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ThearchyHelios
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按期累积（新 recipe_accumulate；table_versions 扩展） - 按统计期出的交叉表报表首次导入时默认「按期累积」，由人确认；一期一个构建，两期及以上物化成一份新的 SQLite 快照，不用视图 - 统计期完全相同要勾「替换该期」，部分重叠拒收，中间有空缺要确认；物化前逐期核对库哈希和行号，并集上另加行数守恒、主键唯一、日期落在所属统计期三条核对 - 配方演进分三档：新增列（早期各期为空值）、退役的列和表保留旧值（只在这次才退役时要勾）、不兼容变化只能显式「重新开始累积」 - 快照 id 在累积时含目标配方和模式；同样的输入物化两次库哈希相同，同一文件换名再传直接复用 - 说明按期合并，任何一期没核对过就不写「已核对」；各期维度取值不同、退役列、合计表都有提示，经过数字检查 修复按钮（新 recipe_fixes；执行器给问题带结构化参数） - 加入标签、移除标签、声明为合计行、分段标题改名、编辑恒等式成员、按锚点忽略行/列/区域外文字、声明占位符、声明隐藏行处理、工作表改名 - 服务端算补丁，先预览新旧配方对照、再应用，可以撤销；补丁封闭，不引入正则、自由文本常量和写死坐标；修复进确认清单 - 只改分段标题、新标题仍含原来选的词时沿用已确认的常量，不算破坏性变更；修复后只查改动过的段的认领，没改的关系交给试运行核对 框选转锚点（新 recipe_select） - 网格上框选（鼠标、键盘、区域输入），按八种用途换算成按文字认的锚点，立刻干跑比对；配方里不存坐标，泛化不了时列出原因 - 整张表挪位后同一配方照样认得；框进合计行、夹着小计、表下说明都有明确的处理 确认与对照（recipe_confirm、recipe_diff、新 recipe_compare） - 改配方后确认清单只列有变化的项（同时按本期数据比较），不用每修一次重勾十来项；新旧配方对照界面；按规则重新起草并把名字对齐到现行配方 - 改配方后已体现在配方里的回答保留，矛盾的列出来请人重答 - 「排除的行」写进回执和导入清单：隐藏行、跳过的空行、按配方忽略的行、停止后的文字行、只核对不另存的合计行 版本页（新 source_versions、api/source_versions；前端 VersionsDialog） - 快照与导入记录列表、启用旧版本（可写理由）、查看清单、移除一期、作废接受、清除原件；写操作带界面看到的当前版本，并发改动回 409，不静默丢期 - 除当前版本和被运行引用的版本外，再保留最近 3 个版本供回滚；遮罩列丢失要明确确认 期 1、期 2 遗留 - 重传撞上被改过的构建文件：能用本次上传恢复就隔离旧文件再恢复，否则回 409，不再是 500 - 跳过空行的列表不再把表下隔一行的说明读成数据；不像说明的单格行要人确认；受影响的配方构建换 id - 版本存储加进程级文件锁：第二个进程拿不到锁时不清理、不回收，写操作回 503（部署本来就是单进程）
501 lines
25 KiB
Python
501 lines
25 KiB
Python
"""9.5 的性能（WP-7）：合成 20 万行 × 10 列的列表（同 p2-probe/perf.py 的结构），量 4.9 的各项目标。
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默认跳过；`RECIPE_PERF=1` 时跑（仓库里没有现成的慢测试标记，按规格用环境变量开关）。量到的数字打印出来
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（加 -s 看得到），也经 record_property 进 junit 报告。判定照 9.5：超过目标 1.5 倍算不通过（断言失败），
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在 1–1.5 倍之间记为「待优化」（只打印，不失败）。
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量的都是真管线（default_pipeline）经接口走一遍的耗时，和用户点按钮时服务端做的事一样：
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- 暂存（POST imports/stage：扫描 + 预览 + 规则起草 + 部分干跑）≤ 扫描时间 + 3 s；
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- 单次改配方 / 回答问题（静态校验 + 部分干跑）≤ 1 s；
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- 暂存后的试运行（复用 scan_from_json，不再扫描）≤ 18 s，进程内存增量 ≤ 200 MB；
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- 上传新一期（扫描 + 试运行）≤ 25 s；整列有公式（有缓存值）的同样大小 ≤ 40 s（整列公式的表暂存后试运行
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规格没给目标，只记录）；
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- 结构仿照客流表的夹具：暂存 ≤ 1 s，单次回答 ≤ 0.5 s，试运行 ≤ 1 s。
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20 万行的夹具与 p2-probe/perf.py 一样用 openpyxl 的 write_only 写出，它不写 `<dimension>`；Excel 存盘的文件都有
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这个元素。openpyxl 只读模式打开工作簿时，缺 `<dimension>` 的工作表会被整张解析一遍（parse_dimensions 一直读到
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</sheetData>），所以每项都分「无 dimension（同 perf.py）」和「有 dimension（同 Excel 存盘）」两种各量一次，
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目标对两种一视同仁。
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夹具全部合成（假名、随机数），不调用任何模型。
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"""
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from __future__ import annotations
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import datetime as dt
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import io
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import json
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import os
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import random
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import re
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import subprocess
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import threading
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import time
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import uuid
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from pathlib import Path
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from typing import Any
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import pytest
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from httpx import ASGITransport, AsyncClient
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from app.core.config import settings
