# 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 """TODO: Add a description here.""" import csv import json import os import datasets # TODO: Add BibTeX citation # Find for instance the citation on arxiv or on the dataset repo/website _CITATION = """\ @InProceedings{ealvaradob:dataset, title = {Phishing Datasets}, author={Esteban Alvarado}, year={2024} } """ _DESCRIPTION = """\ Dataset designed for phishing classification tasks in various data types. """ _HOMEPAGE = "" _LICENSE = "" _URLS = { "texts": "texts.json", "urls": "urls.json", "webs": "webs.json", "combined_full": "combined_full.json", "combined_reduced": "combined_reduced.json" } class PhishingDatasets(datasets.GeneratorBasedBuilder): """Phishing Datasets Configuration""" VERSION = datasets.Version("1.1.0") BUILDER_CONFIGS = [ datasets.BuilderConfig(name="texts", version=VERSION, description="text subset"), datasets.BuilderConfig(name="urls", version=VERSION, description="urls subset"), datasets.BuilderConfig(name="webs", version=VERSION, description="webs subset"), datasets.BuilderConfig(name="combined_full", version=VERSION, description="combined dataset that have all URLs"), datasets.BuilderConfig(name="combined_reduced", version=VERSION, description="combined dataset that doesn't have all URLs for representativity issues"), ] DEFAULT_CONFIG_NAME = "combined_reduced" def _info(self): features = datasets.Features( { "text": datasets.Value("string"), "label": datasets.Value("int64"), } ) return datasets.DatasetInfo( description=_DESCRIPTION, features=features, supervised_keys=("text", "label"), homepage=_HOMEPAGE, license=_LICENSE, citation=_CITATION, ) def _split_generators(self, dl_manager): urls = _URLS[self.config.name] data_dir = dl_manager.download_and_extract(urls) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "filepath": data_dir, "split": "train", }, ), ] def _generate_examples(self, filepath, split): with open(filepath, encoding="utf-8") as f: data = json.load(f) for index, sample in enumerate(data): yield index, { "text": sample['text'], "label": sample['label'] }