将对象存储桶挂载为本地文件系统路径,以便在沙箱生命周期之间持久保存数据。本教程使用 Cloudflare R2,但同样的方法适用于任何 S3 兼容提供商。
本教程展示如何持久化挂载在 /data 的外部数据目录。如果希望 /workspace 中的工作项目持久化,请参阅备份与恢复。
预计完成时间: 20 分钟
一个 Worker:处理数据,将结果存储在挂载为本地目录的 R2 存储桶中,并演示即使沙箱被销毁并重新创建,数据仍然持久存在。
你将学到的关键概念:
- 将 R2 存储桶挂载为文件系统路径
- 跨沙箱生命周期的自动数据持久化
- 使用标准文件操作处理挂载的存储
- 注册 Cloudflare 账户 ↗。
- 安装
Node.js↗。
Node.js 版本管理器
使用 Volta ↗ 或 nvm ↗ 等 Node 版本管理器,以避免权限问题并切换 Node.js 版本。本指南后续将介绍的 Wrangler 需要 Node 版本 16.17.0 或更高。
你还需要:
- 本地运行的 Docker ↗
- 一个 R2 存储桶(在 Cloudflare 仪表板 ↗ 中创建)
npm create cloudflare@latest -- data-pipeline --template=cloudflare/sandbox-sdk/examples/minimalyarn create cloudflare data-pipeline --template=cloudflare/sandbox-sdk/examples/minimalpnpm create cloudflare@latest data-pipeline --template=cloudflare/sandbox-sdk/examples/minimalcd data-pipeline在 wrangler.json 中添加 R2 存储桶绑定:
{
"name": "data-pipeline",
"compatibility_date": "2025-11-09",
"durable_objects": {
"bindings": [
{ "name": "Sandbox", "class_name": "Sandbox" }
]
},
"r2_buckets": [
{
"binding": "DATA_BUCKET",
"bucket_name": "my-data-bucket"
}
]
}将 my-data-bucket 替换为你的 R2 存储桶名称。请先在 Cloudflare 仪表板 ↗ 中创建该存储桶。
将 src/index.ts 替换为挂载 R2 并处理数据的代码:
import { getSandbox } from "@cloudflare/sandbox";
export { Sandbox } from "@cloudflare/sandbox";
export default {
async fetch(request, env) {
const url = new URL(request.url);
const sandbox = getSandbox(env.Sandbox, "data-processor");
// Mount R2 bucket to /data directory
await sandbox.mountBucket("my-data-bucket", "/data", {
endpoint: "https://YOUR_ACCOUNT_ID.r2.cloudflarestorage.com",
});
if (url.pathname === "/process") {
// Process data and save to mounted R2
const result = await sandbox.exec("python", {
args: [
"-c",
`
import json
import os
from datetime import datetime
# Read input (or create sample data)
data = [
{'id': 1, 'value': 42},
{'id': 2, 'value': 87},
{'id': 3, 'value': 15}
]
# Process: calculate sum and average
total = sum(item['value'] for item in data)
avg = total / len(data)
# Save results to mounted R2 (/data is the mounted bucket)
result = {
'timestamp': datetime.now().isoformat(),
'total': total,
'average': avg,
'processed_count': len(data)
}
os.makedirs('/data/results', exist_ok=True)
with open('/data/results/latest.json', 'w') as f:
json.dump(result, f, indent=2)
print(json.dumps(result))
`,
],
});
return Response.json({
message: "Data processed and saved to R2",
result: JSON.parse(result.stdout),
});
}
if (url.pathname === "/results") {
// Read results from mounted R2
const result = await sandbox.exec("cat", {
args: ["/data/results/latest.json"],
});
if (!result.success) {
return Response.json(
{ error: "No results found yet" },
{ status: 404 },
);
}
return Response.json({
message: "Results retrieved from R2",
data: JSON.parse(result.stdout),
});
}
if (url.pathname === "/destroy") {
// Destroy sandbox to demonstrate persistence
await sandbox.destroy();
return Response.json({
message: "Sandbox destroyed. Data persists in R2!",
});
}
return new Response(
`
Data Pipeline with Persistent Storage
Endpoints:
- POST /process - Process data and save to R2
- GET /results - Retrieve results from R2
- POST /destroy - Destroy sandbox (data survives!)
