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中国校招、实习、社招岗位与招聘日历,下载一次,在本地查。
把分散的公开招聘信息整理成可追溯的 SQLite 数据集。按公司、城市、届次筛选,搜索职位描述,查看招聘时间与原始投递入口。提供 CLI 和 MCP,查询无需 API key,也无需部署服务器。
快速开始 · 查询示例 · 数据与覆盖 · 使用文档 · 参与贡献
看它如何工作
演示取自 2026-10-29 / 30 数据快照,保留来源原文,展示结果节选。动画节奏不代表查询耗时;岗位与日期请以最新数据及原始招聘页为准。
为什么用 job_radar
| 你想做的事 | 项目提供的能力 |
|---|---|
| 找到适合自己的岗位 | 按公司、城市、职类、校招 / 实习 / 社招、毕业年份组合筛选 |
| 阅读真正的岗位要求 | 搜索标题与 JD 原文,保留原始招聘链接 |
| 跟上招聘节奏 | 招聘日历、网申窗口,以及开岗 / 变更 / 下架历史 |
| 接入自己的工作流 | CLI 默认输出 JSON,支持表格;MCP 共用同一查询层 |
| 掌握自己的数据 | SQLite 本地查询,可离线分析;代码与数据分开发版 |
| 判断信息是否可靠 | 官方与聚合来源分开标注,缺失字段留空,统计可复算 |
快速开始
需要 Python 3.11+,支持 Windows、macOS 和 Linux。
pip install jobsearchradar
jobradar update
jobradar search --company 复星医药 --type campus --grad-year 2027 --table
包名是 jobsearchradar,安装后的命令是 jobradar。首次更新下载岗位库和正文库;后续更新会检查版本,已是最新时跳过下载。
国内网络可以使用镜像:
jobradar update --mirror gitee
数据默认位于 ~/.cache/jobradar;通过 JOBRADAR_HOME 指定其他目录。下载、镜像与排错见 FAQ。
查询示例
按条件找岗位
# 公司 + 招聘类型 + 届次
jobradar search --company 复星医药 --type campus --grad-year 2027 --limit 3 --table
# 搜索标题与 JD 正文,多个词共同匹配
jobradar search --text "PyTorch 大模型" --type campus --limit 3 --table
# 城市、职类与去重
jobradar search --city 上海 --category 算法 --type intern --dedupe --table
查看日历与最近变化
jobradar calendar --group 阿里巴巴 --grad-year 2027 --table
jobradar diff --days 7 --types open --table
jobradar diff --days 7 --by category --company 腾讯
jobradar trends 美团 --step-days 7
省略 --table 即输出 JSON,便于脚本处理。用 jobradar show <job_id> 查看单岗详情与 JD;用 jobradar doctor 检查本地数据状态。更多参数见 jobradar --help 与 字段说明。
接入 MCP
pip install "jobsearchradar[mcp]"
jobradar update
在支持 MCP 的客户端中添加 stdio 服务:
{
"mcpServers": {
"jobradar": {
"command": "jobradar-mcp"
}
}
}
提供搜索、单岗详情、近期变化、职类新增、公司对比、趋势、数据状态、招聘日历和统计 9 个工具。自定义数据目录时,在该服务的 env 中传入 JOBRADAR_HOME;客户端需能找到安装环境中的 jobradar-mcp。
需要通过 CLI 集成时,可参考 查询工作流。
数据与覆盖
配置统计 · 2026-10-31
| 指标 | 当前值 | 含义 |
|---|---|---|
| 启用数据源 | 2,242 | 启用的源配置 |
| 配置公司 | 2,201 | 启用源对应的去重公司 |
| 采集适配器 | 27 | 共享平台与自研站适配器 |
| 核心目标覆盖 | 931 / 1,655 · 56.25% | 固定目标池中的配置覆盖 |
| 其中官方 / 聚合 | 606 / 325 | 优先按官方归类,不重复计数 |
已核验发布快照 · 2026-10-29T23:17:25Z
共 294,483 条岗位记录,其中 276,008 条在招记录;在招 JD 正文覆盖率 97.3%。招聘日历样本共 4,874 条,含 2,078 条人工整理条目。这是有日期的历史快照,实时规模以本地 jobradar stats 和最新 数据 Release 为准。
配置覆盖不等于当天在招;聚合招聘简章可能对应多个岗位,不能按单个职位理解。日期缺失保留为空,学校公告展示截止日与企业网申截止日分别处理。更多口径、可复算命令与已知限制见 覆盖说明。
数据文件与更新机制
| 文件 | 内容 |
|---|---|
jobs.db |
结构化岗位、状态与变更事件 |
jd_text.db |
岗位职责与任职要求原文 |
calendar.db |
招聘项目、届次、方向、窗口与来源 |
GitHub Actions 定时采集并发布 data-latest,CLI 下载快照后在本地查询。失败抓取不会直接导致岗位下架。数据规模、源可用性和字段完整性随发布变化,使用时应核对 data_as_of 和原始链接。
