Datasets:
tashkeela

	# coding=utf-8
	# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
	#
	# 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.

	# Lint as: python3
	"""Arabic Vocalized Words Dataset."""


	import glob
	import os

	import datasets


	_DESCRIPTION = """\
	Arabic vocalized texts.
	it contains 75 million of fully vocalized words mainly\
	97 books from classical and modern Arabic language.
	"""

	_CITATION = """\
	@article{zerrouki2017tashkeela,
	title={Tashkeela: Novel corpus of Arabic vocalized texts, data for auto-diacritization systems},
	author={Zerrouki, Taha and Balla, Amar},
	journal={Data in brief},
	volume={11},
	pages={147},
	year={2017},
	publisher={Elsevier}
	}
	"""

	_HOMEPAGE = "https://sourceforge.net/projects/tashkeela/"

	_LICENSE = "GPLv2"

	_DOWNLOAD_URL = "https://sourceforge.net/projects/tashkeela/files/latest/download"


	class TashkeelaConfig(datasets.BuilderConfig):
	"""BuilderConfig for Tashkeela."""

	def __init__(self, **kwargs):
	"""BuilderConfig for Tashkeela.

	Args:
	**kwargs: keyword arguments forwarded to super.
	"""
	super(TashkeelaConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)


	class Tashkeela(datasets.GeneratorBasedBuilder):
	"""Tashkeela dataset."""

	BUILDER_CONFIGS = [
	TashkeelaConfig(
	name="plain_text",
	description="Plain text",
	)
	]

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"book": datasets.Value("string"),
	"text": datasets.Value("string"),
	}
	),
	supervised_keys=None,
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	arch_path = dl_manager.download_and_extract(_DOWNLOAD_URL)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"directory": os.path.join(arch_path, "Tashkeela-arabic-diacritized-text-utf8-0.3", "texts.txt")
	},
	),
	]

	def _generate_examples(self, directory):
	"""Generate examples."""

	for id_, file_name in enumerate(sorted(glob.glob(os.path.join(directory, "**.txt")))):
	with open(file_name, encoding="UTF-8") as f:
	yield str(id_), {"book": file_name, "text": f.read().strip()}