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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# TODO: Address all TODOs and remove all explanatory comments
import pandas as pd
import json
import os
import shutil
import datasets
# Find for instance the citation on arxiv or on the dataset repo/website
_CITATION = """\
@InProceedings{huggingface:dataset,
title = {French Fiscal texts},
author={Stan Bienaives
},
year={2022}
}
"""
_DESCRIPTION = """\
This dataset is an extraction from the OPENDATA/JADE. A list of case laws from the French court "Conseil d'Etat".
"""
_HOMEPAGE = "echanges.dila.gouv.fr"
_LICENSE = """/
This dataset is licensed under Creative Commons Attribution 4.0 International License.
"""
_URLS = {
"jade": "https://wisenlp.s3.eu-west-1.amazonaws.com/jade.parquet"
}
_SEED = 42
class FrenchOpenFiscalTexts(datasets.GeneratorBasedBuilder):
"""
This is the main class for the dataset.
"""
VERSION = datasets.Version("1.1.0")
def _info(self):
features = datasets.Features(
{
# "file": datasets.Value("string"),
"title": datasets.Value("string"),
"content": datasets.Value("string"),
"summary": datasets.Value("string"),
"solution": datasets.Value("string"),
"numero": datasets.Value("string"),
"publi_receuil": datasets.Value("string"),
"date": datasets.Value("string"),
}
)
return datasets.DatasetInfo(
# This is the description that will appear on the datasets page.
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
)
def _split_generators(self, dl_manager):
# self.data_dir = dl_manager.download_and_extract(_URLS["jade"])
print(dl_manager.download_config)
df = pd.read_parquet(dl_manager.download(_URLS["jade"]))
print(len(df))
print(df.head())
train = df.sample(frac=0.8,random_state=_SEED)
test = df.drop(train.index)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"dataframe": train},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={"dataframe": test},
),
]
def _generate_examples(self, dataframe):
"""
This function returns the examples in the raw (text) form.
"""
for index, row in dataframe.iterrows():
yield index, {
# "file": row["file"],
"title": row["title"],
"content": row["content"],
"summary": row["summary"],
"solution": row["solution"],
"numero": row["numero"],
"publi_receuil": row["publi_receuil"],
"date": row["date"],
}
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