---
title: Analyze data with AI
description: Upload CSV files, generate analysis code with Claude, and return visualizations.
image: https://developers.cloudflare.com/dev-products-preview.png
---

> Documentation Index  
> Fetch the complete documentation index at: https://developers.cloudflare.com/sandbox/llms.txt  
> Use this file to discover all available pages before exploring further. 

[Skip to content](#%5Ftop) 

# Analyze data with AI

Build an AI-powered data analysis system that accepts CSV uploads, uses Claude to generate Python analysis code, executes it in sandboxes, and returns visualizations.

**Time to complete**: 25 minutes

## Prerequisites

1. Sign up for a [Cloudflare account ↗](https://dash.cloudflare.com/sign-up/workers-and-pages).
2. Install [Node.js ↗](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm).

Node.js version manager

Use a Node version manager like [Volta ↗](https://volta.sh/) or [nvm ↗](https://github.com/nvm-sh/nvm) to avoid permission issues and change Node.js versions. [Wrangler](https://developers.cloudflare.com/workers/wrangler/install-and-update/), discussed later in this guide, requires a Node version of `16.17.0` or later.

You'll also need:

* An [Anthropic API key ↗](https://console.anthropic.com/) for Claude
* [Docker ↗](https://www.docker.com/) running locally

## 1\. Create your project

Create a new Sandbox SDK project:

 npm  yarn  pnpm 

```
npm create cloudflare@latest -- analyze-data --template=cloudflare/sandbox-sdk/examples/minimal
```

```
yarn create cloudflare analyze-data --template=cloudflare/sandbox-sdk/examples/minimal
```

```
pnpm create cloudflare@latest analyze-data --template=cloudflare/sandbox-sdk/examples/minimal
```

Terminal window

```
cd analyze-data
```

## 2\. Install dependencies

 npm  yarn  pnpm  bun 

```
npm i @anthropic-ai/sdk
```

```
yarn add @anthropic-ai/sdk
```

```
pnpm add @anthropic-ai/sdk
```

```
bun add @anthropic-ai/sdk
```

## 3\. Build the analysis handler

Replace `src/index.ts`:

TypeScript

```
import { getSandbox, proxyToSandbox, type Sandbox } from "@cloudflare/sandbox";import Anthropic from "@anthropic-ai/sdk";
export { Sandbox } from "@cloudflare/sandbox";
interface Env {  Sandbox: DurableObjectNamespace<Sandbox>;  ANTHROPIC_API_KEY: string;}
export default {  async fetch(request: Request, env: Env): Promise<Response> {    const proxyResponse = await proxyToSandbox(request, env);    if (proxyResponse) return proxyResponse;
    if (request.method !== "POST") {      return Response.json(        { error: "POST CSV file and question" },        { status: 405 },      );    }
    try {      const formData = await request.formData();      const csvFile = formData.get("file") as File;      const question = formData.get("question") as string;
      if (!csvFile || !question) {        return Response.json(          { error: "Missing file or question" },          { status: 400 },        );      }
      // Upload CSV to sandbox      const sandbox = getSandbox(env.Sandbox, `analysis-${Date.now()}`);      const csvPath = "/workspace/data.csv";      await sandbox.writeFile(csvPath, await csvFile.text());
      // Analyze CSV structure      const structure = await sandbox.exec(        `python3 -c "import pandas as pd; df = pd.read_csv('${csvPath}'); print(f'Rows: {len(df)}'); print(f'Columns: {list(df.columns)[:5]}')"`,      );
      if (!structure.success) {        return Response.json(          { error: "Failed to read CSV", details: structure.stderr },          { status: 400 },        );      }
      // Generate analysis code with Claude      const code = await generateAnalysisCode(        env.ANTHROPIC_API_KEY,        csvPath,        question,        structure.stdout,      );
      // Write and execute the analysis code      await sandbox.writeFile("/workspace/analyze.py", code);      const result = await sandbox.exec("python /workspace/analyze.py");
      if (!result.success) {        return Response.json(          { error: "Analysis failed", details: result.stderr },          { status: 500 },        );      }
      async function streamToBase64(stream) {        const blob = await new Response(stream).blob();        const buffer = await blob.arrayBuffer();        const bytes = new Uint8Array(buffer);
        // Convert to base64        let binary = '';        for (let i = 0; i < bytes.length; i++) {          binary += String.fromCharCode(bytes[i]);        }        return btoa(binary);      }
      // Check for generated chart      let chart = null;      try {        const { content, mimeType } = await sandbox.readFile("/workspace/chart.png", {          encoding: "none"        });        chart = `data:${mimeType};base64,${await streamToBase64(content)}`;      } catch {        // No chart generated      }
      await sandbox.destroy();
      return Response.json({        success: true,        output: result.stdout,        chart,        code,      });    } catch (error: any) {      return Response.json({ error: error.message }, { status: 500 });    }  },};
async function generateAnalysisCode(  apiKey: string,  csvPath: string,  question: string,  csvStructure: string,): Promise<string> {  const anthropic = new Anthropic({ apiKey });
  const response = await anthropic.messages.create({    model: "claude-sonnet-4-5",    max_tokens: 2048,    messages: [      {        role: "user",        content: `CSV at ${csvPath}:${csvStructure}
Question: "${question}"
Generate Python code that:- Reads CSV with pandas- Answers the question- Saves charts to /workspace/chart.png if helpful- Prints findings to stdout
Use pandas, numpy, matplotlib.`,      },    ],    tools: [      {        name: "generate_python_code",        description: "Generate Python code for data analysis",        input_schema: {          type: "object",          properties: {            code: { type: "string", description: "Complete Python code" },          },          required: ["code"],        },      },    ],  });
  for (const block of response.content) {    if (block.type === "tool_use" && block.name === "generate_python_code") {      return (block.input as { code: string }).code;    }  }
  throw new Error("Failed to generate code");}
```

