feat: 第三优先级完善 — CI/CD、PyPI、pre-commit、CHANGELOG、贡献指南、基准测试、ADR

.github/workflows/ci.yml

@@ -0,0 +1,48 @@
+# CI
+name: CI
+
+on:
+  push:
+    branches: [main]
+  pull_request:
+    branches: [main]
+
+jobs:
+  test:
+    name: Test (Python ${{ matrix.python-version }})
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.13"]
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install dependencies
+        run: uv sync --extra dev --extra all
+
+      - name: Run lint (ruff)
+        run: uv run ruff check src/ tests/
+
+      - name: Run type check (mypy)
+        run: uv run mypy src/ --ignore-missing-imports
+
+      - name: Run tests with coverage
+        run: |
+          uv run pytest tests/ \
+            --cov=src \
+            --cov-report=term-missing \
+            --cov-report=xml \
+            -v
+
+      - name: Upload coverage to Codecov
+        uses: codecov/codecov-action@v5
+        with:
+          files: ./coverage.xml
+          fail_ci_if_error: false

.github/workflows/publish.yml

@@ -0,0 +1,28 @@
+# Publish to PyPI
+name: Publish to PyPI
+
+on:
+  push:
+    tags:
+      - "v*"
+
+jobs:
+  publish:
+    name: Build and publish
+    runs-on: ubuntu-latest
+    permissions:
+      id-token: write
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v5
+
+      - name: Build package
+        run: uv build
+
+      - name: Publish to PyPI
+        uses: pypa/gh-action-pypi-publish@release/v1
+        with:
+          packages-dir: dist/

CHANGELOG.md

@@ -0,0 +1,41 @@
+# Changelog
+
+所有值得注意的更改都将记录在此文件中。
+
+格式基于 [Keep a Changelog](https://keepachangelog.com/zh-CN/1.0.0/)，
+版本号遵循 [语义化版本](https://semver.org/lang/zh-CN/)。
+
+## [Unreleased]
+
+### Added
+- 混合检索（BM25 + 向量联合），HybridRetriever + SearchConfig 可配置
+- 增量入库（SHA256 文件变更追踪），CLI `--incremental` / `--force` 选项
+- Cross-Encoder 结果重排序（BAAI/bge-reranker-base）
+- Web 管理界面（Vue 3 SPA，`/admin`）
+- .docx 文档支持（markitdown）
+- 数据导出功能（JSON/CSV），CLI `export` 命令
+- Docker 部署方案 + docker-compose（含 GPU profile）
+- API 审计日志、请求体大小限制、健康检查免限速
+- GitHub Actions CI 流水线 + PyPI 发布
+- Pre-commit 钩子配置（ruff + mypy）
+- 性能基准测试（嵌入 + 检索）
+
+### Changed
+- Searcher 支持 hybrid/vector 检索模式切换
+- Embedder Protocol 修复为标准写法
+- PDF/EPUB Splitter 参数名统一为 `source`
+
+### Fixed
+- CORS `allow_credentials` 配置修复
+- chromadb 不同版本异常类型兼容（NotFoundError）
+
+## [0.1.0] - 2026-07-05
+
+### Added
+- Markdown 文档解析与语义检索
+- 多 Provider 嵌入支持（local/OpenAI/DashScope）
+- 多格式文档（.md/.txt/.pdf/.html/.epub）
+- GPU 自动检测加速
+- FastAPI HTTP API + Typer CLI
+- API Key 认证和速率限制
+- 路径遍历安全防护

