Datasets:
kinnews_kirnews

	# 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.
	"""Kinyarwanda and Kirundi news classification datasets."""


	import csv
	import os

	import datasets


	_CITATION = """\
	@article{niyongabo2020kinnews,
	title={KINNEWS and KIRNEWS: Benchmarking Cross-Lingual Text Classification for Kinyarwanda and Kirundi},
	author={Niyongabo, Rubungo Andre and Qu, Hong and Kreutzer, Julia and Huang, Li},
	journal={arXiv preprint arXiv:2010.12174},
	year={2020}
	}
	"""

	_DESCRIPTION = """\
	Kinyarwanda and Kirundi news classification datasets
	"""

	_HOMEPAGE = "https://github.com/Andrews2017/KINNEWS-and-KIRNEWS-Corpus"
	_LICENSE = "MIT License"

	_URLs = {
	"kinnews": "https://github.com/saradhix/kinnews_kirnews/raw/master/KINNEWS.zip",
	"kirnews": "https://github.com/saradhix/kinnews_kirnews/raw/master/KIRNEWS.zip",
	}


	class KinnewsKirnews(datasets.GeneratorBasedBuilder):
	"""This is Kinyarwanda and Kirundi news dataset called KINNEWS and KIRNEWS."""

	VERSION = datasets.Version("1.1.0")

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(name="kinnews_raw", description="Dataset for Kinyarwanda language"),
	datasets.BuilderConfig(name="kinnews_cleaned", description="Cleaned dataset for Kinyarwanda language"),
	datasets.BuilderConfig(name="kirnews_raw", description="Dataset for Kirundi language"),
	datasets.BuilderConfig(name="kirnews_cleaned", description="Cleaned dataset for Kirundi language"),
	]
	class_labels = [
	"politics",
	"sport",
	"economy",
	"health",
	"entertainment",
	"history",
	"technology",
	"tourism",
	"culture",
	"fashion",
	"religion",
	"environment",
	"education",
	"relationship",
	]
	label_columns = {"kinnews_raw": "kin_label", "kirnews_raw": "kir_label"}

	def _info(self):
	if "raw" in self.config.name:
	features = datasets.Features(
	{
	"label": datasets.ClassLabel(names=self.class_labels),
	self.label_columns[self.config.name]: datasets.Value("string"),
	"en_label": datasets.Value("string"),
	"url": datasets.Value("string"),
	"title": datasets.Value("string"),
	"content": datasets.Value("string"),
	}
	)
	else:
	features = datasets.Features(
	{
	"label": datasets.ClassLabel(names=self.class_labels),
	"title": datasets.Value("string"),
	"content": datasets.Value("string"),
	}
	)
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features,
	supervised_keys=None,
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	lang, kind = self.config.name.split("_")
	data_dir = dl_manager.download_and_extract(_URLs[lang])
	lang_dir = lang.upper()

	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"filepath": os.path.join(data_dir, lang_dir, kind, "train.csv"),
	"split": "train",
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={"filepath": os.path.join(data_dir, lang_dir, kind, "test.csv"), "split": "test"},
	),
	]

	def _generate_examples(self, filepath, split):
	"""Yields examples."""

	with open(filepath, encoding="utf-8") as csv_file:
	csv_reader = csv.reader(
	csv_file, quotechar='"', delimiter=",", quoting=csv.QUOTE_ALL, skipinitialspace=True
	)
	next(csv_reader)

	for id_, row in enumerate(csv_reader):
	if "raw" in self.config.name:
	label, k_label, en_label, url, title, content = row
	yield id_, {
	"label": self.class_labels[int(label) - 1],
	self.label_columns[self.config.name]: k_label,
	"en_label": en_label,
	"url": url,
	"title": title,
	"content": content,
	}
	else:
	label, title, content = row
	yield id_, {
	"label": self.class_labels[int(label) - 1],
	"title": title,
	"content": content,
	}