letras-carnaval-cadiz.py

from datasets import DatasetBuilder, SplitGenerator, Split, Features, Value, Sequence, BuilderConfig, GeneratorBasedBuilder
import datasets
from datasets.utils.download_manager import DownloadManager
from typing import List, Any, Tuple
import json
import os

# Mapping for song_type and group_type
song_type_mapping = {
    1: "presentación",
    2: "pasodoble/tango",
    3: "cuplé",
    4: "estribillo",
    5: "popurrí",
    6: "cuarteta",
}

group_type_mapping = {
    1: "coro",
    2: "comparsa",
    3: "chirigota",
    4: "cuarteto",
}

class CadizCarnivalConfig(BuilderConfig):
    def __init__(self, **kwargs):
        super().__init__(version=datasets.Version("1.0.2"), **kwargs)

class CadizCarnivalDataset(GeneratorBasedBuilder):
    VERSION = "1.0.0"
    BUILDER_CONFIGS = [
        CadizCarnivalConfig(name="accurate", description="This part of my dataset covers accurate data"),
        CadizCarnivalConfig(name="midaccurate", description="This part of my dataset covers midaccurate data"),
    ]

    def _info(self):
        return datasets.DatasetInfo(
        description="_DESCRIPTION",
        features=datasets.Features({
            "id": Value("string"),
            "authors": Sequence(Value("string")),
            "song_type": Value("string"),
            "year": Value("string"),
            "group": Value("string"),
            "group_type": Value("string"),
            "lyrics": Sequence(Value("string")),
        }),
        supervised_keys=None,
        homepage="https://letrascarnavalcadiz.com/",
        citation="_CITATION",
    )

    def _split_generators(self, dl_manager: DownloadManager) -> List[SplitGenerator]:
        urls_to_download = {
            "accurate": "https://huggingface.co/datasets/IES-Rafael-Alberti/letras-carnaval-cadiz/raw/main/data/accurate-00000-of-00001.json",
            "midaccurate": "https://huggingface.co/datasets/IES-Rafael-Alberti/letras-carnaval-cadiz/raw/main/data/midaccurate-00000-of-00001.json"
        }
        downloaded_files = dl_manager.download_and_extract(urls_to_download)

        return [
            SplitGenerator(name="accurate", gen_kwargs={"filepath": downloaded_files["accurate"]}),
            SplitGenerator(name="midaccurate", gen_kwargs={"filepath": downloaded_files["midaccurate"]}),
        ]


    def _generate_examples(self, filepath: str):
        with open(filepath, encoding="utf-8") as f:
            data = json.load(f)
            for item in data:
                item["song_type"] = song_type_mapping.get(item["song_type"], "indefinido")
                item["group_type"] = group_type_mapping.get(item["group_type"], "indefinido")
                yield item["id"], item