主分支新增 FTS5 trigram 索引,长关键词保持字面子串语义,短词回退 LIKE。首次打开新版数据库会构建索引;约 29 万条岗位的本机样本约需 1 分钟,额外占用约 199 MB。公开数据库保留兼容格式,索引由新版客户端本地建立。详见 发布与兼容性。
项目如何运行
flowchart LR
A["公开招聘来源"] --> B["合规检查 · 27 个适配器"]
B --> C["归一化 · 去重 · 状态事件"]
C --> D["GitHub Release / SQLite 快照"]
E["人工核验的招聘日历"] --> D
D --> F["本地 CLI"]
D --> G["MCP"]
F --> H["筛选 · 检索 · 分析"]
G --> H
采集运行在 GitHub Actions,查询运行在你的电脑上。核心查询集中在一处,CLI 与 MCP 共享相同筛选规则。
一起把它做好
欢迎补充公开招聘源、修正公司归属与招聘日期、改进适配器、提交可复现的问题,或完善翻译。
git clone https://github.com/lijiaqi-AI-Product-Manager/job_radar.git
cd job_radar
uv sync --frozen --all-extras
uv run pytest
uv run ruff check .
从 贡献指南、开发规范 和 路线图 开始。问题反馈请附命令、数据时间与原始来源链接,帮助维护者快速定位。
如果它帮你少翻了几个招聘网站,欢迎 Star,也欢迎分享给正在找工作的朋友。
文档与许可
文档索引 · 常见问题 · 覆盖说明 · 更新日志 · 合规声明
代码采用 MIT License。招聘文本与来源站点内容的权利归原权利人;代码许可不构成对第三方内容的额外授权。项目只访问允许公开读取的内容,不绕过登录、验证码或访问限制。详见 数据使用说明。
Metadata
Release files for jobsearchradar 2.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Change of provenance
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We recommend inspecting the repository and configuration before proceeding. View details.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| jobsearchradar-2.0.0.tar.gz | 3.4 MB | With provenance | Details for jobsearchradar-2.0.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| jobsearchradar-2.0.0-py3-none-any.whl | Python 3 | none | any | Details for jobsearchradar-2.0.0-py3-none-any.whl |
Total release size: 3.6 MB
Release files / jobsearchradar-2.0.0.tar.gz
Change of provenance
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| Download URL | jobsearchradar-2.0.0.tar.gz |
|---|---|
| Size | 3.4 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
3f428118c38becacb8ee54231808181c31b9ffec8ffeffedab69df739d1387f6
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| Download URL | jobsearchradar-2.0.0-py3-none-any.whl |
|---|---|
| Size | 233.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
9712a4e6a6aadc58bbbaa9bc3427b8199aef19f6e478bdf80cde4c615e814c18
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.16
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Nov 1, 2026.
Transparency logSecurity for jobsearchradar 2.0.0
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While this could reflect a routine change by the project maintainers, it may also indicate that the release files have been compromised.
Repository
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PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Nov 1, 2026.
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