# coding=utf-8

"""UrbanSound8K dataset."""


import os
import textwrap
import datasets
import itertools
import pandas as pd
import typing as tp
from pathlib import Path
from sklearn.model_selection import train_test_split

_DATASET_URL = 'https://zenodo.org/records/1203745/files/UrbanSound8K.tar.gz?download=1'

SAMPLE_RATE = 8_000

CLASSES = [
    'air_conditioner', 
    'car_horn', 
    'children_playing', 
    'dog_bark', 
    'drilling', 
    'engine_idling', 
    'gun_shot', 
    'jackhammer', 
    'siren', 
    'street_music', 
]


class UrbanSound8KConfig(datasets.BuilderConfig):
    """BuilderConfig for UrbanSound8K."""
    
    def __init__(self, features, **kwargs):
        super(UrbanSound8KConfig, self).__init__(version=datasets.Version("0.0.1", ""), **kwargs)
        self.features = features


class UrbanSound8K(datasets.GeneratorBasedBuilder):

    BUILDER_CONFIGS = [
        UrbanSound8KConfig(
            features=datasets.Features(
                {
                    "file": datasets.Value("string"),
                    "audio": datasets.Audio(sampling_rate=SAMPLE_RATE),
                    "sound": datasets.Value("string"),
                    "label": datasets.ClassLabel(names=CLASSES),
                }
            ),
            name=f"fold{f}", 
            description='',
        ) for f in range(1, 10+1)
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description="",
            features=self.config.features,
            supervised_keys=None,
            homepage="",
            citation="",
            task_templates=None,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        archive_path = dl_manager.download_and_extract(_DATASET_URL)

        metadata_df = pd.read_csv(os.path.join(archive_path, 'UrbanSound8K/metadata', 'UrbanSound8K.csv'))
        filename2fold = {row['slice_file_name']:row['fold'] for idx, row in metadata_df.iterrows()}
        filename2class = {row['slice_file_name']:row['class'] for idx, row in metadata_df.iterrows()}

        extensions = ['.wav']
        _, _walker = fast_scandir(archive_path, extensions, recursive=True)
        _walker_with_fold = [(fileid, f'fold{filename2fold.get(Path(fileid).name)}') for fileid in _walker]

        fold = self.config.name
        folds = [f'fold{i+1}' for i in range(10)]
        train_fold = [f for f in folds if f != fold]
        test_fold = fold

        train_walker = [fileid for fileid, fold in _walker_with_fold if fold in train_fold]
        test_walker = [fileid for fileid, fold in _walker_with_fold if fold in test_fold]
            
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN, gen_kwargs={"audio_paths": train_walker, "split": "train", "metadata_df": metadata_df}
            ), 
            datasets.SplitGenerator(
                name=datasets.Split.TEST, gen_kwargs={"audio_paths": test_walker, "split": "test", "metadata_df": metadata_df}
            ), 
        ]

    def _generate_examples(self, audio_paths, split=None, metadata_df=None):
        filename2fold = {row['slice_file_name']:row['fold'] for idx, row in metadata_df.iterrows()}
        filename2class = {row['slice_file_name']:row['class'] for idx, row in metadata_df.iterrows()}
        
        for guid, audio_path in enumerate(audio_paths):
            yield guid, {
                "id": str(guid), 
                "file": audio_path, 
                "audio": audio_path, 
                "sound": filename2class.get(Path(audio_path).name), 
                "label": filename2class.get(Path(audio_path).name), 
            }


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