Datasets:
myanmar_news

	# 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.


	import csv
	import os

	import datasets
	from datasets.tasks import TextClassification


	# no BibTeX citation
	_CITATION = ""

	_DESCRIPTION = """\
	The Myanmar news dataset contains article snippets in four categories:
	Business, Entertainment, Politics, and Sport.

	These were collected in October 2017 by Aye Hninn Khine
	"""

	_LICENSE = "GPL-3.0"

	_URLs = {"default": "https://github.com/Georeactor/MyanmarNewsClassificationSystem/archive/main.zip"}


	class MyanmarNews(datasets.GeneratorBasedBuilder):
	VERSION = datasets.Version("1.0.1")

	def _info(self):
	class_names = ["Sport", "Politic", "Business", "Entertainment"]
	features = datasets.Features(
	{
	"text": datasets.Value("string"),
	"category": datasets.ClassLabel(names=class_names),
	}
	)
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features,
	supervised_keys=None,
	homepage="https://github.com/ayehninnkhine/MyanmarNewsClassificationSystem",
	license=_LICENSE,
	citation=_CITATION,
	task_templates=[TextClassification(text_column="text", label_column="category")],
	)

	def _split_generators(self, dl_manager):
	my_urls = _URLs[self.config.name]
	data_dir = dl_manager.download_and_extract(my_urls)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"filepath": os.path.join(data_dir, "MyanmarNewsClassificationSystem-main", "topics.csv"),
	"split": "train",
	},
	),
	]

	def _generate_examples(self, filepath, split):
	with open(filepath, encoding="utf-8") as f:
	rdr = csv.reader(f, delimiter="\t")
	next(rdr)
	rownum = 0
	for row in rdr:
	rownum += 1
	yield rownum, {
	"text": row[0],
	"category": row[1],
	}