File size: 3,249 Bytes
a6c12ae |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 |
# 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"])
df = pd.read_parquet(self.data_dir)
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"],
}
|