Datasets:

StanBienaives
/

french-open-fiscal-texts

Languages: French

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french-open-fiscal-texts / french-open-fiscal-texts.py

StanBienaives

loader file should have the repo name

e615d9b about 2 years ago

raw history blame contribute delete

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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"],
	}