Upload letras-carnaval-cadiz.py

letras-carnaval-cadiz.py

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+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)
+
+        if self.config.name == "accurate":
+            return [SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["accurate"]})]
+        elif self.config.name == "midaccurate":
+            return [SplitGenerator(name=datasets.Split.TRAIN, 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