#!/usr/bin/env python3
"""One-off utility: redact GitHub PAT-like strings in Data/*.csv (in place)."""
from __future__ import annotations

import re
import sys
from pathlib import Path

ROOT = Path(__file__).resolve().parents[1]
DATA = ROOT / "Data"
REDACTED = "[REDACTED_GITHUB_TOKEN]"

# Fine-grained and classic PAT shapes; require sufficient length to avoid ghp_import-style false positives.
_PATTERNS = [
    re.compile(r"github_pat_[A-Za-z0-9_]{20,}"),
    re.compile(r"ghp_[A-Za-z0-9]{36,}"),
    re.compile(r"gho_[A-Za-z0-9]{36,}"),
    re.compile(r"ghu_[A-Za-z0-9]{36,}"),
    re.compile(r"ghs_[A-Za-z0-9]{36,}"),
    re.compile(r"ghr_[A-Za-z0-9]{36,}"),
]


def redact_text(text: str) -> tuple[str, int]:
    count = 0
    for pattern in _PATTERNS:
        text, n = pattern.subn(REDACTED, text)
        count += n
    return text, count


def process_file(path: Path) -> int:
    tmp = path.with_suffix(path.suffix + ".redacting")
    total = 0
    with open(path, encoding="utf-8", errors="replace") as src, open(
        tmp, "w", encoding="utf-8", newline=""
    ) as dst:
        for line in src:
            new_line, n = redact_text(line)
            total += n
            dst.write(new_line)
    tmp.replace(path)
    return total


def main() -> None:
    if not DATA.is_dir():
        print(f"Missing {DATA}", file=sys.stderr)
        sys.exit(1)
    csv_files = sorted(DATA.rglob("*.csv"))
    grand = 0
    for path in csv_files:
        n = process_file(path)
        if n:
            print(f"  {path.relative_to(ROOT)}: {n} redaction(s)")
        grand += n
    print(f"Done. {grand} token-like string(s) redacted across {len(csv_files)} file(s).")


if __name__ == "__main__":
    main()