CONTRIBUTING.md

@@ -0,0 +1,54 @@
+# 贡献指南
+
+## 开发环境
+
+```bash
+git clone git@github.com:LHY0125/md-vector-db.git
+cd md-vector-db
+uv sync --extra dev --extra all
+uv run pre-commit install
+```
+
+## 开发流程
+
+1. **Fork 仓库** → 创建功能分支 `feat/xxx`
+2. **写测试**（TDD）: 先在 `tests/` 下写失败测试
+3. **实现功能**: 最少代码让测试通过
+4. **运行全部测试**: `uv run pytest tests/ --cov=src -v`
+5. **确保覆盖率 ≥ 80%**: `uv run pytest tests/ --cov=src --cov-fail-under=80`
+6. **Lint 检查**: `uv run ruff check src/ tests/`
+7. **类型检查**: `uv run mypy src/ --ignore-missing-imports`
+8. **提交**: 遵循约定式提交格式
+9. **创建 PR**: 描述清楚变更内容和测试结果
+
+## 提交消息格式
+
+```
+<类型>: <描述>
+
+<可选正文>
+```
+
+类型: `feat`, `fix`, `refactor`, `docs`, `test`, `chore`, `perf`, `ci`
+
+## 代码风格
+
+- Python 3.13+，遵循 PEP 8
+- 类型注解覆盖所有 public API
+- 中文注释
+- 小文件原则（<800 行），函数 <50 行
+
+## 添加新文档格式支持
+
+1. 在 `src/core/splitters/` 下实现 Splitter Protocol
+2. 在 `src/core/splitters/registry.py` 注册扩展名
+3. 在 `pyproject.toml` 添加可选依赖
+4. 在 `tests/` 下添加测试
+5. 更新 `README.md`
+
+## 运行基准测试
+
+```bash
+uv sync --extra bench
+uv run pytest tests/benchmarks/ -v --benchmark-only
+```

README.md

@@ -1,5 +1,8 @@
 # md-vector-db
 
+[![CI](https://lhy-git.liuhangyv.top/Serendipity/md-vector-db/actions/workflows/ci.yml/badge.svg)](https://github.com/LHY0125/md-vector-db/actions/workflows/ci.yml)
+[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
+
 Markdown 文档向量数据库 — 将 Markdown 文件自动分块、嵌入、存入 ChromaDB，通过语义检索快速查找相关内容。提供 **CLI 命令行工具**和 **HTTP API** 两种使用方式供其他项目集成。
 
 ## 功能特性
@@ -180,14 +183,14 @@ docker exec -it md-vector-db uv run md-vector-db ingest /app/md_docs/doc.md
 
 所有命令均支持 `--config/-c`（配置文件）、`--collection/-C`（集合名，默认 `default`）。
 
-| 命令                              | 说明                                                     |
-| --------------------------------- | -------------------------------------------------------- |
+| 命令                                | 说明                                                     |
+| ----------------------------------- | -------------------------------------------------------- |
 | `ingest <文件路径> --incremental` | 增量入库单文件，自动跳过未变更文件                       |
 | `ingest <文件路径> --force`       | 强制重新入库（忽略增量检查）                             |
 | `ingest-dir <目录路径>`           | 递归入库目录下所有支持的文档格式                         |
-| `search <查询> -k <数量> --mode`  | 语义检索，`--mode hybrid\|vector`，`--json` JSON 输出  |
+| `search <查询> -k <数量> --mode`  | 语义检索，`--mode hybrid\|vector`，`--json` JSON 输出 |
 | `stats`                           | 显示 chunks 总数、源文件列表                             |
-| `export -o <文件> -f <json\|csv>` | 导出 collection 数据                                    |
+| `export -o <文件> -f <json\|csv>`  | 导出 collection 数据                                     |
 | `serve -p <端口>`                 | 启动 HTTP 服务（默认 8000）                              |
 
 ---
@@ -327,6 +330,16 @@ index-strategy = "unsafe-best-match"              # 允许跨源查找
 
 ---
 
+---
+
+## 文档
+
+- [API 参考](docs/api_reference.md)
+- [架构决策记录](docs/architecture.md)
+- 
+- [贡献指南](CONTRIBUTING.md)
+- [变更日志](CHANGELOG.md)
+
 ## License
 
