Code Sandboxes
Code Sandboxes is a Python package for creating safe, isolated environments where AI systems can write, run, and test code without affecting the real world or the user's device.
Package Scope
Code Sandboxes is the execution layer in the Datalayer AI stack:
This section clarifies what the package owns versus what is delegated to adjacent layers.
┌─────────────────────────────────────────────────────────────┐
│ agent-runtimes │
│ (Agent hosting, protocols, UI) │
├──────────────────────────┬──────────────────────────────────┤
│ agent-codemode │ agent-skills │
│ (discovery, codegen) │ (skills management) │
├──────────────────────────┴──────────────────────────────────┤
│ code-sandboxes │ ◀── You are here
│ (Safe code execution environment) │
└─────────────────────────────────────────────────────────────┘
Responsibilities:
- ✅ Execute Python/shell code safely in isolated environments
- ✅ Provide filesystem operations (read, write, list, upload, download)
- ✅ Run shell commands with streaming output
- ✅ Manage sandbox lifecycle (start, stop, snapshot)
- ✅ Support multiple isolation levels (local, Docker, cloud)
Not Responsible For:
- ❌ MCP tool discovery or binding generation (→ agent-codemode)
- ❌ Skill management and composition (→ agent-skills)
- ❌ Agent protocols or UI components (→ agent-runtimes)
Key Features
- 🔒 Secure Isolation: Run untrusted code safely in sandboxed environments
- 🐍 Python Code Execution: Execute Python code with streaming output and rich results
- 📁 Filesystem Operations: Read, write, list, upload, and download files
- 💻 Command Execution: Run shell commands with streaming support
- 📸 Snapshots: Save and restore sandbox state
- 🚀 GPU Support: Access GPU compute for ML workloads
Sandbox Variants
Code Sandboxes supports multiple execution backends:
| Variant | Isolation Level | Best For |
|---|---|---|
local-eval | None (Python exec) | Development, testing |
local-docker | Container | Local isolated execution |
local-jupyter | Process (Jupyter kernel) | Local persistent state |
datalayer-runtime | Cloud VM | Production, GPU workloads |
Quick Start
pip install code-sandboxes
from code_sandboxes import Sandbox
with Sandbox.create() as sandbox:
result = sandbox.run_code("print('Hello from the sandbox!')")
print(result.stdout) # Hello from the sandbox!
Integration with Other Packages
With agent-codemode
Code Sandboxes is used by agent-codemode to execute tool composition code:
from code_sandboxes import Sandbox
from agent_codemode import CodeModeExecutor, ToolRegistry
# agent-codemode uses code-sandboxes internally
executor = CodeModeExecutor(registry, sandbox_variant="datalayer-runtime")
With agent-skills
Agent Skills uses Code Sandboxes to execute skill scripts:
from code_sandboxes import LocalEvalSandbox
from agent_skills import SandboxExecutor
sandbox = LocalEvalSandbox()
executor = SandboxExecutor(sandbox)
Learn More
📄️ Code Sandboxes
Code Sandboxes is a Python package for creating safe, isolated environments where AI systems can write, run, and test code without affecting the real world or the user's device.
📄️ Sandboxes
A sandbox is an isolated environment where code can be executed safely. Code Sandboxes provides a unified API across different execution backends.
📄️ Installation
Basic Installation
📄️ Comparison
This page compares Code Sandboxes with other popular code execution platforms: E2B and Modal.
📄️ API Reference
Sandbox Class
📄️ Examples
Run the examples from the examples directory.