Getting Started

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This section introduces core concepts, common workflows, and next steps for using Daytona after completing the Quick Start guide.

Dashboard

Daytona Dashboard ↗ is a visual user interface where you can manage sandboxes, access API keys, view usage, and more. It serves as the primary point of control for managing your Daytona resources.

SDKs

Daytona provides Python and TypeScript SDKs to programmatically interact with Daytona Sandboxes. They support sandbox lifecycle management, code execution, resource access, and more.

To interact with Daytona Sandboxes from the SDK, see the Python SDK and TypeScript SDK references.

CLI

Daytona provides command-line access to core features for interacting with Daytona Sandboxes, including managing their lifecycle, snapshots, and more.

To interact with Daytona Sandboxes from the command line, install the Daytona CLI:

Mac/Linux
Windows

brew install daytonaio/cli/daytona

powershell -Command "irm https://get.daytona.io/windows | iex"

After installing the Daytona CLI, use the daytona command to interact with Daytona Sandboxes from the command line.

To view all available commands and flags, see the CLI Reference.

API

Daytona provides a RESTful API for interacting with Daytona Sandboxes, including managing their lifecycle, snapshots, and more. It serves as a flexible and powerful way to interact with Daytona from your own applications.

To interact with Daytona Sandboxes from the API, see the API Reference.

Multiple runtime support

Daytona supports multiple programming language runtimes for direct code execution inside the sandbox.

TypeScript SDK works across multiple JavaScript runtimes including Node.js, browsers, and serverless platforms: Cloudflare Workers, AWS Lambda, Azure Functions, etc.

Using the Daytona SDK in browser-based environments or frameworks like Vite and Next.js requires configuring node polyfills.

Daytona in Vite projects

When using Daytona SDK in a Vite-based project, configure node polyfills to ensure compatibility.

Add the following configuration to your vite.config.ts file in the plugins array:

import { nodePolyfills } from 'vite-plugin-node-polyfills'

export default defineConfig({
  plugins: [
    // ... other plugins
    nodePolyfills({
      globals: { global: true, process: true, Buffer: true },
      overrides: {
        path: 'path-browserify-win32',
      },
    }),
  ],
  // ... rest of your config
})

Daytona in Next.js projects

When using Daytona SDK in a Next.js project, configure node polyfills to ensure compatibility with Webpack and Turbopack bundlers.

Add the following configuration to your next.config.ts file:

import type { NextConfig } from 'next'
import NodePolyfillPlugin from 'node-polyfill-webpack-plugin'
import { env, nodeless } from 'unenv'

const { alias: turbopackAlias } = env(nodeless, {})

const nextConfig: NextConfig = {
  // Turbopack
  experimental: {
    turbo: {
      resolveAlias: {
        ...turbopackAlias,
      },
    },
  },
  // Webpack
  webpack: (config, { isServer }) => {
    if (!isServer) {
      config.plugins.push(new NodePolyfillPlugin())
    }
    return config
  },
}

export default nextConfig

Run code inside a Sandbox

Create a Daytona Sandbox instance and run code securely inside it. The following snippet is an example of running a calculation securely inside a Daytona Sandbox.

Python
TypeScript

from daytona import Daytona, DaytonaConfig

# Initialize the Daytona client
daytona = Daytona(DaytonaConfig(api_key="YOUR_API_KEY"))

# Create the Sandbox instance
sandbox = daytona.create()

# Run code securely inside the Sandbox
response = sandbox.process.code_run('print("Sum of 3 and 4 is " + str(3 + 4))')
if response.exit_code != 0:
    print(f"Error running code: {response.exit_code} {response.result}")
else:
    print(response.result)

