fix(export): 增加文档级组合复杂度预算与并发渲染限制
针对 PR 审阅 P1「组合复杂度仍可长时间占满导出线程」与 P3「EXPORT_OUTPUT_TOO_LARGE 误标 HTTP 413」: - plot: FunctionPlot 记录整块 AST 节点数(node_count),parser 累计 - html: 单篇文档累计节点预算 _MAX_TOTAL_PLOT_NODES=8000,超限回退占位 - service: 并发渲染信号量 MAX_CONCURRENT_RENDERS=2,超限额任务排队等待 - docs: 错误码区分同步 HTTP 错误与异步任务错误,EXPORT_OUTPUT_TOO_LARGE 由 error_code 返回而非 HTTP 413 - 补充节点预算与并发限制两条回归测试(全量 627 通过) Co-Authored-By: Claude Code <noreply@anthropic.com>
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@@ -43,6 +43,10 @@ MAX_JOBS = 100
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MAX_MARKDOWN_CHARS = 200_000
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# 最终导出产物大小上限,防止超大 HTML 耗尽内存/磁盘
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MAX_EXPORT_BYTES = 20 * 1024 * 1024 # 20 MB
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# 并发渲染上限:解析/渲染是 CPU 密集的同步工作,限制同时执行的任务数,
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# 防止大量任务同时占满工作线程与内存
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MAX_CONCURRENT_RENDERS = 2
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_render_slots = asyncio.Semaphore(MAX_CONCURRENT_RENDERS)
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# 产物有效期
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FILE_TTL = timedelta(hours=24)
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@@ -208,47 +212,50 @@ async def _execute(
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}
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)
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try:
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# 让出一次,使「创建后立即取消」的 queued 任务能及时进入 cancelled
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await asyncio.sleep(0)
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if cancel_event.is_set():
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raise ExportCancelled()
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# 并发渲染限额:解析/渲染是 CPU 密集的同步工作,用信号量限制同时执行的任务数,
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# 超出限额的任务在此排队等待,避免大量任务同时占满工作线程与内存
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async with _render_slots:
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# 让出一次,使「创建后立即取消」的 queued 任务能及时进入 cancelled
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await asyncio.sleep(0)
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if cancel_event.is_set():
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raise ExportCancelled()
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# 解析与渲染都是 CPU 密集的同步工作,放入线程执行避免阻塞事件循环,
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# 使运行中的取消能在渲染边界生效;写文件前再次检查取消。
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document = await asyncio.to_thread(parse_document, markdown)
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document.attributes["title"] = title
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if metadata:
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document.attributes["metadata"] = metadata
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# 解析与渲染都是 CPU 密集的同步工作,放入线程执行避免阻塞事件循环,
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# 使运行中的取消能在渲染边界生效;写文件前再次检查取消。
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document = await asyncio.to_thread(parse_document, markdown)
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document.attributes["title"] = title
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if metadata:
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document.attributes["metadata"] = metadata
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result = await asyncio.to_thread(_render_document, document, options)
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if cancel_event.is_set():
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raise ExportCancelled()
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if len(result.content) > MAX_EXPORT_BYTES:
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raise ExportTooLarge()
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result = await asyncio.to_thread(_render_document, document, options)
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if cancel_event.is_set():
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raise ExportCancelled()
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if len(result.content) > MAX_EXPORT_BYTES:
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raise ExportTooLarge()
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out_dir = get_settings().exports_path
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out_dir.mkdir(parents=True, exist_ok=True)
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path = _export_path(job_id)
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path.write_bytes(result.content)
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out_dir = get_settings().exports_path
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out_dir.mkdir(parents=True, exist_ok=True)
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path = _export_path(job_id)
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path.write_bytes(result.content)
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completed_at = _now()
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_jobs[job_id] = _jobs[job_id].model_copy(
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update={
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"status": ExportStatus.completed,
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"progress": ExportProgress(
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phase="completed", current=1, total=1, percent=1.0
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),
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"file": ExportFile(
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file_name=f"{_safe_download_name(title)}.html",
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mime_type=result.mime_type,
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size=len(result.content),
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sha256=hashlib.sha256(result.content).hexdigest(),
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expires_at=completed_at + FILE_TTL,
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),
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"warnings": result.warnings,
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"completed_at": completed_at,
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}
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)
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completed_at = _now()
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_jobs[job_id] = _jobs[job_id].model_copy(
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update={
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"status": ExportStatus.completed,
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"progress": ExportProgress(
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phase="completed", current=1, total=1, percent=1.0
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),
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"file": ExportFile(
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file_name=f"{_safe_download_name(title)}.html",
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mime_type=result.mime_type,
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size=len(result.content),
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sha256=hashlib.sha256(result.content).hexdigest(),
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expires_at=completed_at + FILE_TTL,
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),
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"warnings": result.warnings,
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"completed_at": completed_at,
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}
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)
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except ExportCancelled:
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_jobs[job_id] = _jobs[job_id].model_copy(
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update={
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