feat(convert): integrate process metrics into JSON and SQLite converters

- add process_metrics function to record peak RSS and CPU time
- update JSON converter to include metrics in completion marker
- modify SQLite converter to utilize new metrics for performance tracking
- enhance storage size updates with locking mechanism for concurrent access

common/storage_sizes.py

@@ -8,24 +8,45 @@ touches other formats' rows.
 from __future__ import annotations
 
 import logging
+import os
+import time
 from pathlib import Path
 
 logger = logging.getLogger(__name__)
 
 HEADER = "format,variant,bytes"
+LOCK_TIMEOUT_S = 30.0  # converters 04-07 may run in parallel; the update is a
+LOCK_POLL_S = 0.2      # read-modify-write, so it is serialized via a lock file
 
 
 def update_storage_sizes(bench_dir: Path, fmt: str, variants: list[tuple[str, int]]) -> Path:
-	path = bench_dir / "storage_sizes.csv"
-	kept: list[str] = []
-	if path.exists():
-		lines = path.read_text(encoding="ascii").splitlines()
-		if lines and lines[0] != HEADER:
-			raise ValueError(f"{path}: unexpected header {lines[0]!r}")
-		kept = [ln for ln in lines[1:] if ln and ln.split(",", 1)[0] != fmt]
-	rows = kept + [f"{fmt},{variant},{nbytes}" for variant, nbytes in variants]
 	bench_dir.mkdir(parents=True, exist_ok=True)
-	with open(path, "w", encoding="ascii", newline="\n") as fh:
-		fh.write(HEADER + "\n" + "\n".join(rows) + "\n")
+	path = bench_dir / "storage_sizes.csv"
+	lock = bench_dir / "storage_sizes.lock"
+	fd = _acquire(lock)
+	try:
+		kept: list[str] = []
+		if path.exists():
+			lines = path.read_text(encoding="ascii").splitlines()
+			if lines and lines[0] != HEADER:
+				raise ValueError(f"{path}: unexpected header {lines[0]!r}")
+			kept = [ln for ln in lines[1:] if ln and ln.split(",", 1)[0] != fmt]
+		rows = kept + [f"{fmt},{variant},{nbytes}" for variant, nbytes in variants]
+		with open(path, "w", encoding="ascii", newline="\n") as fh:
+			fh.write(HEADER + "\n" + "\n".join(rows) + "\n")
+	finally:
+		os.close(fd)
+		lock.unlink()
 	logger.info("storage_sizes.csv: %s -> %s", fmt, ", ".join(f"{v}={b}" for v, b in variants))
 	return path
+
+
+def _acquire(lock: Path) -> int:
+	deadline = time.monotonic() + LOCK_TIMEOUT_S
+	while True:
+		try:
+			return os.open(lock, os.O_CREAT | os.O_EXCL | os.O_WRONLY)
+		except FileExistsError:
+			if time.monotonic() > deadline:
+				raise TimeoutError(f"storage_sizes lock held too long: {lock}")
+			time.sleep(LOCK_POLL_S)