Datasets:
farsi_news

	# Copyright 2020 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
	"""Farsi News Datasets: Hamshahri and RadioFarda"""


	import json

	import datasets


	_CITATION = """\
	"""

	_DESCRIPTION = """\
	Contains Farsi (Persian) datasets for Machine Learning tasks, particularly NLP.
	These datasets have been extracted from the RSS feed of two Farsi news agency websites:

	- Hamshahri
	- RadioFarda
	"""

	_URL = "https://raw.githubusercontent.com/sci2lab/Farsi-datasets/master/farsi_news/"
	_URLS = {
	"hamshahri": _URL + "hamshahri.json",
	"radiofarda": _URL + "radiofarda.json",
	}


	class FarsiNews(datasets.GeneratorBasedBuilder):
	"""Farsi News Datasets: Hamshahri and RadioFarda"""

	VERSION = datasets.Version("1.0.0")

	def _info(self):
	return datasets.DatasetInfo(
	# This is the description that will appear on the datasets page.
	description=_DESCRIPTION,
	# datasets.features.FeatureConnectors
	features=datasets.Features(
	{
	"title": datasets.Value("string"),
	"summary": datasets.Value("string"),
	"link": datasets.Value("string"),
	"tags": datasets.features.Sequence(datasets.Value("string")),
	}
	),
	# If there's a common (input, target) tuple from the features,
	# specify them here. They'll be used if as_supervised=True in
	# builder.as_dataset.
	supervised_keys=None,
	# Homepage of the dataset for documentation
	homepage="https://github.com/sci2lab/Farsi-datasets",
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	# dl_manager is a datasets.download.DownloadManager that can be used to
	# download and extract URLs
	urls_to_download = _URLS
	dl_dir = dl_manager.download_and_extract(urls_to_download)
	return [
	datasets.SplitGenerator(
	name="hamshahri",
	# These kwargs will be passed to _generate_examples
	gen_kwargs={"filepath": dl_dir["hamshahri"], "split": "hamshahri"},
	),
	datasets.SplitGenerator(
	name="radiofarda",
	# These kwargs will be passed to _generate_examples
	gen_kwargs={"filepath": dl_dir["radiofarda"], "split": "radiofarda"},
	),
	]

	def _generate_examples(self, filepath, split):
	"""Yields examples."""
	with open(filepath, encoding="utf-8") as f:
	data = json.load(f)
	for id_, example in enumerate(data):
	yield id_, example