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#!/usr/bin/python3
# -*- coding: utf-8 -*-
from collections import defaultdict
import json
from pathlib import Path
import random
import re
from typing import Any, Dict, List, Tuple
import datasets
_urls = {
"enron_spam": "data/enron_spam.jsonl",
"enron_spam_subset": "data/enron_spam_subset.jsonl",
"ling_spam": "data/ling_spam.jsonl",
"sms_spam": "data/sms_spam.jsonl",
"spam_assassin": "data/spam_assassin.jsonl",
"spam_detection": "data/spam_detection.jsonl",
"spam_emails": "data/spam_emails.jsonl",
"spam_message": "data/spam_message.jsonl",
"spam_message_lr": "data/spam_message_lr.jsonl",
"trec07p": "data/trec07p.jsonl",
"youtube_spam_collection": "data/youtube_spam_collection.jsonl",
}
_CITATION = """\
@dataset{spam_detect,
author = {Xing Tian},
title = {spam_detect},
month = sep,
year = 2023,
publisher = {Xing Tian},
version = {1.0},
}
"""
class SpamDetect(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.0.0")
intent_configs = list()
for name in _urls.keys():
config = datasets.BuilderConfig(name=name, version=VERSION, description=name)
intent_configs.append(config)
BUILDER_CONFIGS = [
*intent_configs,
]
def _info(self):
features = datasets.Features({
"text": datasets.Value("string"),
"label": datasets.Value("string"),
"category": datasets.Value("string"),
"data_source": datasets.Value("string"),
})
return datasets.DatasetInfo(
features=features,
supervised_keys=None,
homepage="",
license="",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
url = _urls[self.config.name]
dl_path = dl_manager.download(url)
archive_path = dl_path
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"archive_path": archive_path, "split": "train"},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={"archive_path": archive_path, "split": "validation"},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={"archive_path": archive_path, "split": "test"},
),
]
def _generate_examples(self, archive_path, split):
"""Yields examples."""
archive_path = Path(archive_path)
idx = 0
with open(archive_path, "r", encoding="utf-8") as f:
for row in f:
sample = json.loads(row)
if sample["split"] != split:
continue
yield idx, {
"text": sample["text"],
"label": sample["label"],
"category": sample["category"],
"data_source": sample["data_source"],
}
idx += 1
if __name__ == '__main__':
pass
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