# Clean up the Sandbox
sandbox.delete()

import { Daytona } from '@daytonaio/sdk'

async function main() {
  // Initialize the Daytona client
  const daytona = new Daytona({
    apiKey: 'YOUR_API_KEY',
  })

  let sandbox;
  try {
    // Create the Sandbox instance
    sandbox = await daytona.create({
      language: "python",
    });
    // Run code securely inside the Sandbox
    const response = await sandbox.process.codeRun(
      'print("Sum of 3 and 4 is " + str(3 + 4))'
    );
    if (response.exitCode !== 0) {
      console.error("Error running code:", response.exitCode, response.result);
    } else {
      console.log(response.result);
    }
  } catch (error) {
    console.error("Sandbox flow error:", error);
  } finally {
    // Clean up the Sandbox
    if (sandbox) {
      await sandbox.delete();
    }
  }
}

main().catch(console.error)

Python
TypeScript

python main.py

bash npx tsx ./index.ts

Sum of 3 and 4 is 7

Preview your app

Preview your app by uploading a file containing a simple Flask app to a Daytona Sandbox. The web server runs on port 3000 and is accessible through the provided preview URL.

Python
TypeScript

from daytona import Daytona, DaytonaConfig, SessionExecuteRequest

daytona = Daytona(DaytonaConfig(api_key="YOUR_API_KEY"))

sandbox = daytona.create()

app_code = b'''
from flask import Flask

app = Flask(__name__)

@app.route('/')
def hello():
    return """
    <!DOCTYPE html>
    <html>
    <head>
        <title>Hello World</title>
        <link rel="icon" href="https://www.daytona.io/favicon.ico">
    </head>
    <body style="display: flex; justify-content: center; align-items: center; height: 100vh; margin: 0; background-color: #0a0a0a; font-family: Arial, sans-serif;">
        <div style="text-align: center; padding: 2rem; border-radius: 10px; background-color: white; box-shadow: 0 4px 8px rgba(0,0,0,0.1);">
            <img src="https://raw.githubusercontent.com/daytonaio/daytona/main/assets/images/Daytona-logotype-black.png" alt="Daytona Logo" style="width: 180px; margin: 10px 0px;">
            <p>This web app is running in a Daytona sandbox!</p>
        </div>
    </body>
    </html>
    """

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=3000)
'''

# Save the Flask app to a file

sandbox.fs.upload_file(app_code, "app.py")

# Create a new session and execute a command

exec_session_id = "python-app-session"
sandbox.process.create_session(exec_session_id)

sandbox.process.execute_session_command(exec_session_id, SessionExecuteRequest(
    command="python /app.py",
    var_async=True
))

# Get the preview link for the Flask app

preview_info = sandbox.get_preview_link(3000)
print(f"Flask app is available at: {preview_info.url}")

import { Daytona } from '@daytonaio/sdk';

const daytona = new Daytona(({
  apiKey: "YOUR_API_KEY"
}));

async function main() {
  const sandbox = await daytona.create();

  const appCode = Buffer.from(`
from flask import Flask

app = Flask(__name__)

@app.route('/')
def hello():
    return """
    <!DOCTYPE html>
    <html>
    <head>
        <title>Hello World</title>
        <link rel="icon" href="https://www.daytona.io/favicon.ico">
    </head>
    <body style="display: flex; justify-content: center; align-items: center; height: 100vh; margin: 0; background-color: #0a0a0a; font-family: Arial, sans-serif;">
        <div style="text-align: center; padding: 2rem; border-radius: 10px; background-color: white; box-shadow: 0 4px 8px rgba(0,0,0,0.1);">
            <img src="https://raw.githubusercontent.com/daytonaio/daytona/main/assets/images/Daytona-logotype-black.png" alt="Daytona Logo" style="width: 180px; margin: 10px 0px;">
            <p>This web app is running in a Daytona sandbox!</p>
        </div>
    </body>
    </html>
    """

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=3000)
  `);

  // Save the Flask app to a file
  await sandbox.fs.uploadFile(appCode, "app.py");

  // Create a new session and execute a command
  const execSessionId = "python-app-session";
  await sandbox.process.createSession(execSessionId);

  await sandbox.process.executeSessionCommand(execSessionId, ({
    command: `python app.py`,
    async: true,
  }));

  // Get the preview link for the Flask app
  const previewInfo = await sandbox.getPreviewLink(3000);
  console.log(`Flask app is available at: ${previewInfo.url}`);
}

main().catch(error => console.error("Error:", error));

To access the preview URL endpoint programmatically, learn more about Preview & Authentication.

