Datasets:

marianbasti
/

jurisprudencia-Argentina-SAIJ

Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      JSON parse error: Column(/referencias-normativas/referencia-normativa) changed from array to object in row 2
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 160, in _generate_tables
                  df = pandas_read_json(f)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
                  return pd.read_json(path_or_buf, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 815, in read_json
                  return json_reader.read()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1025, in read
                  obj = self._get_object_parser(self.data)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1051, in _get_object_parser
                  obj = FrameParser(json, **kwargs).parse()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1187, in parse
                  self._parse()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1403, in _parse
                  ujson_loads(json, precise_float=self.precise_float), dtype=None
              ValueError: Trailing data
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 233, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2998, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1918, in _head
                  return _examples_to_batch(list(self.take(n)))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2093, in __iter__
                  for key, example in ex_iterable:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1576, in __iter__
                  for key_example in islice(self.ex_iterable, self.n - ex_iterable_num_taken):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 279, in __iter__
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 163, in _generate_tables
                  raise e
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 137, in _generate_tables
                  pa_table = paj.read_json(
                File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: JSON parse error: Column(/referencias-normativas/referencia-normativa) changed from array to object in row 2

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Jurisprudencia de la Repùblica Argentina - Sistema Argentino de Información Jurídica

Este dataset es actualizado diariamente con la información de SAIJ utilizando la librería de SandboxAI

Formato

El formato del dataset es el siguiente:

{
  "numero-sumario": "Número de identificación del sumario",
  "materia": "Área del derecho a la que pertenece el caso",
  "timestamp": "Fecha y hora de creación del registro",
  "timestamp-m": "Fecha y hora de la última modificación del registro",
  "sumario": "Resumen del caso",
  "caratula": "Título del caso",
  "descriptores": {
    "descriptor": [
      {
        "elegido": {
          "termino": "Término elegido para describir al caso"
        },
        "preferido": {
          "termino": "Término preferido para describir al caso"
        },
        "sinonimos": {
          "termino": ["Lista de sinónimos"]
        }
      }
    ],
    "suggest": {
      "termino": ["Lista de términos sugeridos"]
    }
  },
  "fecha": "Fecha del caso",
  "instancia": "Instancia judicial",
  "jurisdiccion": {
    "codigo": "Código de la jurisdicción",
    "descripcion": "Descripción de la jurisdicción",
    "capital": "Capital de la jurisdicción",
    "id-pais": "ID del país"
  },
  "numero-interno": "Número interno del caso",
  "provincia": "Provincia donde se lleva el caso",
  "tipo-tribunal": "Tipo de tribunal",
  "referencias-normativas": {
    "referencia-normativa": {
      "cr": "Referencia cruzada",
      "id": "ID de la referencia normativa",
      "ref": "Referencia normativa"
    }
  },
  "fecha-alta": "Fecha de alta del registro",
  "fecha-mod": "Fecha de última modificación del registro",
  "fuente": "Fuente del registro",
  "uid-alta": "UID de alta",
  "uid-mod": "UID de modificación",
  "texto": "Texto completo del caso",
  "id-infojus": "ID de Infojus",
  "titulo": "Título del sumario",
  "guid": "GUID del registro"
}

Uso

Podés usar este dataset sin descargarlo por completo, trayendo data filtrada con un solo query. Podes hacerlo así:

# En este ejemplo, filtramos entradas por fecha
import requests
API_TOKEN = "tu_api_token"
headers = {"Authorization": f"Bearer {API_TOKEN}"}
date='2024-03-01'
API_URL = f"https://datasets-server.huggingface.co/filter?dataset=marianbasti/jurisprudencia-Argentina-SAIJ&config=default&split=train&where=timestamp='{date}T00:00:00'"
def query():
    response = requests.get(API_URL, headers=headers)
    return response.json()
data = query()

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