## 4\. Set up local environment variables

Create a `.dev.vars` file in your project root for local development:

Terminal window

```
echo "ANTHROPIC_API_KEY=your_api_key_here\nSANDBOX_TRANSPORT=rpc" > .dev.vars
```

Replace `your_api_key_here` with your actual API key from the [Anthropic Console ↗](https://console.anthropic.com/).

The `SANDBOX_TRANSPORT` is required to use the new file streaming APIs.

Note

The `.dev.vars` file is automatically gitignored and only used during local development with `npm run dev`.

## 5\. Test locally

Download a sample CSV:

Terminal window

```
# Create a test CSVecho "year,rating,title2020,8.5,Movie A2021,7.2,Movie B2022,9.1,Movie C" > test.csv
```

Start the dev server:

Terminal window

```
npm run dev
```

Test with curl:

Terminal window

```
curl -X POST http://localhost:8787 \  -F "file=@test.csv" \  -F "question=What is the average rating by year?"
```

Response:

```
{  "success": true,  "output": "Average ratings by year:\n2020: 8.5\n2021: 7.2\n2022: 9.1",  "chart": "data:image/png;base64,...",  "code": "import pandas as pd\nimport matplotlib.pyplot as plt\n..."}
```

## 6\. Deploy

Deploy your Worker:

Terminal window

```
npx wrangler deploy
```

Then set your Anthropic API key as a production secret:

Terminal window

```
npx wrangler secret put ANTHROPIC_API_KEY
```

Paste your API key from the [Anthropic Console ↗](https://console.anthropic.com/) when prompted.

Warning

Wait 2-3 minutes after first deployment for container provisioning.

## What you built

An AI data analysis system that:

* Uploads CSV files to sandboxes
* Uses Claude's tool calling to generate analysis code
* Executes Python with pandas and matplotlib
* Returns text output and visualizations

## Next steps

* [Code Interpreter API](https://developers.cloudflare.com/sandbox/api/interpreter/) \- Use the built-in code interpreter
* [File operations](https://developers.cloudflare.com/sandbox/guides/manage-files/) \- Advanced file handling
* [Streaming output](https://developers.cloudflare.com/sandbox/guides/streaming-output/) \- Real-time progress updates

```json
{"@context":"https://schema.org","@type":"TechArticle","@id":"https://developers.cloudflare.com/sandbox/tutorials/analyze-data-with-ai/#page","headline":"Analyze data with AI · Cloudflare Sandbox SDK docs","description":"Upload CSV files, generate analysis code with Claude, and return visualizations.","url":"https://developers.cloudflare.com/sandbox/tutorials/analyze-data-with-ai/","inLanguage":"en","image":"https://developers.cloudflare.com/dev-products-preview.png","dateModified":"2026-05-13","publisher":{"@type":"Organization","name":"Cloudflare","url":"https://www.cloudflare.com/"},"isPartOf":{"@type":"WebSite","@id":"https://developers.cloudflare.com/#website","name":"Cloudflare Docs","url":"https://developers.cloudflare.com/"}}
{"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"item":{"@id":"/directory/","name":"Directory"}},{"@type":"ListItem","position":2,"item":{"@id":"/sandbox/","name":"Sandbox SDK"}},{"@type":"ListItem","position":3,"item":{"@id":"/sandbox/tutorials/","name":"Tutorials"}},{"@type":"ListItem","position":4,"item":{"@id":"/sandbox/tutorials/analyze-data-with-ai/","name":"Analyze data with AI"}}]}
```