Try this flow:
1. POST /process (processes and saves to R2)
2. POST /destroy (destroys sandbox)
3. GET /results (data still accessible from R2)
`,
{ headers: { "Content-Type": "text/plain" } },
);
},
};import { getSandbox, type Sandbox } from '@cloudflare/sandbox';
export { Sandbox } from '@cloudflare/sandbox';
interface Env {
Sandbox: DurableObjectNamespace<Sandbox>;
DATA_BUCKET: R2Bucket;
}
export default {
async fetch(request: Request, env: Env): Promise<Response> {
const url = new URL(request.url);
const sandbox = getSandbox(env.Sandbox, 'data-processor');
// Mount R2 bucket to /data directory
await sandbox.mountBucket('my-data-bucket', '/data', {
endpoint: 'https://YOUR_ACCOUNT_ID.r2.cloudflarestorage.com'
});
if (url.pathname === '/process') {
// Process data and save to mounted R2
const result = await sandbox.exec('python', {
args: ['-c', `
import json
import os
from datetime import datetime
# Read input (or create sample data)
data = [
{'id': 1, 'value': 42},
{'id': 2, 'value': 87},
{'id': 3, 'value': 15}
]
# Process: calculate sum and average
total = sum(item['value'] for item in data)
avg = total / len(data)
# Save results to mounted R2 (/data is the mounted bucket)
result = {
'timestamp': datetime.now().isoformat(),
'total': total,
'average': avg,
'processed_count': len(data)
}
os.makedirs('/data/results', exist_ok=True)
with open('/data/results/latest.json', 'w') as f:
json.dump(result, f, indent=2)
print(json.dumps(result))
`]
});
return Response.json({
message: 'Data processed and saved to R2',
result: JSON.parse(result.stdout)
});
}
if (url.pathname === '/results') {
// Read results from mounted R2
const result = await sandbox.exec('cat', {
args: ['/data/results/latest.json']
});
if (!result.success) {
return Response.json({ error: 'No results found yet' }, { status: 404 });
}
return Response.json({
message: 'Results retrieved from R2',
data: JSON.parse(result.stdout)
});
}
if (url.pathname === '/destroy') {
// Destroy sandbox to demonstrate persistence
await sandbox.destroy();
return Response.json({ message: 'Sandbox destroyed. Data persists in R2!' });
}
return new Response(`
Data Pipeline with Persistent Storage
Endpoints:
- POST /process - Process data and save to R2
- GET /results - Retrieve results from R2
- POST /destroy - Destroy sandbox (data survives!)
Try this flow:
1. POST /process (processes and saves to R2)
2. POST /destroy (destroys sandbox)
3. GET /results (data still accessible from R2)
`, { headers: { 'Content-Type': 'text/plain' } });
}
};生成 R2 API 令牌:
- 在 Cloudflare 仪表板 ↗ 中前往 R2 > Overview(概览)
- 选择 Manage R2 API Tokens(管理 R2 API 令牌)
- 创建具有 Object Read & Write 权限的令牌
- 复制 Access Key ID(访问密钥 ID) 与 Secret Access Key(秘密访问密钥)
将凭据设置为 Worker secrets:
npx wrangler secret put AWS_ACCESS_KEY_ID
# Paste your R2 Access Key ID
npx wrangler secret put AWS_SECRET_ACCESS_KEY
# Paste your R2 Secret Access KeyWorker secrets 经过加密,仅已部署的 Worker 可访问。调用 mountBucket() 时,SDK 会自动检测这些凭据。
部署你的 Worker:
npx wrangler deploy部署后,wrangler 会输出你的 Worker URL(例如 https://data-pipeline.yourname.workers.dev)。
现在针对已部署的 Worker 进行测试。将 YOUR_WORKER_URL 替换为你的实际 Worker URL:
# 1. Process data (saves to R2)
curl -X POST https://YOUR_WORKER_URL/process
# Returns: { "message": "Data processed...", "result": { "total": 144, "average": 48, ... } }
# 2. Verify data is accessible
curl https://YOUR_WORKER_URL/results
# Returns the same results from R2
# 3. Destroy the sandbox
curl -X POST https://YOUR_WORKER_URL/destroy
# Returns: { "message": "Sandbox destroyed. Data persists in R2!" }
# 4. Access results again (from new sandbox)
curl https://YOUR_WORKER_URL/results
# Still works! Data persisted across sandbox lifecycle关键洞察:销毁沙箱后,下一次请求会创建新的沙箱实例,挂载同一个 R2 存储桶,并发现数据仍然存在。
在本教程中,你构建了一个通过 R2 存储桶挂载演示文件系统持久化的数据处理流水线:
- 挂载存储桶:使用
mountBucket()将 R2 作为本地目录访问 - 标准文件操作:使用熟悉的文件系统命令(
cat、Pythonopen()等)访问挂载的存储桶 - 自动持久化:写入挂载目录的数据在沙箱销毁后仍然保留
- 选择正确的持久化模型:对
/data等外部存储目录使用存储桶挂载;当你需要/workspace下的持久工作区时,考虑备份与恢复 - 凭据管理:使用环境变量或显式凭据配置 R2 访问