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# 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."""
import csv
import os
import datasets
logger = datasets.logging.get_logger(__name__)
_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(
f"{path_to_manual_file} does not exist. Make sure you insert a manual dir via `datasets.load_dataset('turkishmoviesentiment', data_dir=...)` that includes a file name {_FILENAME}. Manual download instructions: {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."""
logger.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])
}
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