---
title: CodeInterpreterTool
description: A tool for secure Python code execution in isolated Docker environments
icon: code
---

## CodeInterpreterTool

The CodeInterpreterTool provides secure Python code execution capabilities using Docker containers. It supports dynamic library installation and offers both safe (Docker-based) and unsafe (direct) execution modes.

## Installation

```bash
pip install 'crewai[tools]'
```

## Usage Example

```python
from crewai import Agent
from crewai_tools import CodeInterpreterTool

# Initialize the tool
code_tool = CodeInterpreterTool()

# Create an agent with the tool
programmer = Agent(
    role='Code Executor',
    goal='Execute and analyze Python code',
    backstory='Expert at writing and executing Python code.',
    tools=[code_tool],
    verbose=True
)
```

## Input Schema

```python
class CodeInterpreterSchema(BaseModel):
    code: str = Field(
        description="Python3 code used to be interpreted in the Docker container. ALWAYS PRINT the final result and the output of the code"
    )
    libraries_used: List[str] = Field(
        description="List of libraries used in the code with proper installing names separated by commas. Example: numpy,pandas,beautifulsoup4"
    )
```

## Function Signature

```python
def __init__(
    self,
    code: Optional[str] = None,
    user_dockerfile_path: Optional[str] = None,
    user_docker_base_url: Optional[str] = None,
    unsafe_mode: bool = False,
    **kwargs
):
    """
    Initialize the code interpreter tool.

    Args:
        code (Optional[str]): Default code to execute
        user_dockerfile_path (Optional[str]): Custom Dockerfile path
        user_docker_base_url (Optional[str]): Custom Docker daemon URL
        unsafe_mode (bool): Enable direct code execution
        **kwargs: Additional arguments for base tool
    """

def _run(
    self,
    code: str,
    libraries_used: List[str],
    **kwargs: Any
) -> str:
    """
    Execute Python code in Docker container or directly.

    Args:
        code (str): Python code to execute
        libraries_used (List[str]): Required libraries
        **kwargs: Additional arguments

    Returns:
        str: Execution output or error message
    """
```

## Best Practices

1. Security Considerations:
   - Use Docker mode by default
   - Validate input code
   - Control library access
   - Monitor execution time

2. Docker Configuration:
   - Use custom Dockerfile when needed
   - Handle container lifecycle
   - Manage resource limits
   - Clean up after execution

3. Library Management:
   - Specify exact versions
   - Use trusted packages
   - Handle dependencies
   - Verify installations

4. Error Handling:
   - Catch execution errors
   - Handle timeouts
   - Manage Docker errors
   - Provide clear messages

## Integration Example

```python
from crewai import Agent, Task, Crew
from crewai_tools import CodeInterpreterTool

# Initialize tool
code_tool = CodeInterpreterTool()

# Create agent
programmer = Agent(
    role='Code Executor',
    goal='Execute data analysis code',
    backstory='Expert Python programmer specializing in data analysis.',
    tools=[code_tool]
)

# Define task
analysis_task = Task(
    description="""Analyze the dataset using pandas and 
    create a summary visualization with matplotlib.""",
    agent=programmer
)

# The tool will use:
# {
#   "code": """
#   import pandas as pd
#   import matplotlib.pyplot as plt
#   
#   # Load and analyze data
#   df = pd.read_csv('data.csv')
#   summary = df.describe()
#   
#   # Create visualization
#   plt.figure(figsize=(10, 6))
#   df['column'].hist()
#   plt.savefig('output.png')
#   
#   print(summary)
#   """,
#   "libraries_used": "pandas,matplotlib"
# }

# Create crew
crew = Crew(
    agents=[programmer],
    tasks=[analysis_task]
)

# Execute
result = crew.kickoff()
```

## Advanced Usage

### Custom Docker Configuration
```python
# Use custom Dockerfile
tool = CodeInterpreterTool(
    user_dockerfile_path="/path/to/Dockerfile"
)

# Use custom Docker daemon
tool = CodeInterpreterTool(
    user_docker_base_url="tcp://remote-docker:2375"
)
```

### Direct Execution Mode
```python
# Enable unsafe mode (not recommended)
tool = CodeInterpreterTool(unsafe_mode=True)

# Execute code directly
result = tool.run(
    code="print('Hello, World!')",
    libraries_used=[]
)
```

### Error Handling Example
```python
try:
    code_tool = CodeInterpreterTool()
    result = code_tool.run(
        code="""
        import numpy as np
        arr = np.array([1, 2, 3])
        print(f"Array mean: {arr.mean()}")
        """,
        libraries_used=["numpy"]
    )
    print(result)
except Exception as e:
    print(f"Error executing code: {str(e)}")
```

## Notes

- Inherits from BaseTool
- Docker-based isolation
- Dynamic library installation
- Secure code execution
- Custom Docker support
- Comprehensive error handling
- Resource management
- Container cleanup
- Library dependency handling
- Execution output capture