打包体积与代码优化
减少 Worker 的打包体积和 CPU 使用量，让边缘代码加载更快并在限制范围内运行。
打包体积与代码优化 是 CoddyKit 上的免费 Edge Computing with Cloudflare Workers & Deno 课时。 这是第 4 节课，共 4 节。 你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。 这是 Edge Computing with Cloudflare Workers & Deno 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 Edge Computing with Cloudflare Workers & Deno 课程共包含 4 节课。
本课时的部分内容尚未翻译，以英文显示。
Why Bundle Size Matters
Workers have a script size limit (1 MB compressed on the free plan, more on paid).
Smaller bundles mean:
- Faster parse and startup
- Lower memory footprint
- Reduced cold-start impact
Optimizing your code is a direct performance win at the edge.
Measure Before Optimizing
Wrangler reports your bundle size on every build. Always measure first.
wrangler deploy --dry-run
# Total Upload: 142.18 KiB / gzip: 38.94 KiBTree Shaking
Use ES module import/export so the bundler can tree-shake unused code.
Import only what you need, never the whole library when a single function will do.
// Good: only pulls debounce
import debounce from 'lodash-es/debounce';
// Bad: pulls all of lodash
import _ from 'lodash';Prefer Lightweight Dependencies
Heavy npm packages bloat bundles fast. Prefer small, edge-friendly libraries.
- Use the platform
URL,crypto.subtle, andfetchinstead of polyfills - Swap moment.js for a tiny date helper
- Audit with a bundle analyzer
Use Web Standard APIs
Workers and Deno expose many Web Platform APIs natively, so you avoid bundling polyfills.
// Native crypto, no dependency needed
const hash = await crypto.subtle.digest(
'SHA-256',
new TextEncoder().encode('hello')
);Minification
Wrangler minifies production builds by default, but confirm it is enabled.
[build]
minify = trueReduce CPU Time
Workers bill and limit by CPU time, not wall-clock. Optimize hot paths:
- Avoid synchronous loops over huge arrays
- Cache computed results in KV or memory
- Stream large responses instead of buffering
Stream Instead of Buffer
Streaming sends data as it is produced, keeping memory low and CPU steady.
const { readable, writable } = new TransformStream();
response.body.pipeTo(writable);
return new Response(readable, response);Lazy-Load Rarely Used Code
Dynamic import() can defer loading code paths that are not always needed, keeping the initial module lean.
if (needsHeavyFeature) {
const { process } = await import('./heavy.js');
process();
}Analyze Your Bundle
Use an analyzer to see which dependencies dominate. esbuild (which Wrangler uses) can emit a metafile.
esbuild src/index.ts --bundle --metafile=meta.json
# upload meta.json to esbuild.github.io/analyzeBest Practices Summary
To keep edge code fast and small:
- Measure bundle size on every deploy
- Tree-shake and import narrowly
- Prefer native Web APIs over polyfills
- Minify, stream, and lazy-load
- Cut CPU time in hot paths
Quick Check
Which technique most directly lets the bundler remove unused library code?
Recap
You optimized both size and speed:
- Measure first, then tree-shake and minify
- Use native Web APIs and lightweight deps
- Stream and lazy-load to cut memory and CPU
- Analyze the bundle to find offenders
Lean Workers start faster and cost less, every kilobyte counts at the edge.
常见问题解答
「打包体积与代码优化」课时是免费的吗？
是的 — 「打包体积与代码优化」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 Edge Computing with Cloudflare Workers & Deno 课程的其余内容，请升级到 CoddyKit PRO。 Edge Computing with Cloudflare Workers & Deno 课程共包含 4 节课。
「打包体积与代码优化」这节课中我会学到什么？
减少 Worker 的打包体积和 CPU 使用量，让边缘代码加载更快并在限制范围内运行。 你通过在浏览器中直接运行的动手代码来练习 Edge Computing with Cloudflare Workers & Deno，全天候 AI 导师会在你学习这节课的过程中回答你的问题。
学习 Edge Computing with Cloudflare Workers & Deno 需要有经验吗？
无需任何先前经验。CoddyKit 上的 Edge Computing with Cloudflare Workers & Deno 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。 这是第 4 节课，共 4 节。
「打包体积与代码优化」课时需要多长时间？
大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。
我能在这节 Edge Computing with Cloudflare Workers & Deno 课中编写并运行代码吗？
能。每节 Edge Computing with Cloudflare Workers & Deno 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。