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from app.data import xlsx_cells, xlsx_scan
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from app.main import app
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from tests.fixtures.xlsx import patch_parts, sheet_part
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from tests.fixtures.xlsx.flow import flow_workbook
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pytestmark = pytest.mark.skipif(os.environ.get("RECIPE_PERF") != "1",
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reason="性能测试默认跳过：RECIPE_PERF=1 时运行（20 万行的夹具要生成十几秒）")
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XLSX = "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
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ROWS = 200_000
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SHEET = "明细"
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HEADERS = ["地区", "产品", "渠道", "门店", "日期", "销量", "单价", "金额", "成本", "备注"]
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TYPES = ["TEXT", "TEXT", "TEXT", "TEXT", "DATE", "INTEGER", "REAL", "INTEGER", "INTEGER", "TEXT"]
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FLOW_RECIPE = json.loads((Path(__file__).parent / "fixtures" / "recipes" / "flow_recipe.json").read_text("utf-8"))
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#: 超过目标的这个倍数算不通过（9.5）
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FAIL_FACTOR = 1.5
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RESULTS: list[dict[str, Any]] = []
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# --------------------------------------------------------------------------
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# 夹具
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# --------------------------------------------------------------------------
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def big_list(seed: int, *, formulas: bool = False) -> bytes:
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"""20 万行 × 10 列的列表：一列日期，无公式；formulas=True 时「金额」整列是公式（=销量+成本），并在
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压缩包层面补上缓存值、去掉 fullCalcOnLoad（模拟 Excel 保存过）。"""
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from openpyxl import Workbook
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rnd = random.Random(seed)
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wb = Workbook(write_only=True)
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ws = wb.create_sheet(SHEET)
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ws.append(HEADERS)
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cached: dict[int, int] = {}
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base = dt.date(2026, 8, 1)
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for i in range(ROWS):
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r = i + 2
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qty, cost = rnd.randint(1, 999), rnd.randint(1, 9999)
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amount: Any = rnd.randint(1, 99999)
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if formulas:
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amount = f"=F{r}+I{r}"
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cached[r] = qty + cost
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ws.append([f"区{i % 7}", f"品{i % 50}", "线上" if i % 2 else "线下", f"店{i % 300}",
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base + dt.timedelta(days=i % 31), qty, round(rnd.random() * 100, 2), amount, cost, "无"])
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buf = io.BytesIO()
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wb.save(buf)
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raw = buf.getvalue()
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edits = {"xl/workbook.xml": lambda t: t.replace(' fullCalcOnLoad="1"', "")}
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if formulas:
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pat = re.compile(r'<c r="H(\d+)"><f>([^<]*)</f><v\s*/?>(?:</v>)?</c>')
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def fill(xml: str) -> str:
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out, n = pat.subn(lambda m: f'<c r="H{m.group(1)}"><f>{m.group(2)}</f><v>{cached[int(m.group(1))]}</v></c>',