 MIT

docs/api_reference.md

@@ -0,0 +1,68 @@
+# md-vector-db API 参考文档
+
+## REST API
+
+- **Base URL**: `http://localhost:8000/api/v1`
+- **认证**: `X-API-Key` Header（取决于 `MD_VECTOR_API_KEY` 环境变量）
+- **速率限制**: 60s 窗口内最多 30 请求
+
+### GET /health — 健康检查
+
+无需认证。
+
+```json
+{
+  "status": "ok",
+  "checks": {
+    "chromadb": {"status": "ok", "count": 1240},
+    "embedder": {"status": "ok", "dimension": 512}
+  }
+}
+```
+
+### GET /collections — 列出集合
+
+需 API Key。返回 `{"collections": [{"name": "...", "count": N}, ...]}`。
+
+### POST /search — 语义检索
+
+| 字段 | 类型 | 必填 | 约束 |
+|------|------|------|------|
+| query | string | ✅ | 1-2000 字符 |
+| top_k | int | ❌ | 1-100，默认 10 |
+| collection | string | ❌ | ≤128 字符 |
+
+返回 `{"results": [...], "collection": "..."}`，每条结果含 `id`, `content`, `source_file`, `section_title`, `heading_level`, `score`。
+
+### POST /ingest — 入库文档
+
+| 字段 | 类型 | 必填 | 约束 |
+|------|------|------|------|
+| file_path | string | 二选一 | 安全路径 |
+| content | string | 二选一 | ≤500KB |
+| file_name | string | 推荐 | 1-255 字符 |
+| collection | string | ❌ | ≤128 字符 |
+
+返回 `{"status": "ok", "chunks": N, "file": "...", "collection": "..."}`。
+
+### DELETE /documents/{file_name} — 删除文档
+
+查询参数: `collection` (可选)。
+
+| 状态码 | 含义 |
+|--------|------|
+| 200 | 删除成功 |
+| 400 | file_name 不合法 |
+| 401 | API Key 无效 |
+| 404 | 文档不存在 |
+
+## CLI 命令
+
+```bash
+md-vector-db ingest <文件> --incremental --force
+md-vector-db ingest-dir <目录> -C <集合>
+md-vector-db search "<查询>" -k 10 --mode hybrid --json
+md-vector-db stats -C <集合>
+md-vector-db export -o output.json -f json
+md-vector-db serve -p 8000
+```

docs/architecture.md

@@ -0,0 +1,43 @@
+# 架构决策记录 (ADR)
+
+## ADR-1: 为什么选择 ChromaDB？
+
+**日期**: 2026-07-05 | **状态**: 已采纳
+
+**背景**: 需要一个嵌入式向量数据库来持久化文档嵌入。
+
+**候选**: ChromaDB（嵌入式 SQLite）、Qdrant（独立服务）、FAISS（纯内存）、Milvus（生产级集群）
+
+**决策**: ChromaDB。零运维成本远超吞吐量考量。内置 Collection 概念映射多知识库场景。
+
+**代价**: 高并发下逊于 Qdrant/Milvus。未来可透明迁移（Embedder/Searcher 已隔离 ChromaDB 依赖）。
+
+---
+
+## ADR-2: 为什么默认 bge-small-zh-v1.5？
+
+**日期**: 2026-07-05 | **状态**: 已采纳
+
+**候选**: bge-small-zh-v1.5 (512维/23M)、bge-large-zh-v1.5 (1024维/324M)、text2vec-large-chinese、m3e-base
+
+**决策**: bge-small-zh-v1.5。RTX 4060 上 729 chunks 嵌入仅 1.8s，日常精度足够。高精度场景可切换 large 模型或 OpenAI API。
+
+---
+
+## ADR-3: 为什么采用 Protocol 而非 ABC？
+
+**日期**: 2026-07-05 | **状态**: 已采纳
+
+**候选**: typing.Protocol（结构化子类型）、abc.ABC（名义子类型）、Callable（丢失类型信息）
+
+**决策**: Protocol。外部模块无需依赖本项目源码即可实现 Splitter/Embedder，对插件化友好。
+
+---
+
+## ADR-4: 为什么使用 rank-bm25 而非集成搜索引擎？
+
+**日期**: 2026-07-11 | **状态**: 已采纳
+
+**候选**: rank-bm25（纯 Python BM25）、Elasticsearch（外部服务）、Whoosh（纯 Python 全文搜索）
+
+**决策**: rank-bm25。零运维、轻量、与现有 ChromaDB 架构匹配。在向量候选上做 BM25 重打分（而非全文索引所有文档），兼顾性能和精度。

