a7242f0c69
- 包含4个产业方向的前端项目：智能开发、智能制造、大健康、财经商贸 - 已清理node_modules、.yoyo等大文件，项目大小从2.6GB优化至631MB - 配置完善的.gitignore文件 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
85 lines
3.2 KiB
JavaScript
85 lines
3.2 KiB
JavaScript
const fs = require('fs');
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// 读取数据
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const companyJobsNewData = JSON.parse(fs.readFileSync('./src/data/companyJobsNew.json', 'utf8'));
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const companyImagesData = JSON.parse(fs.readFileSync('./网页未导入数据/智能制造产业/智能制造_内推岗位企业图片.json', 'utf8'));
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const interviewStatusData = JSON.parse(fs.readFileSync('./src/data/interviewStatus.json', 'utf8'));
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console.log("=== 数据转换测试 ===\n");
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// 创建图片映射（复制mockData.js中的逻辑）
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const companyImagesMap = {};
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companyImagesData.forEach(item => {
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const positionName = item["内推岗位名称"];
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const imageLinks = item["BOSS照片链接"];
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if (positionName && imageLinks) {
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companyImagesMap[positionName] = imageLinks.split(',').map(url => url.trim());
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}
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});
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console.log("图片映射创建完成，共", Object.keys(companyImagesMap).length, "个岗位\n");
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// 获取面试状态中的岗位
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const interviewedPositions = interviewStatusData.map(status => status["查询岗位名称"]);
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console.log("面试状态岗位数:", interviewedPositions.length);
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console.log("面试状态岗位:", interviewedPositions.join(", "));
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// 模拟transformCompanyJobs函数
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const today = new Date();
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today.setHours(0, 0, 0, 0);
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const transformedJobs = companyJobsNewData
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.filter(job => !interviewedPositions.includes(job["内推岗位名称"]))
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.map((job, index) => {
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const positionName = job["内推岗位名称"];
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const companyImages = companyImagesMap[positionName] || [];
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return {
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id: index + 1,
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position: positionName,
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hasImages: companyImages.length > 0,
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imageCount: companyImages.length,
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details: {
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companyImages: companyImages
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}
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};
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});
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console.log("\n=== 转换后的岗位数据 ===");
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console.log("过滤后岗位总数:", transformedJobs.length);
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console.log("有图片的岗位数:", transformedJobs.filter(j => j.hasImages).length);
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console.log("\n=== 前10个转换后的岗位 ===");
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transformedJobs.slice(0, 10).forEach((job, idx) => {
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const mark = job.hasImages ? "✅" : "❌";
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console.log(mark, (idx+1) + ".", job.position,
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job.hasImages ? `(${job.imageCount}张)` : "(无图片)");
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});
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console.log("\n=== 有图片的岗位详细信息 ===");
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const jobsWithImages = transformedJobs.filter(j => j.hasImages);
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jobsWithImages.forEach((job, idx) => {
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console.log(`${idx+1}. ${job.position}: ${job.imageCount}张图片`);
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if (job.details.companyImages.length > 0) {
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console.log(` 第一张: ${job.details.companyImages[0].substring(0, 80)}...`);
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}
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});
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console.log("\n=== 被过滤掉的面试状态岗位中有图片的 ===");
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const filteredJobsWithImages = companyJobsNewData
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.filter(job => interviewedPositions.includes(job["内推岗位名称"]))
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.filter(job => companyImagesMap[job["内推岗位名称"]])
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.map(job => ({
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position: job["内推岗位名称"],
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imageCount: companyImagesMap[job["内推岗位名称"]].length
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}));
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if (filteredJobsWithImages.length > 0) {
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console.log("注意：以下岗位有图片但因为在面试状态中被过滤：");
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filteredJobsWithImages.forEach((job, idx) => {
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console.log(` ${idx+1}. ${job.position} (${job.imageCount}张图片)`);
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});
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} else {
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console.log("无");
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}
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