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#!/usr/bin/python3
# -*- coding: utf-8 -*-
import argparse
from collections import defaultdict
import json
import os
from pathlib import Path
import random
import re
import sys
pwd = os.path.abspath(os.path.dirname(__file__))
sys.path.append(os.path.join(pwd, '../../'))
import pandas as pd
from tqdm import tqdm
from project_settings import project_path
def get_args():
parser = argparse.ArgumentParser()
parser.add_argument("--data_dir", default="data/youtube_spam_collection", type=str)
parser.add_argument(
"--output_file",
default=(project_path / "data/youtube_spam_collection.jsonl"),
type=str
)
args = parser.parse_args()
return args
def main():
args = get_args()
data_dir = Path(args.data_dir)
with open(args.output_file, "w", encoding="utf-8") as f:
for filename in data_dir.glob("*.csv"):
df = pd.read_csv(filename.as_posix())
for i, row in tqdm(df.iterrows(), total=len(df)):
# print(row)
text = row["CONTENT"]
label = row["CLASS"]
text = text.replace("", "")
label = "spam" if label == 1 else "ham"
if label not in ("spam", "ham"):
raise AssertionError
num = random.random()
if num < 0.9:
split = "train"
elif num < 0.95:
split = "validation"
else:
split = "test"
row = {
"text": text,
"label": label,
"category": filename.stem,
"data_source": "youtube_spam_collection",
"split": split
}
row = json.dumps(row, ensure_ascii=False)
f.write("{}\n".format(row))
return
if __name__ == '__main__':
main()
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