Created
June 18, 2021 18:30
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scruples preprocess
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"""Compare preprocessed scruples to original titles. | |
Usage: | |
python -m sc.scripts.from_scruples | |
""" | |
import code # code.interact(local=dict(globals(), **locals())) | |
import json | |
import os | |
from typing import List, Tuple, Set, Dict, Any, Optional, NamedTuple, Iterator, Callable | |
from mbforbes_python_utils import read | |
import pandas as pd | |
from tqdm import tqdm | |
from sc.scrape.person_recognizer import tokenize | |
def main() -> None: | |
pattern = "data/scruples-corpus/{}.scruples-corpus.jsonl" | |
splits = ["train", "dev", "test"] | |
res: List[Dict[str, Any]] = [] | |
total, skipped = 0, 0 | |
for split in splits: | |
lines = read(pattern.format(split)).split("\n") | |
total += len(lines) | |
for line in tqdm(lines): | |
data = json.loads(line) | |
if ( | |
"post_id" in data | |
and "action" in data | |
and data["action"] is not None | |
and "description" in data["action"] | |
): | |
res.append( | |
{ | |
"subreddit": "amitheasshole", | |
"reddit-id": data["post_id"], | |
"cleaned": data["action"]["description"], | |
"tokenized": " ".join(tokenize(data["action"]["description"])), | |
"orig": data["title"], | |
"meta": json.dumps({"scruples-split": split}), | |
} | |
) | |
else: | |
skipped += 1 | |
print(f"Skipped {skipped}/{total} ({100*skipped/total:.2f}%)") | |
os.makedirs("data/sentences/", exist_ok=True) | |
pd.DataFrame(res).to_csv( | |
"data/sentences/scruples-processed.v0.3.tsv", sep="\t", index=False | |
) | |
if __name__ == "__main__": | |
main() |
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