e2b-sandboxes
E2B open-source cloud sandboxes for executing AI-generated code securely. USE FOR: run code in sandbox, e2b, code interpreter, execute AI code, secure code execution, isolated environment, AI coding agent execution, run untrusted code, cloud sandbox, code execution API, python sandbox cloud, AI agent code runner, safe code execution, jupyter sandbox.
来源信息
- 仓库
- mahmoud20138/Tradecraft
- 最近来源活动
- 2026年4月23日 08:40
- 检测到的 SKILL.md 语言
- 英语
- 星标
- 15
- 分支
- 4
安装方式
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
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SKILL.md
来源说明 · 只读预览- name
- e2b-sandboxes
- description
- E2B open-source cloud sandboxes for executing AI-generated code securely. USE FOR: run code in sandbox, e2b, code interpreter, execute AI code, secure code execution, isolated environment, AI coding agent execution, run untrusted code, cloud sandbox, code execution API, python sandbox cloud, AI agent code runner, safe code execution, jupyter sandbox.
- kind
- tool
- category
- dev/tools
- repo
- https://github.com/e2b-dev/E2B
- tags
- ["sandbox","code-execution","ai","cloud","security"]
- status
- active
# E2B Code Interpreter Sandboxes
> Secure isolated cloud VMs for executing AI-generated code. Open-source.
## Installation
```bash
pip install e2b-code-interpreter
npm i @e2b/code-interpreter
export E2B_API_KEY=your_key_here # get at https://e2b.dev/dashboard
```
## Python Usage
```python
from e2b_code_interpreter import Sandbox
# Basic execution
with Sandbox() as sandbox:
result = sandbox.run_code("x = 1 + 1; print(x)")
print(result.logs.stdout) # ["2"]
# Stateful multi-step session
with Sandbox() as sandbox:
sandbox.run_code("data = [1, 2, 3]")
r = sandbox.run_code("print(sum(data))")
print(r.logs.stdout) # ["6"]
```
## TypeScript Usage
```typescript
import { Sandbox } from "@e2b/code-interpreter"
const sandbox = await Sandbox.create()
const result = await sandbox.runCode("print(1 + 1)")
console.log(result.logs.stdout)
await sandbox.kill()
```
## Use With Claude AI Agent
```python
from anthropic import Anthropic
from e2b_code_interpreter import Sandbox
client = Anthropic()
sandbox = Sandbox()
response = client.messages.create(
model="claude-sonnet-4-6",
max_tokens=1024,
messages=[{"role": "user", "content": "Write Python to compute fibonacci(10)"}]
)
code = response.content[0].text
result = sandbox.run_code(code)
print(result.logs.stdout)
sandbox.kill()
```
## Key Features
| Feature | Detail |
|---------|--------|
| Isolation | Each sandbox = fresh cloud VM |
| Stateful | Variables persist within session |
| Languages | Python, JavaScript/TypeScript |
| Outputs | stdout, stderr, rich results (plots, tables) |
| Self-hostable | GCP (prod-ready), AWS (in progress), Azure (planned) |
## Self-Hosting
```bash
# GCP (production-ready)
terraform apply -var-file=gcp.tfvars
```
---
在 GitHub 查看