Datasets:
interpress_news_category_tr_lite

	# 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.
	# Lint as: python3
	"""Turkish News Category Dataset (270K - Lite Version) - Interpress Media Monitoring Company"""


	import csv
	import os

	import datasets


	logger = datasets.logging.get_logger(__name__)


	_DESCRIPTION = """\
	It is a Turkish news data set consisting of 273601 news in 10 categories, compiled from print media and news websites between 2010 and 2017 by the Interpress (https://www.interpress.com/) media monitoring company. It has been rearranged as easily separable and with fewer classes.
	"""

	_CITATION = ""
	_LICENSE = "unknown"
	_HOMEPAGE = "https://www.interpress.com/"
	_DOWNLOAD_URL = "https://www.interpress.com/downloads/interpress_news_category_tr_270k_lite.zip"
	_DATASET_URLS = {
	"train": "interpress_news_category_tr_270k_lite_train.tsv",
	"test": "interpress_news_category_tr_270k_lite_test.tsv",
	}


	class InterpressNewsCategoryTRLiteConfig(datasets.BuilderConfig):
	"""BuilderConfig for InterpressNewsCategoryTRLite."""

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

	Args:
	**kwargs: keyword arguments forwarded to super.
	"""
	super(InterpressNewsCategoryTRLiteConfig, self).__init__(**kwargs)


	class InterpressNewsCategoryTRLite(datasets.GeneratorBasedBuilder):
	"""Turkish News Category Dataset (270K - Lite Version) - Interpress Media Monitoring Company"""

	BUILDER_CONFIGS = [
	InterpressNewsCategoryTRLiteConfig(
	name="270k_10class",
	version=datasets.Version("1.0.0"),
	description="Turkish News Category Dataset (270K - Lite Version) - Interpress Media Monitoring Company",
	),
	]

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"content": datasets.Value("string"),
	"category": datasets.features.ClassLabel(
	names=[
	"kültürsanat",
	"ekonomi",
	"siyaset",
	"eğitim",
	"dünya",
	"spor",
	"teknoloji",
	"magazin",
	"sağlık",
	"gündem",
	]
	),
	}
	),
	supervised_keys=None,
	homepage=_HOMEPAGE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	dl_dir = dl_manager.download_and_extract(_DOWNLOAD_URL)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(dl_dir, _DATASET_URLS["train"])}
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST, gen_kwargs={"filepath": os.path.join(dl_dir, _DATASET_URLS["test"])}
	),
	]

	def _generate_examples(self, filepath):
	"""Generate InterpressNewsCategoryTRLite examples."""
	logger.info("⏳ Generating examples from = %s", filepath)
	with open(filepath, encoding="utf-8") as f:
	reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
	for idx, row in enumerate(reader):
	yield idx, {
	"content": row["news"],
	"category": int(row["label"]),
	}