# E2B Code Interpreter SDK — Sandboxed Python for AI Agents

> E2B Code Interpreter is a Python SDK for AI agents to run untrusted code safely. Jupyter-like cells, file uploads, charts auto-rendered. ~150ms cold start.

## Install

Save as a script file and run:

## Quick Use

1. Sign up at e2b.dev → copy your API key
2. `pip install e2b-code-interpreter`
3. `Sandbox.create()` then `sandbox.run_code('...')` — outputs include text, charts, files

---

## Intro

The E2B Code Interpreter SDK gives AI agents a managed Jupyter-like environment to execute Python with file uploads, plot rendering, and persistent state across cells. ~150ms cold start, full Linux underneath. Best for: ChatGPT-style code-interpreter features in your own product, data analysis agents, autonomous coding agents that need to run their own code. Works with: Python SDK and JS SDK. Setup time: 2 minutes.

---

### Run code from agent

```python
from e2b_code_interpreter import Sandbox

with Sandbox.create() as sandbox:
    # Upload a CSV
    sandbox.files.write("/data/sales.csv", open("sales.csv", "rb").read())

    # Execute code
    execution = sandbox.run_code('''
import pandas as pd
df = pd.read_csv('/data/sales.csv')
df.groupby('region')['amount'].sum().plot(kind='bar')
''')

    # Get text output
    print(execution.text)

    # Get charts (auto-extracted as PNG)
    for chart in execution.results:
        if chart.png:
            with open(f"chart-{chart.id}.png", "wb") as f:
                f.write(chart.png)
```

### Persistent state across calls

```python
sandbox = Sandbox.create()

# First call defines a function
sandbox.run_code('''
def analyze_sales(region):
    return df[df.region == region]['amount'].sum()
''')

# Second call uses the function — state preserved
result = sandbox.run_code("analyze_sales('US')")
print(result.text)  # whatever the function returned
```

### Hook into Claude / GPT tool use

```python
from anthropic import Anthropic
from e2b_code_interpreter import Sandbox

sandbox = Sandbox.create()

tools = [{
    "name": "run_python",
    "description": "Run Python code in a sandbox. Persistent state across calls.",
    "input_schema": {
        "type": "object",
        "properties": {"code": {"type": "string"}},
        "required": ["code"]
    }
}]

response = anthropic.messages.create(
    model="claude-3-5-sonnet-20241022",
    tools=tools,
    messages=[{"role": "user", "content": "Plot the FAANG stock prices over 2024"}],
)

# When Claude calls run_python, execute in sandbox and return output
```

---

### FAQ

**Q: Is E2B free?**
A: Yes — generous free tier (~100 hours of sandbox time per month). Paid tiers add longer sessions, more concurrency, persistent disk. Self-hosting is possible via E2B's open-source firecracker-based runtime.

**Q: How is this different from running code in Modal Sandboxes?**
A: E2B is optimized for *interactive* code execution (Jupyter cells, persistent kernel state, chart auto-extraction). Modal Sandboxes are general-purpose Linux. For ChatGPT-style code interpreter UX, E2B is the more direct fit.

**Q: Is it safe to run untrusted code?**
A: Yes — E2B uses Firecracker microVMs (the same tech as AWS Lambda) for isolation. Each sandbox has its own kernel, filesystem, and network namespace. Sandbox-to-sandbox or sandbox-to-host escalation is the threat model E2B is built to prevent.

---

## Source & Thanks

> Built by [E2B](https://github.com/e2b-dev). Licensed under Apache-2.0.
>
> [e2b-dev/code-interpreter](https://github.com/e2b-dev/code-interpreter) — ⭐ 1,500+

---

<!-- ZH -->

## 快速使用

1. 在 e2b.dev 注册，复制 API key
2. `pip install e2b-code-interpreter`
3. `Sandbox.create()` 然后 `sandbox.run_code('...')`，输出含文本、图表、文件

---

## 简介

E2B Code Interpreter SDK 给 AI agent 一个托管的类 Jupyter 环境，能跑 Python、上传文件、渲染图表、跨 cell 保留状态。~150ms 冷启动，底下是完整 Linux。适合在自己产品里搭 ChatGPT 风格的 code interpreter、数据分析 agent、需要跑自己代码的自主编码 agent。Python SDK 和 JS SDK 都有。装机时间 2 分钟。

---

### 从 agent 跑代码

```python
from e2b_code_interpreter import Sandbox

with Sandbox.create() as sandbox:
    # 上传 CSV
    sandbox.files.write("/data/sales.csv", open("sales.csv", "rb").read())

    # 执行代码
    execution = sandbox.run_code('''
import pandas as pd
df = pd.read_csv('/data/sales.csv')
df.groupby('region')['amount'].sum().plot(kind='bar')
''')

    # 拿文本输出
    print(execution.text)

    # 拿图（自动抽取为 PNG）
    for chart in execution.results:
        if chart.png:
            with open(f"chart-{chart.id}.png", "wb") as f:
                f.write(chart.png)
```

### 跨调用持久状态

```python
sandbox = Sandbox.create()

# 第一次调用定义函数
sandbox.run_code('''
def analyze_sales(region):
    return df[df.region == region]['amount'].sum()
''')

# 第二次调用使用函数 —— 状态保留
result = sandbox.run_code("analyze_sales('US')")
print(result.text)  # 函数返回的内容
```

### 接到 Claude / GPT 的工具使用

```python
from anthropic import Anthropic
from e2b_code_interpreter import Sandbox

sandbox = Sandbox.create()

tools = [{
    "name": "run_python",
    "description": "Run Python code in a sandbox. Persistent state across calls.",
    "input_schema": {
        "type": "object",
        "properties": {"code": {"type": "string"}},
        "required": ["code"]
    }
}]

response = anthropic.messages.create(
    model="claude-3-5-sonnet-20241022",
    tools=tools,
    messages=[{"role": "user", "content": "Plot the FAANG stock prices over 2024"}],
)

# Claude 调 run_python 时，在 sandbox 里执行并返回输出
```

---

### FAQ

**Q: E2B 免费吗？**
A: 免费 —— 大方的免费档（每月约 100 小时 sandbox 时间）。付费档加更长会话、更高并发、持久磁盘。E2B 的开源 firecracker 运行时也能自托管。

**Q: 跟在 Modal Sandbox 里跑代码啥区别？**
A: E2B 优化 *交互式* 代码执行（Jupyter cell、持久 kernel 状态、图自动抽取）。Modal Sandbox 是通用 Linux。要 ChatGPT 风格 code interpreter 体验，E2B 更直接。

**Q: 跑不可信代码安全吗？**
A: 安全 —— E2B 用 Firecracker microVM（跟 AWS Lambda 一样的技术）做隔离。每个 sandbox 有独立 kernel / 文件系统 / 网络命名空间。E2B 就是为防 sandbox 之间或 sandbox 到 host 提权设计的。

---

## 来源与感谢

> Built by [E2B](https://github.com/e2b-dev). Licensed under Apache-2.0.
>
> [e2b-dev/code-interpreter](https://github.com/e2b-dev/code-interpreter) — ⭐ 1,500+


---
Source: https://tokrepo.com/en/workflows/e2b-code-interpreter-sdk-sandboxed-python-for-ai-agents
Author: E2B