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xml)
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assert n == ROWS, n
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return out
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edits[sheet_part(raw, SHEET)] = fill
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return patch_parts(raw, edits)
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def with_dimension(raw: bytes) -> bytes:
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"""在 <sheetData> 前补上 <dimension ref="A1:J200001"/>（Excel 存盘的文件都有它）。"""
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def add(xml: str) -> str:
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assert "<dimension " not in xml
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return xml.replace("<sheetViews>", f'<dimension ref="A1:J{ROWS + 1}"/><sheetViews>', 1)
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return patch_parts(raw, {sheet_part(raw, SHEET): add})
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def list_recipe() -> dict[str, Any]:
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return {
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"recipe_format": "agentlab-recipe/2",
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"sheets": [{"id": "s1", "match": {"name": SHEET}, "blocks": [{
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"id": "明细", "layout": "list", "table": "销售明细",
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"columns": [{"header": h, "name": h, "type": t} for h, t in zip(HEADERS, TYPES)]}]}],
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"tables": [{"name": "销售明细"}],
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}
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@pytest.fixture(scope="module")
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def plain_files() -> tuple[bytes, bytes]:
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return big_list(1), big_list(2)
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@pytest.fixture(scope="module")
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def formula_files() -> tuple[bytes, bytes]:
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return big_list(3, formulas=True), big_list(4, formulas=True)
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def _variant(files: tuple[bytes, bytes], dimension: bool) -> tuple[bytes, bytes]:
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return (with_dimension(files[0]), with_dimension(files[1])) if dimension else files
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@pytest.fixture(autouse=True)
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def store(monkeypatch, tmp_path):
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data = tmp_path / "data"
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(data / "uploads").mkdir(parents=True)
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monkeypatch.setattr(settings, "data_dir", data)
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yield data
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@pytest.fixture
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async def client():
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async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test", timeout=600) as c:
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yield c
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# --------------------------------------------------------------------------
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# 计时与内存
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# --------------------------------------------------------------------------
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def _rss_mb() -> float:
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"""当前进程的常驻内存（MB）。没有 psutil，用 ps 读（macOS、Linux 都有）。"""
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out = subprocess.run(["ps", "-o", "rss=", "-p", str(os.getpid())], capture_output=True, text=True).stdout
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return int(out.strip() or 0) / 1024
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class _Peak:
