Datasets:
turkish_movie_sentiment

	# 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
	"""TurkishMovieSentiment: This dataset contains turkish movie reviews."""

	from __future__ import absolute_import, division, print_function

	import csv
	import logging
	import os

	import datasets


	_DESCRIPTION = """\
	This data set is a dataset from kaggle consisting of Turkish movie reviews and scored between 0-5.
	"""

	_CITATION = ""
	_LICENSE = "CC0: Public Domain"
	_HOMEPAGE = "https://www.kaggle.com/mustfkeskin/turkish-movie-sentiment-analysis-dataset"
	_FILENAME = "turkish_movie_sentiment_dataset.csv"


	class TurkishMovieSentimentConfig(datasets.BuilderConfig):
	"""BuilderConfig for TurkishMovieSentiment"""

	def __init__(self, **kwargs):
	"""BuilderConfig for TurkishMovieSentiment.
	Args:
	**kwargs: keyword arguments forwarded to super.
	"""
	super(TurkishMovieSentimentConfig, self).__init__(**kwargs)


	class TurkishMovieSentiment(datasets.GeneratorBasedBuilder):
	"""TurkishMovieSentiment: This dataset contains turkish movie reviews."""

	BUILDER_CONFIGS = [
	TurkishMovieSentimentConfig(
	name="turkishmoviesentiment",
	version=datasets.Version("1.0.0"),
	description="This dataset contains turkish movie reviews.",
	),
	]

	@property
	def manual_download_instructions(self):
	return """\
	You need to go to https://www.kaggle.com/mustfkeskin/turkish-movie-sentiment-analysis-dataset,
	and manually download the TurkishMovieSentiment. Once it is completed,
	a file named archive.zip will be appeared in your Downloads folder
	or whichever folder your browser chooses to save files to. You then have
	to unzip the file and move turkish_movie_sentiment_dataset.csv under <path/to/folder>.
	The <path/to/folder> can e.g. be "~/manual_data".
	TurkishMovieSentiment can then be loaded using the following command `datasets.load_dataset("turkishmoviesentiment", data_dir="<path/to/folder>")`.
	"""

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"point": datasets.Value("float32"),
	"comment": datasets.Value("string"),
	"film_name": datasets.Value("string"),
	}
	),
	supervised_keys=None,
	# Homepage of the dataset for documentation
	homepage=_HOMEPAGE,
	# License for the dataset if available
	license=_LICENSE,
	# Citation for the dataset
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	path_to_manual_file = os.path.abspath(os.path.expanduser(dl_manager.manual_dir))
	if not os.path.exists(path_to_manual_file):
	raise FileNotFoundError(
	"{} does not exist. Make sure you insert a manual dir via `datasets.load_dataset('turkishmoviesentiment', data_dir=...)` that includes a file name {}. Manual download instructions: {})".format(
	path_to_manual_file, _FILENAME, self.manual_download_instructions
	)
	)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(path_to_manual_file, _FILENAME)}
	)
	]

	def _generate_examples(self, filepath):
	"""Generate TurkishMovieSentiment examples."""
	logging.info("⏳ Generating examples from = %s", filepath)
	with open(filepath, encoding="utf-8") as f:
	rdr = csv.reader(f, delimiter=",")
	next(rdr)
	rownum = 0
	for row in rdr:
	rownum += 1
	yield rownum, {
	"comment": row[0],
	"film_name": row[1],
	"point": row[2].replace(",", "."), # convert string to floating point ([0-5])
	}