pyproject.toml

@@ -1,7 +1,21 @@
 [project]
 name = "md-vector-db"
 version = "0.1.0"
-description = "Markdown 文档向量数据库，支持语义检索"
+description = "Markdown 文档向量数据库 — 语义检索、混合检索、REST API"
+readme = "README.md"
+license = {text = "MIT"}
+authors = [
+    {name = "刘航宇", email = "3364451258@qq.com"},
+]
+keywords = ["vector-database", "semantic-search", "rag", "chromadb", "markdown"]
+classifiers = [
+    "Development Status :: 4 - Beta",
+    "Intended Audience :: Developers",
+    "License :: OSI Approved :: MIT License",
+    "Programming Language :: Python :: 3.13",
+    "Topic :: Scientific/Engineering :: Artificial Intelligence",
+    "Topic :: Text Processing :: Markup",
+]
 requires-python = ">=3.13"
 dependencies = [
     "chromadb>=0.5.0",
@@ -15,6 +29,12 @@ dependencies = [
     "rank-bm25>=0.2.2",
 ]
 
+[project.urls]
+Homepage = "https://github.com/LHY0125/md-vector-db"
+Documentation = "https://github.com/LHY0125/md-vector-db#readme"
+Repository = "https://github.com/LHY0125/md-vector-db"
+Issues = "https://github.com/LHY0125/md-vector-db/issues"
+
 [project.scripts]
 md-vector-db = "src.cli.main:app"
 
@@ -24,6 +44,7 @@ pdf = ["pymupdf>=1.24.0"]
 html = ["beautifulsoup4>=4.12.0"]
 epub = ["ebooklib>=0.18"]
 docx = ["markitdown>=0.1.0"]
+bench = ["pytest-benchmark>=5.0"]
 all = ["md-vector-db[pdf,html,epub,docx]", "requests>=2.31.0", "openai>=1.0.0"]
 
 [build-system]
@@ -56,3 +77,4 @@ ignore_missing_imports = true
 [tool.pytest.ini_options]
 testpaths = ["tests"]
 pythonpath = ["src"]
+norecursedirs = ["tests/benchmarks"]

scripts/bump_version.py

@@ -0,0 +1,47 @@
+"""版本号管理 — 更新 pyproject.toml 中的 version."""
+import re
+import sys
+from pathlib import Path
+
+
+def bump(part: str) -> str:
+    """递增版本号.
+
+    Args:
+        part: "major" | "minor" | "patch"
+
+    Returns:
+        新版本号字符串
+    """
+    pyproject = Path(__file__).parent.parent / "pyproject.toml"
+    content = pyproject.read_text(encoding="utf-8")
+    match = re.search(r'version\s*=\s*"(\d+)\.(\d+)\.(\d+)"', content)
+    if not match:
+        print("错误: 未找到 version 字段", file=sys.stderr)
+        sys.exit(1)
+    major, minor, patch = int(match[1]), int(match[2]), int(match[3])
+    if part == "major":
+        major += 1
+        minor = 0
+        patch = 0
+    elif part == "minor":
+        minor += 1
+        patch = 0
+    elif part == "patch":
+        patch += 1
+    else:
+        print(f"错误: 未知的版本部分 '{part}'，可选: major/minor/patch", file=sys.stderr)
+        sys.exit(1)
+
+    new_version = f"{major}.{minor}.{patch}"
+    new_content = content.replace(match[0], f'version = "{new_version}"')
+    pyproject.write_text(new_content, encoding="utf-8")
+    print(f"版本: {match[1]}.{match[2]}.{match[3]} → {new_version}")
+    return new_version
+
+
+if __name__ == "__main__":
+    if len(sys.argv) != 2:
+        print("用法: python scripts/bump_version.py <major|minor|patch>")
+        sys.exit(1)
+    bump(sys.argv[1])