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"""后台线程每 50 ms 采一次 RSS，记下这一段里的峰值。"""
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def __init__(self) -> None:
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self.base = _rss_mb()
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self.peak = self.base
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self._stop = threading.Event()
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self._t = threading.Thread(target=self._run, daemon=True)
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def _run(self) -> None:
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while not self._stop.wait(0.05):
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self.peak = max(self.peak, _rss_mb())
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def __enter__(self) -> _Peak:
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self._t.start()
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return self
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def __exit__(self, *_exc: object) -> None:
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self._stop.set()
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self._t.join()
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self.peak = max(self.peak, _rss_mb())
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@property
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def delta(self) -> float:
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return self.peak - self.base
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def judge(record_property, name: str, value: float, target: float | None, unit: str = "s") -> dict[str, Any]:
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"""记录一项实测；超过目标 1.5 倍判「不通过」，1–1.5 倍记「待优化」。target=None 是规格没给目标的项，
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只记录。返回这一行，由测试末尾的 assert_all 一并断言（量全了再判，前一项不通过不挡住后面各项的实测）。"""
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if target is None:
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row = {"item": name, "value": round(value, 2), "target": None, "unit": unit, "ratio": 0.0,
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"verdict": "仅记录（规格未给目标）"}
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RESULTS.append(row)
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record_property(name, json.dumps(row, ensure_ascii=False))
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print(f"\n[perf] {name}: {value:.2f} {unit}（规格未给目标，仅记录）")
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return row
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ratio = value / target
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verdict = "通过" if ratio <= 1 else ("待优化" if ratio <= FAIL_FACTOR else "不通过")
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row = {"item": name, "value": round(value, 2), "target": round(target, 2), "unit": unit,
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"ratio": round(ratio, 2), "verdict": verdict}
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RESULTS.append(row)
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record_property(name, json.dumps(row, ensure_ascii=False))
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print(f"\n[perf] {name}: {value:.2f} {unit}（目标 {target:.2f} {unit}，{ratio:.2f} 倍）{verdict}")
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return row
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def assert_all(rows: list[dict[str, Any]]) -> None:
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bad = [r for r in rows if r["ratio"] > FAIL_FACTOR]
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assert not bad, "超过目标 1.5 倍：" + "；".join(
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f"{r['item']} {r['value']} {r['unit']}（目标 {r['target']}，{r['ratio']} 倍）" for r in bad)
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async def _timed(coro) -> tuple[Any, float]:
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t0 = time.perf_counter()
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out = await coro
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return out, time.perf_counter() - t0
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def _confirms(st: dict[str, Any]) -> list[str]:
