Delete loading script

clickbait_news_bg.py

@@ -1,119 +0,0 @@
-# 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.
-
-""" Dataset with clickbait and fake news in Bulgarian. """
-
-
-import openpyxl  # noqa: requires this pandas optional dependency for reading xlsx files
-import pandas as pd
-
-import datasets
-
-
-_CITATION = """\
-@InProceedings{clickbait_news_bg,
-title = {Dataset with clickbait and fake news in Bulgarian. Introduced for the Hack the Fake News 2017.},
-authors={Data Science Society},
-year={2017},
-url={https://gitlab.com/datasciencesociety/case_fake_news/}
-}
-"""
-
-# TODO: Add description of the dataset here
-# You can copy an official description
-_DESCRIPTION = """\
-Dataset with clickbait and fake news in Bulgarian. Introduced for the Hack the Fake News 2017.
-"""
-
-# TODO: Add a link to an official homepage for the dataset here
-_HOMEPAGE = "https://gitlab.com/datasciencesociety/case_fake_news/"
-
-# TODO: Add the licence for the dataset here if you can find it
-_LICENSE = ""
-
-# TODO: Add link to the official dataset URLs here
-# The HuggingFace dataset library don't host the datasets but only point to the original files
-# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
-_URLs = {
-    "default_train": "https://gitlab.com/datasciencesociety/case_fake_news/-/raw/master/data/FN_Training_Set.xlsx",
-    "default_validation": "https://gitlab.com/datasciencesociety/case_fake_news/-/raw/master/data/FN_Validation_Set.xlsx",
-}
-
-
-class ClickbaitNewsBG(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("1.1.0")
-    DEFAULT_CONFIG_NAME = "default"
-
-    def _info(self):
-        if self.config.name == "default":
-            features = datasets.Features(
-                {
-                    "fake_news_score": datasets.features.ClassLabel(names=["legitimate", "fake"]),
-                    "click_bait_score": datasets.features.ClassLabel(names=["normal", "clickbait"]),
-                    "content_title": datasets.Value("string"),
-                    "content_url": datasets.Value("string"),
-                    "content_published_time": datasets.Value("string"),
-                    "content": datasets.Value("string"),
-                }
-            )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        data_dir = dl_manager.download(_URLs)
-
-        return [
-            datasets.SplitGenerator(
-                name=spl_enum,
-                gen_kwargs={
-                    "filepath": data_dir[f"{self.config.name}_{spl}"],
-                    "split": spl,
-                },
-            )
-            for spl, spl_enum in [
-                ("train", datasets.Split.TRAIN),
-                ("validation", datasets.Split.VALIDATION),
-            ]
-        ]
-
-    def _generate_examples(self, filepath, split):
-        """Yields examples."""
-        keys = [
-            "fake_news_score",
-            "click_bait_score",
-            "content_title",
-            "content_url",
-            "content_published_time",
-            "content",
-        ]
-        with open(filepath, "rb") as f:
-            data = pd.read_excel(f, engine="openpyxl")
-            for id_, row in enumerate(data.itertuples()):
-                row_dict = dict()
-                for key, value in zip(keys, row[1:]):
-                    if key == "fake_news_score":
-                        row_dict[key] = "legitimate" if value == 1 else "fake"
-                    elif key == "click_bait_score":
-                        row_dict[key] = "normal" if value == 1 else "clickbait"
-                    else:
-                        row_dict[key] = str(value)
-                yield id_, row_dict