tests/benchmarks/conftest.py

@@ -0,0 +1,41 @@
+"""基准测试共享 fixture."""
+import pytest
+
+from src.core.config import ChunkConfig, EmbedConfig
+from src.core.db import VectorDB
+from src.core.embedder import create_embedder
+from src.core.ingest import DocumentIngestor
+from src.core.search import Searcher
+
+
+@pytest.fixture(scope="module")
+def benchmark_db(tmp_path_factory):
+    """模块级共享 ChromaDB 实例."""
+    persist_dir = tmp_path_factory.mktemp("bench_data")
+    return VectorDB(persist_dir=str(persist_dir))
+
+
+@pytest.fixture(scope="module")
+def benchmark_embedder():
+    """模块级共享 LocalEmbedder."""
+    config = EmbedConfig(mode="local", local_model="BAAI/bge-small-zh-v1.5")
+    return create_embedder(config)
+
+
+@pytest.fixture(scope="module")
+def benchmark_searcher(benchmark_db, benchmark_embedder):
+    """预填充数据的 Searcher."""
+    ingestor = DocumentIngestor(
+        benchmark_db, benchmark_embedder, "bench_collection",
+        chunk_config=ChunkConfig(max_size=1000, overlap=100),
+    )
+    for i in range(100):
+        content = (
+            f"# 文档{i}\n\n"
+            + "\n\n".join(
+                f"第{j}段用于基准测试。关键词: Python, Rust, GPU, 向量数据库。"
+                for j in range(5)
+            )
+        )
+        ingestor.ingest_content(content, f"bench_{i}.md")
+    return Searcher(benchmark_db, benchmark_embedder, "bench_collection")

tests/benchmarks/test_bench_embed.py

@@ -0,0 +1,23 @@
+"""嵌入性能基准测试."""
+import pytest
+
+
+def test_bench_embed_single(benchmark, benchmark_embedder):
+    """单文本嵌入耗时."""
+    text = "这是一段测试文本，用于测量嵌入速度。"
+    benchmark(benchmark_embedder.embed, [text])
+
+
+def test_bench_embed_batch_32(benchmark, benchmark_embedder):
+    """批量 32 文本嵌入耗时."""
+    texts = [f"测试文本第{i}条，模拟真实文档内容。" for i in range(32)]
+    benchmark(benchmark_embedder.embed, texts)
+
+
+def test_bench_embed_batch_100(benchmark, benchmark_embedder):
+    """批量 100 文本嵌入耗时（GPU 优势显著）."""
+    texts = [
+        f"测试文本第{i}条。Python 通用编程语言，用于数据科学和 AI。"
+        for i in range(100)
+    ]
+    benchmark(benchmark_embedder.embed, texts)

tests/benchmarks/test_bench_search.py

@@ -0,0 +1,17 @@
+"""检索性能基准测试."""
+import pytest
+
+
+def test_bench_search_top5(benchmark, benchmark_searcher):
+    """top_k=5 检索耗时."""
+    benchmark(benchmark_searcher.search, "Python 向量数据库", top_k=5)
+
+
+def test_bench_search_top20(benchmark, benchmark_searcher):
+    """top_k=20 检索耗时."""
+    benchmark(benchmark_searcher.search, "Rust 编程语言 GPU", top_k=20)
+
+
+def test_bench_search_cold_start(benchmark, benchmark_searcher):
+    """冷启动检索耗时."""
+    benchmark(benchmark_searcher.search, "GPU 加速 深度学习 嵌入", top_k=10)

