#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import glob
import json
import os
from functools import partial
from pathlib import Path

import datasets

VERSION = datasets.Version("0.0.1")

SAMPLE_RATE = 16000

URLS = {'introduction_psychology': 'data/introduction_psychology.zip',
        'a_descriptive_statistics': 'data/a_descriptive_statistics.zip',
        'inherited_how_does_the_internet_work': 'data/inherited_how_does_the_internet_work.zip',
        'data_structures': 'data/data_structures.zip',
        'computational_thinking': 'data/computational_thinking.zip',
        'physics_intro': 'data/physics_intro.zip',
        'data_intro': 'data/data_intro.zip',
        'introduction_to_the_philosophy_of_education': 'data/introduction_to_the_philosophy_of_education.zip',
        'yad_vashem': 'data/yad_vashem.zip',
        'algorithms': 'data/algorithms.zip',
        'blue-and-white_tv': 'data/blue-and-white_tv.zip',
        'covid_mindfulness': 'data/covid_mindfulness.zip',
        'preparation_for_a_job_interview-_ways_to_success': 'data/preparation_for_a_job_interview-_ways_to_success.zip',
        'what_is_the_world_introduction_to_general_chemistry': 'data/what_is_the_world_introduction_to_general_chemistry.zip',
        'networking_create_a_network_of_professional_progress': 'data/networking_create_a_network_of_professional_progress.zip',
        'how_to_learn': 'data/how_to_learn.zip',
        'post_modern_education': 'data/post_modern_education.zip',
        'introduction_to_renewable_energy': 'data/introduction_to_renewable_energy.zip',
        'science_communication': 'data/science_communication.zip',
        'introduction_to_physics_-_mechanics': 'data/introduction_to_physics_-_mechanics.zip',
        'negotiations_different_cultures_and_what_between_them': 'data/negotiations_different_cultures_and_what_between_them.zip',
        'computation_models': 'data/computation_models.zip',
        'object_oriented_programming': 'data/object_oriented_programming.zip',
        'from_another_angle_math': 'data/from_another_angle_math.zip'}


class CampusHebrewSpeech(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIGS = [
        datasets.BuilderConfig(name="campus_hebrew_speech",
                               version=VERSION,
                               description=f"Campus Hebrew Speech Recognition dataset")
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description="Hebrew speech datasets",
            features=datasets.Features(
                {
                    "uid": datasets.Value("string"),
                    "file_id": datasets.Value("string"),
                    "audio": datasets.Audio(sampling_rate=SAMPLE_RATE),
                    "sentence": datasets.Value("string"),
                    "n_segment": datasets.Value("int32"),
                    "duration_ms": datasets.Value("float32"),
                    "language": datasets.Value("string"),
                    "sample_rate": datasets.Value("int32"),
                    "course": datasets.Value("string"),
                    "sentence_length": datasets.Value("int32"),
                    "n_tokens": datasets.Value("int32"),
                }
            ),
            supervised_keys=("audio", "sentence"),
            homepage="https://huggingface.co/datasets/imvladikon/hebrew_speech_campus",
            citation="TODO",
        )

    def _split_generators(self, dl_manager):
        # course_links = {
        #     course: dl_manager.download_and_extract(link) + "/" + course
        #     for course, link in URLS.items()
        # }
        course_links = {
            'from_another_angle-_mathematics_teaching_practices': 'data/from_another_angle-_mathematics_teaching_practices',
            'introduction_to_renewable_energy': 'data/introduction_to_renewable_energy',
            'negotiations_different_cultures_and_what_between_them': 'data/negotiations_different_cultures_and_what_between_them',
            'introduction_to_physics_-_mechanics': 'data/introduction_to_physics_-_mechanics',
            'networking-_create_a_network_of_professional_progress': 'data/networking-_create_a_network_of_professional_progress',
            'post_modern_education': 'data/post_modern_education',
            'physics_intro': 'data/physics_intro',
            'algorithms': 'data/algorithms',
            'blue-and-white_tv': 'data/blue-and-white_tv',
            'what_is_the_world-_introduction_to_general_chemistry': 'data/what_is_the_world-_introduction_to_general_chemistry',
            'computational_thinking': 'data/computational_thinking',
            'preparation_for_a_job_interview-_ways_to_success': 'data/preparation_for_a_job_interview-_ways_to_success',
            'a_descriptive_statistics': 'data/a_descriptive_statistics',
            'yad_vashem': 'data/yad_vashem',
            'introduction_to_the_philosophy_of_education': 'data/introduction_to_the_philosophy_of_education',
            'covid_mindfulness': 'data/covid_mindfulness',
            'data_structures': 'data/data_structures',
            'computation_models': 'data/computation_models',
            'introduction_psychology': 'data/introduction_psychology',
            'how_to_learn': 'data/how_to_learn',
            'inherited_-_how_does_the_internet_work': 'data/inherited_-_how_does_the_internet_work',
            'object_oriented_programming': 'data/object_oriented_programming',
            'science_communication': 'data/science_communication',
            'data_intro': 'data/data_intro'}

        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "course_links": course_links,
                    "split": "train"},
            )
        ]

    def _generate_examples(self, course_links, split):
        idx = 0
        for course, root_path in course_links.items():
            root_path = "/content/hebrew_speech_campus/" + root_path
            for metadata_file in Path(root_path).glob("*.json"):
                audio_file = Path(metadata_file).stem + ".wav"
                metadata = json.load(open(metadata_file, encoding="utf-8"))
                yield idx, {
                    "uid": metadata["file"].split("_")[0],
                    "file_id": Path(metadata["file"]).stem,
                    "audio": os.path.join(root_path, audio_file),
                    "sentence": metadata["text"],
                    "n_segment": metadata["n_segment"],
                    "duration_ms": 1000 * metadata["duration"],
                    "language": metadata["language"],
                    "sample_rate": SAMPLE_RATE,
                    "course": course,
                    "sentence_length": len(metadata["text"]),
                    "n_tokens": metadata["text"].count(" ") + 1,
                }
                idx += 1