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Upload letras-carnaval-cadiz.py

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  1. letras-carnaval-cadiz.py +66 -0
letras-carnaval-cadiz.py ADDED
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+ from datasets import DatasetBuilder, SplitGenerator, Split, Features, Value, Sequence, BuilderConfig
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+ from datasets.utils.download_manager import DownloadManager
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+ from typing import List, Any, Tuple
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+ import json
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+ import os
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+
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+ # Mapping for song_type and group_type
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+ song_type_mapping = {
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+ 1: "presentación",
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+ 2: "pasodoble/tango",
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+ 3: "cuplé",
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+ 4: "estribillo",
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+ 5: "popurrí",
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+ 6: "cuarteta",
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+ }
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+
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+ group_type_mapping = {
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+ 1: "coro",
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+ 2: "comparsa",
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+ 3: "chirigota",
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+ 4: "cuarteto",
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+ }
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+
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+ class CadizCarnivalConfig(BuilderConfig):
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+ def __init__(self, **kwargs):
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+ super(CadizCarnivalConfig, self).__init__(**kwargs)
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+
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+ class CadizCarnivalDataset(DatasetBuilder):
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+ VERSION = "1.0.0"
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+ BUILDER_CONFIGS = [
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+ CadizCarnivalConfig(name="accurate", description="This part of my dataset covers accurate data"),
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+ CadizCarnivalConfig(name="midaccurate", description="This part of my dataset covers midaccurate data"),
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+ ]
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+
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+ def _info(self):
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+ return Features({
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+ "id": Value("string"),
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+ "authors": Sequence(Value("string")),
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+ "song_type": Value("string"),
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+ "year": Value("string"),
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+ "group": Value("string"),
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+ "group_type": Value("string"),
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+ "lyric": Sequence(Value("string")),
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+ })
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+
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+ def _split_generators(self, dl_manager: DownloadManager) -> List[SplitGenerator]:
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+ urls_to_download = {
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+ "accurate": "https://huggingface.co/datasets/IES-Rafael-Alberti/letras-carnaval-cadiz/raw/main/data/accurate-00000-of-00001.json",
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+ "midaccurate": "https://huggingface.co/datasets/IES-Rafael-Alberti/letras-carnaval-cadiz/raw/main/data/midaccurate-00000-of-00001.json"
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+ }
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+ downloaded_files = dl_manager.download_and_extract(urls_to_download)
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+
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+ if self.config.name == "accurate":
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+ return [SplitGenerator(name="accurate", gen_kwargs={"filepath": downloaded_files["accurate"]})]
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+ elif self.config.name == "midaccurate":
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+ return [SplitGenerator(name="midaccurate", gen_kwargs={"filepath": downloaded_files["midaccurate"]})]
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+
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+
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+
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+ def _generate_examples(self, filepath: str) -> Tuple[str, Any]:
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+ with open(filepath, encoding="utf-8") as f:
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+ data = json.load(f)
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+ for item in data:
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+ item["song_type"] = song_type_mapping.get(item["song_type"], "indefinido")
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+ item["group_type"] = group_type_mapping.get(item["group_type"], "indefinido")
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+ yield item["id"], item