_archive_part2_path, test_archive_part3_path]:
            _, _walker = fast_scandir(part, extensions, recursive=True)
            _test_walker.extend(_walker)
        
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN, gen_kwargs={"audio_filepaths": _train_walker, "split": "train"}
            ), 
            datasets.SplitGenerator(
                name=datasets.Split.TEST, gen_kwargs={"audio_filepaths": _test_walker, "split": "test"}
            ), 
        ]

    def _generate_examples(self, audio_filepaths, split=None):

        def extract_bracketed_items(filename):
            # Regex pattern to find text inside square brackets
            pattern = r'\[([^\]]+)\]'
            # Find all occurrences of the pattern
            items = re.findall(pattern, filename)
            return items

        def deduplicate(lst):
            return list(dict.fromkeys(lst))
    
        if split == 'train':
            for guid, audio_path in enumerate(audio_filepaths):
                labels = extract_bracketed_items(audio_path)
                labels = deduplicate(labels)
                labels = [label for label in labels if label in INSTRUMENTS]
                yield guid, {
                    "id": str(guid),
                    "file": audio_path, 
                    "audio": audio_path, 
                    "instrument": labels, 
                    "label": labels 
                }
                
        elif split == 'test':
            for guid, audio_path in enumerate(audio_filepaths):
                labels = []
                with open(audio_path.replace('.wav', '.txt'), 'r') as f:
                    for line in f:
                        labels.append(line.strip())
                labels = deduplicate(labels)
                yield guid, {
                    "id": str(guid),
                    "file": audio_path, 
                    "audio": audio_path, 
                    "instrument": labels, 
                    "label": labels 
                }


def fast_scandir(path: str, exts: tp.List[str], recursive: bool = False):
    # Scan files recursively faster than glob
    # From github.com/drscotthawley/aeiou/blob/main/aeiou/core.py
    subfolders, files = [], []

    try:  # hope to avoid 'permission denied' by this try
        for f in os.scandir(path):
            try:  # 'hope to avoid too many levels of symbolic links' error
                if f.is_dir():
                    subfolders.append(f.path)
                elif f.is_file():
                    if os.path.splitext(f.name)[1].lower() in exts:
                        files.append(f.path)
            except Exception:
                pass
    except Exception:
        pass

    if recursive:
        for path in list(subfolders):
            sf, f = fast_scandir(path, exts, recursive=recursive)
            subfolders.extend(sf)
            files.extend(f)  # type: ignore

    return subfolders, files