uv.lock

@@ -1206,6 +1206,9 @@ all = [
     { name = "pymupdf" },
     { name = "requests" },
 ]
+bench = [
+    { name = "pytest-benchmark" },
+]
 dev = [
     { name = "httpx" },
     { name = "mypy" },
@@ -1240,6 +1243,7 @@ requires-dist = [
     { name = "openai", marker = "extra == 'all'", specifier = ">=1.0.0" },
     { name = "pymupdf", marker = "extra == 'pdf'", specifier = ">=1.24.0" },
     { name = "pytest", marker = "extra == 'dev'", specifier = ">=8.0" },
+    { name = "pytest-benchmark", marker = "extra == 'bench'", specifier = ">=5.0" },
     { name = "pytest-cov", marker = "extra == 'dev'", specifier = ">=5.0" },
     { name = "python-dotenv", specifier = ">=1.2.2" },
     { name = "pyyaml", specifier = ">=6.0" },
@@ -1250,7 +1254,7 @@ requires-dist = [
     { name = "typer", specifier = ">=0.12.0" },
     { name = "uvicorn", extras = ["standard"], specifier = ">=0.30.0" },
 ]
-provides-extras = ["dev", "pdf", "html", "epub", "docx", "all"]
+provides-extras = ["dev", "pdf", "html", "epub", "docx", "bench", "all"]
 
 [[package]]
 name = "mdurl"
@@ -1559,7 +1563,7 @@ name = "nvidia-cudnn-cu12"
 version = "9.1.0.70"
 source = { registry = "https://pypi.tuna.tsinghua.edu.cn/simple/" }
 dependencies = [
-    { name = "nvidia-cublas-cu12", marker = "python_full_version >= '3.14' or sys_platform == 'darwin' or sys_platform == 'linux'" },
+    { name = "nvidia-cublas-cu12", marker = "(python_full_version >= '3.14' and sys_platform != 'win32') or sys_platform == 'darwin' or sys_platform == 'linux'" },
 ]
 wheels = [
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@@ -1570,7 +1574,7 @@ name = "nvidia-cufft-cu12"
 version = "11.2.1.3"
 source = { registry = "https://pypi.tuna.tsinghua.edu.cn/simple/" }
 dependencies = [
-    { name = "nvidia-nvjitlink-cu12", marker = "python_full_version >= '3.14' or sys_platform == 'darwin' or sys_platform == 'linux'" },
+    { name = "nvidia-nvjitlink-cu12", marker = "(python_full_version >= '3.14' and sys_platform != 'win32') or sys_platform == 'darwin' or sys_platform == 'linux'" },
 ]
 wheels = [
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@@ -1589,9 +1593,9 @@ name = "nvidia-cusolver-cu12"
 version = "11.6.1.9"
 source = { registry = "https://pypi.tuna.tsinghua.edu.cn/simple/" }
 dependencies = [
-    { name = "nvidia-cublas-cu12", marker = "python_full_version >= '3.14' or sys_platform == 'darwin' or sys_platform == 'linux'" },
-    { name = "nvidia-cusparse-cu12", marker = "python_full_version >= '3.14' or sys_platform == 'darwin' or sys_platform == 'linux'" },
-    { name = "nvidia-nvjitlink-cu12", marker = "python_full_version >= '3.14' or sys_platform == 'darwin' or sys_platform == 'linux'" },
+    { name = "nvidia-cublas-cu12", marker = "(python_full_version >= '3.14' and sys_platform != 'win32') or sys_platform == 'darwin' or sys_platform == 'linux'" },
+    { name = "nvidia-cusparse-cu12", marker = "(python_full_version >= '3.14' and sys_platform != 'win32') or sys_platform == 'darwin' or sys_platform == 'linux'" },
+    { name = "nvidia-nvjitlink-cu12", marker = "(python_full_version >= '3.14' and sys_platform != 'win32') or sys_platform == 'darwin' or sys_platform == 'linux'" },
 ]
 wheels = [
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@@ -1602,7 +1606,7 @@ name = "nvidia-cusparse-cu12"
 version = "12.3.1.170"
 source = { registry = "https://pypi.tuna.tsinghua.edu.cn/simple/" }
 dependencies = [
-    { name = "nvidia-nvjitlink-cu12", marker = "python_full_version >= '3.14' or sys_platform == 'darwin' or sys_platform == 'linux'" },
+    { name = "nvidia-nvjitlink-cu12", marker = "(python_full_version >= '3.14' and sys_platform != 'win32') or sys_platform == 'darwin' or sys_platform == 'linux'" },
 ]
 wheels = [
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@@ -1942,6 +1946,15 @@ wheels = [
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 ]
 
