Master Secure AI Code Execution with Daytona SDK: A Complete Guide

Introduction to Daytona SDK Sandbox Environment

This tutorial demonstrates how to use Daytona SDK to create a secure sandbox environment for executing untrusted or AI-generated Python code safely within a Notebook. Starting with basic sandbox creation and execution, it gradually advances into more complex scenarios including data processing, file operations, and AI-generated code execution.

Setting Up the Daytona SDK

The tutorial begins by installing and importing Daytona SDK, initializing the core classes Daytona, DaytonaConfig, and CreateSandboxParams. These classes help configure and create secure Python sandboxes. Standard libraries like os, time, and json are also imported to assist with operations inside the sandbox.

Basic Sandbox Creation and Code Execution

A simple sandbox is created where basic Python code is executed, demonstrating isolated code execution without affecting the host environment. Example code runs print statements and simple arithmetic operations.

Secure Data Processing

The tutorial shows how to install dependencies like pandas inside the sandbox and process data securely. It creates a sample dataset and computes statistics such as average age and salary, outputting the results as a JSON string.

File Operations Within Sandbox

File creation, reading, and listing are showcased within the sandbox. A JSON file is written and then read back, and the contents of the workspace directory are listed to demonstrate file system interaction safely isolated from the host.

Executing AI-Generated Code Snippets

Various AI-generated Python code snippets are run securely inside the sandbox. These include calculating Fibonacci sequences recursively, sorting algorithms, and performing data analysis with statistical calculations.

Parallel Task Execution Across Multiple Sandboxes

The tutorial creates multiple sandboxes to run different tasks in parallel, such as computing prime numbers, string processing, and mathematical calculations. This showcases Daytona's ability to handle concurrent isolated executions.

Cleaning Up Resources

Finally, the tutorial emphasizes the importance of resource management by cleaning up and removing all created sandboxes, preventing resource leaks and maintaining system hygiene.

Running the Full Tutorial

A main function guides users through setting up a Daytona account, obtaining an API key, and running the full tutorial. It includes validation checks to ensure the API key is correctly set before executing the workflow.

This comprehensive guide empowers developers to safely execute dynamic and AI-generated Python code, making Daytona SDK a valuable tool for secure code execution in machine learning pipelines or automated testing frameworks.