Connect to an LLM

Connect to an LLM using the Anthropic API and ask Claude to generate code for getting the factorial of 25 and then execute it inside in a Daytona Sandbox.

Python
TypeScript

import os
import re
import requests
from daytona import Daytona, DaytonaConfig
from dotenv import load_dotenv

load_dotenv()

daytona = Daytona(DaytonaConfig())

sandbox = daytona.create()

def get_claude_response(api_key, prompt):
    url = "https://api.anthropic.com/v1/messages"
    headers = {
        "x-api-key": api_key,
        "anthropic-version": "2023-06-01",
        "Content-Type": "application/json"
    }
    data = {
        "model": "claude-3-7-sonnet-latest",
        "max_tokens": 256,
        "messages": [{"role": "user", "content": prompt}]
    }
    response = requests.post(url, json=data, headers=headers)
    if response.status_code == 200:
        content = response.json().get("content", [])
        return "".join([item["text"] for item in content if item["type"] == "text"])
    else:
        return f"Error {response.status_code}: {response.text}"

prompt = "Python code that returns the factorial of 25. Output only the code. No explanation. No intro. No comments. Just raw code in a single code block."

result = get_claude_response(os.environ["ANTHROPIC_API_KEY"], prompt)

code_match = re.search(r"```python\n(.*?)```", result, re.DOTALL)

code = code_match.group(1) if code_match else result
code = code.replace('\\', '\\\\')

# Run Python code inside the Sandbox and get the output

response = sandbox.process.code_run(code)
print("The factorial of 25 is", response.result)

Ensure the following environment variables are set and run the snippet:

ANTHROPIC_API_KEY="YOUR_ANTHROPIC_API_KEY"
DAYTONA_API_KEY="YOUR_DAYTONA_API_KEY"
DAYTONA_TARGET=us
python claude-example.py

> The factorial of 25 is 15511210043330985984000000

import { Daytona } from '@daytonaio/sdk'
import * as dotenv from 'dotenv'
import axios from 'axios'

dotenv.config()

const daytona = new Daytona()

async function getClaudeResponse(apiKey: string, prompt: string): Promise<string> {
  const url = "https://api.anthropic.com/v1/messages"
  const headers = {
    "x-api-key": apiKey,
    "anthropic-version": "2023-06-01",
    "Content-Type": "application/json"
  }
  const data = {
    "model": "claude-3-7-sonnet-latest",
    "max_tokens": 256,
    "messages": [{"role": "user", "content": prompt}]
  }

  try {
    const response = await axios.post(url, data, { headers })
    if (response.status === 200) {
      const content = response.data.content || []
      return content
        .filter((item: any) => item.type === "text")
        .map((item: any) => item.text)
        .join("")
    } else {
      return `Error ${response.status}: ${response.statusText}`
    }
  } catch (error: any) {
    return `Error: ${error.message}`
  }
}

async function main() {
  const sandbox = await daytona.create()

  const prompt = "Python code that returns the factorial of 25. Output only the code. No explanation. No intro. No comments. Just raw code in a single code block."

  const result = await getClaudeResponse(process.env.ANTHROPIC_API_KEY || "", prompt)

  // Extract code from the response using regex
  const codeMatch = result.match(/```python\n(.*?)```/s)

  let code = codeMatch ? codeMatch[1] : result
  code = code.replace(/\\/g, '\\\\')

  // Run the extracted code in the sandbox
  const response = await sandbox.process.codeRun(code)
  console.log("The factorial of 25 is", response.result)
}

main().catch(console.error)

Running the snippet:

ANTHROPIC_API_KEY="your-anthropic-api-key"
DAYTONA_API_KEY="your-daytona-api-key"
DAYTONA_TARGET=us
npx ts-node claude-example.ts

> The factorial of 25 is 15511210043330985984000000

Examples

Daytona provides Python and TypeScript/JavaScript examples to create Daytona Sandboxes and run your code.

Learn more by checking the Daytona repository on GitHub.