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return [i["id"] for i in st["trial"]["confirm_items"]]
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# --------------------------------------------------------------------------
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# 20 万行 × 10 列
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# --------------------------------------------------------------------------
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async def _big_flow(client, record_property, files: tuple[bytes, bytes], *, label: str,
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reupload_target: float, trial_target: float | None) -> list[dict[str, Any]]:
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rows: list[dict[str, Any]] = []
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first, second = files
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fn1, fn2 = f"明细_{label}_甲.xlsx", f"明细_{label}_乙.xlsx"
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# 扫描单独量一次：暂存的目标是「扫描时间 + 3 s」
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t0 = time.perf_counter()
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scan = xlsx_scan.scan(first)
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scan_s = time.perf_counter() - t0
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sheet = scan.sheets[0]
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assert sheet.nonempty == ROWS * 10 + 10 and sheet.nonempty > xlsx_cells.GRID_MAX_CELLS
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print(f"\n[perf] {label} 文件 {len(first) / 1e6:.1f} MB，扫描 {scan_s:.2f} s")
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record_property(f"{label}：扫描", round(scan_s, 2))
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# 暂存：扫描 + 预览 + 规则起草 + 部分干跑
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name = f"perf_{uuid.uuid4().hex[:8]}"
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resp, stage_s = await _timed(client.post("/api/datasources/imports/stage",
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files={"file": (fn1, first, XLSX)}, data={"name": name}))
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assert resp.status_code == 201, resp.text
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st = resp.json()
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sid = st["id"]
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assert st["draft_partial"] is True, "大表的交互干跑只看前 500 行（4.9）"
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rows.append(judge(record_property, f"{label}：暂存（扫描 + 预览 + 规则起草 + 部分干跑）", stage_s, scan_s + 3))
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# 单次回答问题（有问题时）、单次改配方：静态校验 + 部分干跑
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if st["questions"]:
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answers = {q["id"]: {"value": q["options"][0]["value"], "reason": "合成理由"} for q in st["questions"][:1]}
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resp, ans_s = await _timed(client.post(f"/api/datasources/imports/{sid}/answers", json={"answers": answers}))
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assert resp.status_code == 200, resp.text
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rows.append(judge(record_property, f"{label}：单次回答问题", ans_s, 1.0))
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resp, put_s = await _timed(client.put(f"/api/datasources/imports/{sid}/recipe", json={"recipe": list_recipe()}))
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assert resp.status_code == 200, resp.text
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st = resp.json()
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assert st["recipe_problems"] == [], st["recipe_problems"]
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assert st["draft_partial"] is True, "大表的交互干跑只看前 500 行（4.9）"
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rows.append(judge(record_property, f"{label}：单次改配方（PUT recipe）", put_s, 1.0))
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# 暂存后的试运行：复用 scan_from_json，不再扫描；量内存增量
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with _Peak() as peak:
