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# coding=utf-8
# 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.
"""Arabic Billion Words Corpus"""
import os
import re
import datasets
_CITATION = """\
@article{el20161,
title={1.5 billion words arabic corpus},
author={El-Khair, Ibrahim Abu},
journal={arXiv preprint arXiv:1611.04033},
year={2016}
}
"""
_DESCRIPTION = """\
Abu El-Khair Corpus is an Arabic text corpus, that includes more than five million newspaper articles.
It contains over a billion and a half words in total, out of which, there are about three million unique words.
The corpus is encoded with two types of encoding, namely: UTF-8, and Windows CP-1256.
Also it was marked with two mark-up languages, namely: SGML, and XML.
"""
_HOMEPAGE = "http://abuelkhair.net/index.php/en/arabic/abu-el-khair-corpus"
_URL = "http://abuelkhair.net/corpus/"
_URLs = {
"Alittihad": _URL + "Alittihad_XML_utf_8.rar",
"Almasryalyoum": _URL + "Almasryalyoum_XML_utf_8.rar",
"Almustaqbal": _URL + "Almustaqbal_XML_utf_8.rar",
"Alqabas": _URL + "Alqabas_XML_utf_8.rar",
"Echoroukonline": _URL + "Echoroukonline_XML_utf_8.rar",
"Ryiadh": _URL + "Ryiadh_XML_utf_8.rar",
"Sabanews": _URL + "Sabanews_XML_utf_8.rar",
"SaudiYoum": _URL + "SaudiYoum_XML_utf_8.rar",
"Techreen": _URL + "Techreen_XML_utf_8.rar",
"Youm7": _URL + "Youm7_XML_utf_8.rar",
}
# Some tags are misspelled
# - Misspelled article tags:
# - Alqabas: <Alqabas>, <Alqabas1>
# - Ryiadh: <Ryiadh>, <Ryiadh1>
MISSPELLED_TAGS = {
"Dateline": ["Dateline", "dateline"],
"Headline": ["Headline", "Healine"],
"Text": ["Text"],
"URL": ["URL"],
}
TAG_PATTERNS = {
tag: [re.compile(rf".*?<{label}>(.*?)</{label}>.*?", re.MULTILINE | re.DOTALL) for label in labels]
for tag, labels in MISSPELLED_TAGS.items()
}
class ArabicBillionWords(datasets.GeneratorBasedBuilder):
"""Arabic Billion Words Corpus"""
VERSION = datasets.Version("1.1.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name="Alittihad", version=VERSION, description="This part of dataset covers Alittihad news paper"
),
datasets.BuilderConfig(
name="Almasryalyoum", version=VERSION, description="This part of dataset covers Almasryalyoum news paper"
),
datasets.BuilderConfig(
name="Almustaqbal", version=VERSION, description="This part of dataset covers Almustaqbal news paper"
),
datasets.BuilderConfig(
name="Alqabas", version=VERSION, description="This part of dataset covers Alqabas news paper"
),
datasets.BuilderConfig(
name="Echoroukonline", version=VERSION, description="This part of dataset covers Echoroukonline news paper"
),
datasets.BuilderConfig(
name="Ryiadh", version=VERSION, description="This part of dataset covers Ryiadh news paper"
),
datasets.BuilderConfig(
name="Sabanews", version=VERSION, description="This part of dataset covers Sabanews news paper"
),
datasets.BuilderConfig(
name="SaudiYoum", version=VERSION, description="This part of dataset covers SaudiYoum news paper"
),
datasets.BuilderConfig(
name="Techreen", version=VERSION, description="This part of dataset covers Techreen news paper"
),
datasets.BuilderConfig(
name="Youm7", version=VERSION, description="This part of dataset covers Youm7 news paper"
),
]
def _info(self):
features = datasets.Features(
{
"url": datasets.Value("string"),
"head_line": datasets.Value("string"),
"date": datasets.Value("string"),
"text": datasets.Value("string"),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
my_urls = _URLs[self.config.name]
data_dir = dl_manager.download_and_extract(my_urls)
my_file_name = f"{self.config.name}_utf_8.xml"
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"filepath": os.path.join(data_dir, my_file_name),
},
),
]
def _generate_examples(self, filepath):
"""Yields examples."""
data_tag = self.config.name
pattern = re.compile(rf".*?<{data_tag}(.*?)</{data_tag}.*?", re.MULTILINE | re.DOTALL)
key = 0
lines = ""
with open(filepath, mode="r", encoding="utf-8") as f:
for i, line in enumerate(f):
lines += line
if f"</{data_tag}" in line:
match = pattern.match(lines)
lines = ""
if match:
record = match.group(1)
text = self._clean_text(self._extract_tag("Text", record))
url = self._extract_tag("URL", record)
head_line = self._clean_text(self._extract_tag("Headline", record))
date = self._extract_tag("Dateline", record)
yield key, {"url": url, "head_line": head_line, "date": date, "text": text}
key += 1
@staticmethod
def _extract_tag(tag, text):
# check if the tag is misspelled
for pattern in TAG_PATTERNS[tag]:
match = pattern.match(text)
if match:
return match.group(1)
return ""
@staticmethod
def _clean_text(text):
return text.replace("?", "")
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