Performance is mediocre according to Google Lighthouse analysis

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还没有人认领这个 Issue。

评估

难度
5/5
预计耗时
一周以上
新手友好度
18/100
Issue 类型
缺陷
描述清晰度
需要澄清
活跃度
冷清

调研方向

The issue names no source files or tests; the only concrete starting point is the attached Lighthouse HTML report, which lists the unused JavaScript and CSS and the chained critical requests. Run Lighthouse against a local dspace-angular build to reproduce the 70 score and find which bundles or requests dominate. Done would mean a specific, measured Lighthouse improvement, which the maintainers would need to agree on first.

由索引模型根据 Issue 内容生成。

描述

affects: 10.x affects: 9.x affects: main bug code task help wanted performance / caching

Describe the bug

According to a performance analysis run on sandbox.dspace.org via Google Lighthouse, DSpace only scores 70 out of 100 points. This behavior can also be reproduced on demo.dspace.org and our own institutional DSpace instance. Therefore the performance was already mediocre in DSpace 9 and the reason for the poor performance is not the underlying sandbox server.

Google Lighthouse has several tips on how to resolve this, e.g. reducing unused JavaScript and CSS and avoid chaining critical requests. Please see the attached Lighthouse document for more information and tips.

I am not sure how easy it is to tackle this, nevertheless we wanted to run some performance analysis test during testathon, that's where this bug ticket comes from.

To Reproduce

Steps to reproduce the behavior:

  1. Visit sandbox.dspace.org in Chrome or Chromium
  2. Open developer tools and start a Google Lighthouse analysis

Expected behavior

DSpace should perform well in a performance analysis.

Side notes

DSpace performs well in the accessibility part of the Lighthouse test 🎉 Please ignore the SEO part, the poor ranking stems from the applied robots.txt on the sandbox server.

sandbox.dspace.org-20260408T160850.html

主要语言
TypeScript
星标
180
派生
577
平均合并
1 天 23 小时
30 天内合并 PR
95

环境准备

从这里开始

  1. 先读完整个 Issue,再读项目的贡献指南。
  2. 在 Issue 下留言说明你要接手 —— 这能避免两个人做同样的事。
  3. Fork 仓库,在一个分支上完成修改。
  4. 提交 Pull Request,并在描述里引用这个 Issue 编号。

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