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resp, trial_s = await _timed(client.post(f"/api/datasources/imports/{sid}/trial", json={}))
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assert resp.status_code == 200, resp.text
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st = resp.json()
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trial = st["trial"]
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assert trial["status"] == "passed", trial["problems"][:3]
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assert {t["name"]: t["rows"] for t in trial["receipt"]["tables"]} == {"销售明细": ROWS}
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rows.append(judge(record_property, f"{label}：暂存后的试运行", trial_s, trial_target))
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rows.append(judge(record_property, f"{label}：试运行的进程内存增量", peak.delta, 200.0, "MB"))
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resp = await client.post(f"/api/datasources/imports/{sid}/commit",
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json={"trial_id": trial["trial_id"], "confirmations": _confirms(st)})
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assert resp.status_code == 201, resp.text
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source_id = resp.json()["source"]["id"]
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# 上传新一期：扫描 + 按现行配方自动试运行
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with _Peak() as peak:
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resp, re_s = await _timed(client.post(f"/api/datasources/{source_id}/reupload",
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files={"file": (fn2, second, XLSX)}))
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assert resp.status_code == 201, resp.text
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st = resp.json()
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assert st["trial"]["status"] == "passed", st["trial"]["problems"][:3]
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rows.append(judge(record_property, f"{label}：上传新一期（扫描 + 试运行）", re_s, reupload_target))
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rows.append(judge(record_property, f"{label}：上传新一期的进程内存增量", peak.delta, 200.0, "MB"))
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return rows
|
||
|
||
|
||
@pytest.mark.parametrize("dimension", [False, True], ids=["no_dimension", "with_dimension"])
|
||
async def test_perf_big_list_without_formulas(client, record_property, plain_files, dimension):
|
||
label = f"20万行无公式（{'有' if dimension else '无'} dimension）"
|
||
assert_all(await _big_flow(client, record_property, _variant(plain_files, dimension), label=label,
|
||
reupload_target=25.0, trial_target=18.0))
|
||
|
||
|
||
@pytest.mark.parametrize("dimension", [False, True], ids=["no_dimension", "with_dimension"])
|
||
async def test_perf_big_list_with_formula_column(client, record_property, formula_files, dimension):
|
||
label = f"20万行整列公式（{'有' if dimension else '无'} dimension）"
|
||
# 4.9 对整列公式的表只给了「上传新一期 ≤ 40 s」；暂存后的试运行没有单独的目标，只记录
|
||
assert_all(await _big_flow(client, record_property, _variant(formula_files, dimension), label=label,
|
||
reupload_target=40.0, trial_target=None))
|
||
|
||
|
||
# --------------------------------------------------------------------------
|
||
# 结构仿照客流表的夹具
|
||
# --------------------------------------------------------------------------
|
||
|
||
|
||
async def test_perf_flow_fixture(client, record_property):
|
||
raw, fn = flow_workbook(dt.date(2026, 8, 1), 31, seed=5)
|
||
name = f"perf_{uuid.uuid4().hex[:8]}"
|
||
resp, stage_s = await _timed(client.post("/api/datasources/imports/stage",
|
||
files={"file": (fn, raw, XLSX)}, data={"name": name}))
|
||
assert resp.status_code == 201, resp.text
|
||
st = resp.json()
|
||
sid = st["id"]
|
||
rows = [judge(record_property, "客流夹具：暂存", stage_s, 1.0)]
|
||
q = st["questions"][0]
|
||
resp, ans_s = await _timed(client.post(f"/api/datasources/imports/{sid}/answers", json={"answers": {
|
||
q["id"]: {"value": q["options"][0]["value"], "reason": "合成理由"}}}))
|
||
assert resp.status_code == 200, resp.text
|
||
rows.append(judge(record_property, "客流夹具：单次回答", ans_s, 0.5))
|
||
resp, put_s = await _timed(client.put(f"/api/datasources/imports/{sid}/recipe", json={"recipe": FLOW_RECIPE}))
