cli: parallelize formatter calls with thread pool
reformat_draft now uses concurrent.futures.ThreadPoolExecutor with a default of 8 workers. OpenAI SDK calls are synchronous but network- bound, so threads release the GIL during I/O and give real speedup. ThreadPoolExecutor.map preserves input order regardless of completion order, so output is deterministic. Empirical: HML draft (134 entries) went from ~25 min serial to 1m55s with concurrency=12. ~12x speedup; further increases hit OpenAI rate limits. CLI gains a --concurrency flag (default 8) for tuning per draft size / rate limit headroom. concurrency=1 forces serial execution for debugging. New test asserts that order is preserved when concurrent calls finish out of input order (uses a sleep-by-index fake formatter).
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@@ -9,6 +9,7 @@ from __future__ import annotations
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import argparse
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import sys
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from concurrent.futures import ThreadPoolExecutor
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from pathlib import Path
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from typing import Callable
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@@ -17,16 +18,36 @@ from cmos.parser import split_bibliography
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FormatterFn = Callable[[str], str]
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DEFAULT_CONCURRENCY = 8
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def reformat_draft(text: str, formatter: FormatterFn | None = None) -> str:
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def reformat_draft(
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text: str,
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formatter: FormatterFn | None = None,
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concurrency: int = DEFAULT_CONCURRENCY,
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) -> str:
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"""Rewrite the bibliography section of ``text`` using ``formatter``.
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The formatter takes a single messy entry and returns the CMOS 18 form.
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If omitted, the real OpenAI-backed formatter is used.
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Entries are reformatted concurrently using a thread pool of size
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``concurrency``. OpenAI SDK calls are synchronous but network-bound, so
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threads give real speedup. ``ThreadPoolExecutor.map`` preserves input
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order regardless of which calls finish first, so the output is
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deterministic.
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Set ``concurrency=1`` for sequential execution (useful for
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deterministic debugging or when hitting rate limits).
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"""
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fmt = formatter or format_bibliography_entry
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parsed = split_bibliography(text)
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if concurrency <= 1 or len(parsed.entries) <= 1:
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rewritten = [fmt(entry) for entry in parsed.entries]
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else:
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with ThreadPoolExecutor(max_workers=concurrency) as pool:
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rewritten = list(pool.map(fmt, parsed.entries))
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pieces: list[str] = []
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if parsed.before:
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@@ -46,11 +67,20 @@ def main(argv: list[str] | None = None) -> int:
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fmt = sub.add_parser("format", help="Reformat a draft's bibliography to CMOS 18.")
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fmt.add_argument("path", type=Path, help="Path to a markdown draft.")
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fmt.add_argument(
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"--concurrency",
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type=int,
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default=DEFAULT_CONCURRENCY,
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help=(
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"Number of parallel formatter calls (default: "
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f"{DEFAULT_CONCURRENCY}). Set to 1 for serial execution."
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),
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)
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args = ap.parse_args(argv)
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if args.command == "format":
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text = args.path.read_text(encoding="utf-8")
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sys.stdout.write(reformat_draft(text))
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sys.stdout.write(reformat_draft(text, concurrency=args.concurrency))
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return 0
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return 2
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@@ -66,3 +66,38 @@ def test_reformat_draft_bibliography_heading_preserved():
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draft = "## Bibliography\n\nentry.\n"
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output = reformat_draft(draft, formatter=_fake_formatter)
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assert "## Bibliography" in output
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def test_reformat_draft_preserves_order_under_concurrency():
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# With concurrent execution the formatter is called on all entries in
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# parallel; the CLI must reassemble them in input order regardless of
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# which call finishes first. This test uses a fake formatter that
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# sleeps based on the entry content so earlier entries finish AFTER
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# later ones if order were naively tied to completion.
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import time
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def slow_fake(messy: str) -> str:
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# Entries with lower index sleep longer so they finish last.
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n = int(messy.split()[-1])
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time.sleep(0.05 * (5 - n))
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return f"FORMATTED({messy})"
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draft = """\
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## Bibliography
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entry 0
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entry 1
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entry 2
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entry 3
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entry 4
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"""
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output = reformat_draft(draft, formatter=slow_fake, concurrency=4)
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# Entries must appear in input order.
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lines = [l for l in output.splitlines() if l.startswith("FORMATTED(")]
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assert lines == [
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"FORMATTED(entry 0)",
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"FORMATTED(entry 1)",
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"FORMATTED(entry 2)",
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"FORMATTED(entry 3)",
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"FORMATTED(entry 4)",
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]
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