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daytona

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Basic Information

Daytona provides secure, elastic infrastructure and developer tooling for creating, running, and managing AI-generated code in isolated sandboxes. The repository supplies client SDKs for Python and TypeScript, code examples, and APIs to programmatically create sandboxes, run code, and remove environments. It is designed to let developers execute untrusted or generated code with strong isolation using per-sandbox runtimes, persistent environments, and compatibility with OCI/Docker images. The README highlights a quick start flow that requires an account and API key, and demonstrates sandbox lifecycle management and simple code execution calls. The project emphasizes low-latency sandbox creation and programmatic control over files, Git, language server protocol interactions, and execution flows. The repository targets developers and teams who need a managed runtime service to run, test, and integrate AI-produced code into applications and workflows.

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21139
App URL
https://github.com/daytonaio/daytona
Github Repository
https://github.com/daytonaio/daytona/blob/main/README.md

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App Details

Features
The README documents several core features: sub-90ms sandbox creation for fast start-up, separated and isolated runtime environments to protect host infrastructure, and programmatic control via file, Git, LSP, and execute APIs. It supports unlimited persistence so sandboxes can live indefinitely and promises OCI/Docker image compatibility to run arbitrary container-based environments. SDKs for Python and TypeScript are provided with usage examples illustrating sandbox creation, code execution, and cleanup. The project also calls out planned capabilities such as massive parallelization and forkable sandbox filesystem and memory state. Additional repository signals include installation instructions, a quick start guide, and a reference to dashboard-managed API keys and a web-based console for account management.
Use Cases
Daytona helps teams safely run and iterate on AI-generated code without exposing production systems to risk. By providing fast, isolated sandboxes and SDKs, it enables developers to integrate code execution into testing, development, or agent workflows, automating sandbox lifecycle operations and code evaluation. Persistent sandboxes and OCI compatibility make it easier to reproduce environments and run long-lived sessions or experiments. Programmatic APIs for files, Git, LSP, and execution simplify building higher-level tooling such as automated code evaluation, debugging flows, or CI tasks that involve generated code. The quick start instructions and examples lower the onboarding barrier by showing how to obtain an API key, create a sandbox, run code, handle results, and remove the sandbox when finished.

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