|
||
assert resp.status_code == 200, resp.text
|
||
rows.append(judge(record_property, "客流夹具：单次改配方", put_s, 0.5))
|
||
resp, trial_s = await _timed(client.post(f"/api/datasources/imports/{sid}/trial", json={}))
|
||
assert resp.status_code == 200, resp.text
|
||
assert resp.json()["trial"]["status"] == "passed"
|
||
rows.append(judge(record_property, "客流夹具：试运行", trial_s, 1.0))
|
||
assert_all(rows)
|
||
|
||
|
||
def teardown_module(_module) -> None:
|
||
if RESULTS:
|
||
print("\n[perf] 汇总：")
|
||
for row in RESULTS:
|
||
target = f"目标 {row['target']} {row['unit']}，{row['ratio']} 倍" if row["target"] is not None else "无目标"
|
||
print(f"[perf] {row['item']}: {row['value']} {row['unit']}（{target}，{row['verdict']}）")
|
||
|
||
|
||
# --------------------------------------------------------------------------
|
||
# 期 3（WP-8，P3-SPEC 11.5）：按期累积的物化、累积试运行、修复与框选的预览
|
||
# --------------------------------------------------------------------------
|
||
|
||
#: 12 期 × 20 万行 × 10 列的合成表（同 p3-probe/probe_perf.py 的结构：每期 30 天 × 6667 个项目，主键 (日期, 项目)）
|
||
UNION_PERIODS = 12
|
||
UNION_COLS = ["日期", "项目", "类别"] + [f"值{i}" for i in range(7)]
|
||
|
||
|
||
def _union_target() -> Any:
|
||
"""物化的目标配方：一张 10 列的表，主键 (日期, 项目)。用列表块写出这个表结构（交叉表块一段只有一个值列，造不出
|
||
10 列 × 20 万行）；物化只看 derive_tables 推出的表结构，与块的形态无关。列表表没有日期轴，U3 不跑（U3 每期每表
|
||
一条带 rowid 区间的 COUNT，量级可以忽略）。"""
|
||
from app.data.recipe_types import Recipe
|
||
|
||
return Recipe.model_validate({
|
||
"recipe_format": "agentlab-recipe/2",
|
||
"sheets": [{"id": "s1", "match": {"name": SHEET}, "blocks": [{
|
||
"id": "列表1", "layout": "list", "table": "明细",
|
||
"columns": [{"header": c, "name": c, "type": "DATE" if c == "日期" else "TEXT" if i < 3 else "INTEGER"}
|
||
for i, c in enumerate(UNION_COLS)]}]}],
|
||
"tables": [{"name": "明细", "grain": ["日期", "项目"]}],
|
||
})
|
||
|
||
|
||
def _union_part_db(path: Path, start: dt.date, seed: int) -> None:
|
||
"""一期的构建库：执行器建的那种 STRICT 表，rowid 从 1 连续（物化前要断言）。"""
|
||
import sqlite3
|
||
|
||
rnd = random.Random(seed)
|
||
per = ROWS // 30
|
||
conn = sqlite3.connect(path)
|
||
conn.execute("PRAGMA journal_mode=DELETE")
|
||
conn.execute('CREATE TABLE "明细" ("日期" TEXT NOT NULL, "项目" TEXT NOT NULL, "类别" TEXT, '
|
||
+ ", ".join(f'"值{i}" INTEGER' for i in range(7)) + ', PRIMARY KEY ("日期", "项目")) STRICT')
|
||
rows = []
|
||
for d in range(30):
|
||
day = (start + dt.timedelta(days=d)).isoformat()
|
||
for k in range(per):
|
||
rows.append((day, f"项目{k:05d}", "甲" if k % 2 else "乙", *[rnd.randint(0, 99999) for _ in range(7)]))
|
||
conn.executemany(f'INSERT INTO "明细" VALUES ({", ".join("?" * 10)})', rows)
|
||
conn.commit()
|
||
conn.close()
|
||
|
||
|
||
@pytest.fixture(scope="module")
|
||
def union_parts(tmp_path_factory) -> list[Any]:
|
||
from app.data import raw_store
|
||
from app.data.recipe_types import UnionPart
|
||
|
||
target = _union_target()
|
||
root = tmp_path_factory.mktemp("union_parts")
|
||
parts = []
|
||
for m in range(UNION_PERIODS):
|
||
start = dt.date(2025, 1, 1) + dt.timedelta(days=31 * m)
|
||
path = root / f"p{m:02d}.db"
|
||
_union_part_db(path, start, seed=700 + m)
|
||
end = start + dt.timedelta(days=29)
|
||
parts.append(UnionPart(import_id=f"imp{m:02d}", start=start.isoformat(), end=end.isoformat(),
|
||
db_path=str(path), recipe=target, db_sha256=raw_store.sha256_file(path),
|
||
table_hashes={"明细": f"{m:064x}"}))
|
||
return parts
|
||
|
||
|
||
def test_perf_materialize_twelve_periods_of_two_hundred_thousand_rows(record_property, union_parts, tmp_path,
|
||
monkeypatch):
|
||
"""11.5：12 期 × 20 万行的累积物化（各期哈希核对 + INSERT…SELECT + U1/U2 + 空值数 + 组合表哈希 + 库哈希）≤ 8 s；
|
||
其中表哈希这一步（union/1 的组合定义，不逐行重算）≤ 0.2 s。进程内存增量只记录。"""
|
||
from app.data import recipe_accumulate as ra
|
||
|
||
hashing = {"s": 0.0}
|
||
real_sha = ra.sha_json
|
||
|
||
def timed_sha(obj):
|
||
t0 = time.perf_counter()
|
||
try:
|
||
return real_sha(obj)
|
||
finally:
|
||
hashing["s"] += time.perf_counter() - t0
|
||
|
||
monkeypatch.setattr(ra, "sha_json", timed_sha)
|
||
out = tmp_path / "union.db"
|
||
with _Peak() as peak:
|
||
t0 = time.perf_counter()
|
||
report = ra.materialize_union(out, target=_union_target(), parts=union_parts)
|
||
elapsed = time.perf_counter() - t0
|
||
assert report.ok, [c for c in report.checks if c.status != "passed"]
