| # 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. | |
| # TODO: Address all TODOs and remove all explanatory comments | |
| """id-review-gen: An Indonesian Review Generation Dataset.""" | |
| import csv | |
| import pandas as pd | |
| import datasets | |
| _DESCRIPTION = """\ | |
| This dataset is built as a playground for review text generation. | |
| """ | |
| _HOMEPAGE = "https://github.com/jakartaresearch" | |
| # TODO: Add link to the official dataset URLs here | |
| # The HuggingFace Datasets library doesn't host the datasets but only points to the original files. | |
| # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method) | |
| _TRAIN_URL = ( | |
| "https://github.com/jakartaresearch/id-review-gen/blob/main/data/id-review-generation.csv" | |
| ) | |
| # TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case | |
| class ReviewGen(datasets.GeneratorBasedBuilder): | |
| """GooglePlayReview: An Indonesian Sentiment Analysis Dataset.""" | |
| VERSION = datasets.Version("1.0.0") | |
| def _info(self): | |
| features = datasets.Features( | |
| {"text": datasets.Value("string"), "label": datasets.Value("string")} | |
| ) | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, features=features, homepage=_HOMEPAGE | |
| ) | |
| def _split_generators(self, dl_manager): | |
| train_path = dl_manager.download_and_extract(_TRAIN_URL) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path} | |
| ) | |
| ] | |
| # method parameters are unpacked from `gen_kwargs` as given in `_split_generators` | |
| def _generate_examples(self, filepath): | |
| """Generate examples.""" | |
| df = pd.read_csv(filepath, encoding="utf-8") | |
| for item in df.itertuples(): | |
| print(item) | |
| yield item.Index, {"text": item.text, "label": item.label} | |
| # with open(filepath, encoding="utf-8") as csv_file: | |
| # csv_reader = csv.reader(csv_file, delimiter=",") | |
| # next(csv_reader) | |
| # for id_, row in enumerate(csv_reader): | |
| # text, label = row | |
| # yield id_, {"text": text, "label": label} | |