scripts/clean.py

"""
Clean and deduplicate the SMS Spam Collection v.1.

Source corpus:
  Almeida, T.A., Gomez Hidalgo, J.M., Yamakami, A. (2011).
  Contributions to the study of SMS Spam Filtering: New Collection and Results.
  ACM DOCENG 2011.
  https://archive.ics.uci.edu/dataset/228/sms+spam+collection

What this script does (and why):

1. Reads the raw tab-separated file (label\tmessage).
2. Fixes a small set of CP1252 control bytes (e.g. \\x91-\\x97, \\x85) that
   appear in the original file as artifacts of an earlier round-trip
   through a Windows-1252 environment. These render as control characters
   when the file is read as UTF-8; we map them to their intended
   typographic equivalents (curly quotes, en/em dashes, ellipsis).
3. Cleans whitespace in every message: strips leading/trailing whitespace
   and collapses runs of internal whitespace (multiple spaces, tabs) to a
   single space. Casing is preserved.
4. Deduplicates aggressively. The dedupe key applies:
     - NFKC unicode normalization,
     - whitespace collapse,
     - leading/trailing strip,
     - lowercase.
   The first occurrence of each normalized key is retained. No label
   conflicts exist in the corpus.
5. Writes the cleaned data to data.csv and data.jsonl.

Usage:
  python scripts/clean.py \\
      --in  /path/to/raw/SMSSpamCollection \\
      --out /path/to/SMSSpamCollectionDeduplicated
"""

from __future__ import annotations

import argparse
import csv
import json
import re
import sys
import unicodedata
from collections import Counter
from pathlib import Path

CP1252_FIXES = {
    "\x91": "'",
    "\x92": "'",
    "\x93": '"',
    "\x94": '"',
    "\x96": "-",
    "\x97": "-",
    "\x85": "...",
}


def repair_cp1252_artifacts(text: str) -> str:
    """Replace leaked CP1252 control bytes with their intended characters."""
    for bad, good in CP1252_FIXES.items():
        text = text.replace(bad, good)
    return text


def clean_whitespace(message: str) -> str:
    """Strip leading/trailing whitespace and collapse internal runs of
    whitespace (multiple spaces, tabs, etc.) to a single space.

    Applied to the stored message text. Removes typing/encoding artifacts
    without altering the semantics of the message.
    """
    return re.sub(r"\s+", " ", message.strip())


def normalized_key(message: str) -> str:
    """Build the dedupe key from a message.

    NFKC + collapse-whitespace + strip + lowercase. Aggressive enough to
    catch trivial variants; conservative enough to keep genuinely distinct
    messages separate.
    """
    s = unicodedata.normalize("NFKC", message)
    s = re.sub(r"\s+", " ", s.strip())
    return s.lower()


def load_raw(path: Path) -> list[tuple[str, str]]:
    """Read the raw tab-separated SMS file. Returns list of (label, message)."""
    content = path.read_text(encoding="utf-8")
    content = repair_cp1252_artifacts(content)
    rows: list[tuple[str, str]] = []
    for line_no, line in enumerate(content.splitlines(), start=1):
        if not line:
            continue
        if "\t" not in line:
            print(f"  warning: line {line_no} has no tab, skipping: {line!r}",
                  file=sys.stderr)
            continue
        label, _, message = line.partition("\t")
        rows.append((label.strip(), message))
    return rows


def deduplicate_and_clean(
    rows: list[tuple[str, str]],
) -> tuple[list[tuple[str, str]], int, int]:
    """Apply whitespace cleanup to each message, then deduplicate using
    normalized_key. First occurrence wins. Returns
    (cleaned_rows, num_duplicates_removed, num_messages_whitespace_changed)."""
    seen: set[str] = set()
    cleaned: list[tuple[str, str]] = []
    ws_changed = 0
    for label, message in rows:
        cleaned_message = clean_whitespace(message)
        if cleaned_message != message:
            ws_changed += 1
        key = normalized_key(cleaned_message)
        if key in seen:
            continue
        seen.add(key)
        cleaned.append((label, cleaned_message))
    return cleaned, len(rows) - len(cleaned), ws_changed


def write_csv(rows: list[tuple[str, str]], path: Path) -> None:
    """Write data as CSV with proper escaping. Columns: label, text."""
    with path.open("w", encoding="utf-8", newline="") as fp:
        writer = csv.writer(fp, quoting=csv.QUOTE_ALL)
        writer.writerow(["label", "text"])
        for label, message in rows:
            writer.writerow([label, message])


def write_jsonl(rows: list[tuple[str, str]], path: Path) -> None:
    """Write data as line-delimited JSON. Schema: {"label": ..., "text": ...}."""
    with path.open("w", encoding="utf-8") as fp:
        for label, message in rows:
            json.dump({"label": label, "text": message}, fp, ensure_ascii=False)
            fp.write("\n")


def summarize(label: str, rows: list[tuple[str, str]]) -> None:
    counts = Counter(r[0] for r in rows)
    total = sum(counts.values())
    print(f"{label}: total={total}")
    for k in sorted(counts):
        v = counts[k]
        pct = 100.0 * v / total if total else 0
        print(f"  {k}: {v} ({pct:.1f}%)")


def main() -> int:
    parser = argparse.ArgumentParser(description=__doc__,
                                     formatter_class=argparse.RawDescriptionHelpFormatter)
    parser.add_argument("--in", dest="input", required=True,
                        help="Path to raw SMSSpamCollection file")
    parser.add_argument("--out", dest="output", required=True,
                        help="Output directory for cleaned data")
    args = parser.parse_args()

    in_path = Path(args.input)
    out_dir = Path(args.output)
    out_dir.mkdir(parents=True, exist_ok=True)

    print(f"Reading raw corpus: {in_path}")
    raw = load_raw(in_path)
    summarize("Raw", raw)

    print("\nDeduplicating (NFKC + whitespace + lowercase key) ...")
    print("Also stripping leading/trailing whitespace and collapsing internal runs ...")
    deduped, removed, ws_changed = deduplicate_and_clean(raw)
    print(f"  Duplicates removed:                 {removed}")
    print(f"  Messages with whitespace changes:   {ws_changed}")
    summarize("Cleaned", deduped)

    csv_path = out_dir / "data.csv"
    jsonl_path = out_dir / "data.jsonl"
    write_csv(deduped, csv_path)
    write_jsonl(deduped, jsonl_path)

    print(f"\nWrote:")
    print(f"  {csv_path} ({csv_path.stat().st_size} bytes)")
    print(f"  {jsonl_path} ({jsonl_path.stat().st_size} bytes)")
    return 0


if __name__ == "__main__":
    raise SystemExit(main())