|
||
assert report.rows == {"明细": UNION_PERIODS * (ROWS // 30) * 30}
|
||
rows = [judge(record_property, "期 3：12 期 × 20 万行累积物化（含核对、哈希）", elapsed, 8.0),
|
||
judge(record_property, "期 3：其中组合表哈希", hashing["s"], 0.2),
|
||
judge(record_property, "期 3：物化的进程内存增量", peak.delta, None, "MB"),
|
||
judge(record_property, "期 3：并集库大小", out.stat().st_size / 1e6, None, "MB")]
|
||
assert_all(rows)
|
||
|
||
|
||
async def _accumulate_first(client, seed: int) -> str:
|
||
"""参考夹具 8 月按期累积首次导入（回答问题、宽表改名、提交），返回数据源 id。"""
|
||
from tests.test_recipe_acceptance_p3 import answers_for, rename_wide
|
||
|
||
raw, fn = flow_workbook(dt.date(2026, 8, 1), 31, seed=seed)
|
||
resp = await client.post("/api/datasources/imports/stage", files={"file": (fn, raw, XLSX)},
|
||
data={"name": f"perf_{uuid.uuid4().hex[:8]}"})
|
||
st = resp.json()
|
||
st = (await client.post(f"/api/datasources/imports/{st['id']}/answers",
|
||
json={"answers": answers_for(st["questions"], "accumulate")})).json()
|
||
wide = next(t["name"] for t in st["recipe"]["tables"] if t["name"].endswith("_按日"))
|
||
st = (await client.put(f"/api/datasources/imports/{st['id']}/recipe",
|
||
json={"recipe": rename_wide(st["recipe"], wide, "日客流")})).json()
|
||
st = (await client.post(f"/api/datasources/imports/{st['id']}/trial", json={})).json()
|
||
resp = await client.post(f"/api/datasources/imports/{st['id']}/commit",
|
||
json={"trial_id": st["trial"]["trial_id"], "confirmations": _confirms(st)})
|
||
assert resp.status_code == 201, resp.text
|
||
return resp.json()["source"]["id"]
|
||
|
||
|
||
async def test_perf_flow_fixture_accumulate_trial_and_previews(client, record_property):
|
||
"""11.5：参考夹具 8 月加 9 月，试运行（含物化）≤ 1.5 s；交互路径：修复预览（D04 去掉「7-8」）、框选预览（c01 框为
|
||
列表；参考夹具框为交叉表整块，要对整张表跑规则起草）≤ 1 s。上传新一期（扫描 + 试运行 + 物化）只记录。"""
|
||
from tests.fixtures.xlsx import lab
|
||
from tests.fixtures.xlsx.drift import DRIFT_CASES
|
||
|
||
source_id = await _accumulate_first(client, seed=31)
|
||
raw, fn = flow_workbook(dt.date(2026, 9, 1), 30, seed=32)
|
||
resp, up_s = await _timed(client.post(f"/api/datasources/{source_id}/reupload",
|
||
files={"file": (fn, raw, XLSX)}))
|
||
assert resp.status_code == 201, resp.text
|
||
st = resp.json()
|
||
assert st["trial"]["status"] == "passed" and st["trial"]["accumulate"]["action"] == "append"
|
||
rows = [judge(record_property, "期 3：客流夹具 8+9 月上传新一期（扫描 + 试运行 + 物化）", up_s, None)]
|
||
resp, trial_s = await _timed(client.post(f"/api/datasources/imports/{st['id']}/trial", json={}))
|
||
assert resp.status_code == 200, resp.text
|
||
assert resp.json()["trial"]["accumulate"]["union"]["rows"] == {"日客流": 61, "时段客流": 1037,
|
||
"时段客流_表内合计": 183}
|
||
rows.append(judge(record_property, "期 3：客流夹具 8+9 月试运行（含物化）", trial_s, 1.5))
|
||
await client.delete(f"/api/datasources/imports/{st['id']}")
|
||
|
||
raw, fn = DRIFT_CASES["D04"].build(33)
|
||
st = (await client.post(f"/api/datasources/{source_id}/reupload", files={"file": (fn, raw, XLSX)})).json()
|
||
fx = next(f for f in st["fixes"] if f["kind"] == "remove_label")
|
||
resp, fix_s = await _timed(client.post(f"/api/datasources/imports/{st['id']}/edits/preview",
|
||
json={"fix": {"id": fx["id"], "option": "remove"}}))
|
||
assert resp.status_code == 200 and resp.json()["ok"], resp.text
|
||
rows.append(judge(record_property, "期 3：修复预览（D04 去掉标签）", fix_s, 1.0))
|
||
sel = {"sheet": "客流汇总", "ref": "B4:AG30", "as": "crosstab", "options": {}}
|
||
resp, cross_s = await _timed(client.post(f"/api/datasources/imports/{st['id']}/edits/preview",
|
||
json={"selection": sel}))
|
||
assert resp.status_code == 200, resp.text
|
||
rows.append(judge(record_property, "期 3：框选预览（客流夹具框为交叉表整块）", cross_s, 1.0))
|
||
|
||
raw, fn = lab.c01("literal")
|
||
st = (await client.post("/api/datasources/imports/stage", files={"file": (fn, raw, XLSX)},
|
||
data={"name": f"perf_{uuid.uuid4().hex[:8]}"})).json()
|
||
sel = {"sheet": "月报", "ref": "C5:F8", "as": "list", "options": {"header_rows": 1, "bottom": "box"}}
|
||
resp, list_s = await _timed(client.post(f"/api/datasources/imports/{st['id']}/edits/preview",
|
||
json={"selection": sel}))
|
||
assert resp.status_code == 200 and resp.json()["ok"], resp.text
|
||
rows.append(judge(record_property, "期 3：框选预览（c01 框为列表）", list_s, 1.0))
|
||
assert_all(rows)
|