+[[package]]
+name = "py-cpuinfo"
+version = "9.0.0"
+source = { registry = "https://pypi.tuna.tsinghua.edu.cn/simple/" }
+sdist = { url = "https://pypi.tuna.tsinghua.edu.cn/packages/37/a8/d832f7293ebb21690860d2e01d8115e5ff6f2ae8bbdc953f0eb0fa4bd2c7/py-cpuinfo-9.0.0.tar.gz", hash = "sha256:3cdbbf3fac90dc6f118bfd64384f309edeadd902d7c8fb17f02ffa1fc3f49690", size = 104716, upload-time = "2022-10-25T20:38:06.303Z" }
+wheels = [
+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/e0/a9/023730ba63db1e494a271cb018dcd361bd2c917ba7004c3e49d5daf795a2/py_cpuinfo-9.0.0-py3-none-any.whl", hash = "sha256:859625bc251f64e21f077d099d4162689c762b5d6a4c3c97553d56241c9674d5", size = 22335, upload-time = "2022-10-25T20:38:27.636Z" },
+]
+
 [[package]]
 name = "pybase64"
 version = "1.4.3"
@@ -2181,6 +2194,19 @@ wheels = [
     { url = "https://pypi.tuna.tsinghua.edu.cn/packages/24/25/1de2678b631f5a49215c6c96fff41ba892b0a34df68d6d80292b1b48aa7f/pytest-9.1.1-py3-none-any.whl", hash = "sha256:37a86b45efb9a47a61a36449063e8e18d0cab3161329fc099eb21783169c4f0c", size = 386536, upload-time = "2026-06-19T10:58:31.347Z" },
 ]
 
+[[package]]
+name = "pytest-benchmark"
+version = "5.2.3"
+source = { registry = "https://pypi.tuna.tsinghua.edu.cn/simple/" }
+dependencies = [
+    { name = "py-cpuinfo" },
+    { name = "pytest" },
+]
+sdist = { url = "https://pypi.tuna.tsinghua.edu.cn/packages/24/34/9f732b76456d64faffbef6232f1f9dbec7a7c4999ff46282fa418bd1af66/pytest_benchmark-5.2.3.tar.gz", hash = "sha256:deb7317998a23c650fd4ff76e1230066a76cb45dcece0aca5607143c619e7779", size = 341340, upload-time = "2025-11-09T18:48:43.215Z" }
+wheels = [
+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/33/29/e756e715a48959f1c0045342088d7ca9762a2f509b945f362a316e9412b7/pytest_benchmark-5.2.3-py3-none-any.whl", hash = "sha256:bc839726ad20e99aaa0d11a127445457b4219bdb9e80a1afc4b51da7f96b0803", size = 45255, upload-time = "2025-11-09T18:48:39.765Z" },
+]
+
 [[package]]
 name = "pytest-cov"
 version = "7.1.0"