Code execution tool

Claude can analyze data, create visualizations, perform complex calculations, run system commands, create and edit files, and process uploaded files directly within the API conversation. The code execution tool allows Claude to run Bash commands and manipulate files, including writing code, in a secure, sandboxed environment.

Code execution is free when used with web search or web fetch. When web_search_20260209 or web_fetch_20260209 is included in your request, there are no additional charges for code execution tool calls beyond the standard input and output token costs. Standard code execution charges apply when these tools are not included.

Code execution is a core primitive for building high-performance agents. It enables dynamic filtering in web search and web fetch tools, allowing Claude to process results before they reach the context window, improving accuracy while reducing token consumption.

Model compatibility

The code execution tool is available on the following models:

Platform availability

Code execution is available on:

• Claude API (Anthropic)
• Microsoft Azure AI Foundry

Code execution is not currently available on Amazon Bedrock or Google Vertex AI.

Quick start

Here's a simple example that asks Claude to perform a calculation:

curl https://api.anthropic.com/v1/messages \
    --header "x-api-key: $ANTHROPIC_API_KEY" \
    --header "anthropic-version: 2023-06-01" \
    --header "content-type: application/json" \
    --data '{
        "model": "claude-opus-4-6",
        "max_tokens": 4096,
        "messages": [
            {
                "role": "user",
                "content": "Calculate the mean and standard deviation of [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]"
            }
        ],
        "tools": [{
            "type": "code_execution_20250825",
            "name": "code_execution"
        }]
    }'

How code execution works

When you add the code execution tool to your API request:

1. Claude evaluates whether code execution would help answer your question
2. The tool automatically provides Claude with the following capabilities:
   • Bash commands: Execute shell commands for system operations and package management
   • File operations: Create, view, and edit files directly, including writing code
3. Claude can use any combination of these capabilities in a single request
4. All operations run in a secure sandbox environment
5. Claude provides results with any generated charts, calculations, or analysis

Using code execution with other execution tools

When you provide code execution alongside client-provided tools that also run code (such as a bash tool or custom REPL), Claude is operating in a multi-computer environment. The code execution tool runs in Anthropic's sandboxed container, while your client-provided tools run in a separate environment that you control. Claude can sometimes confuse these environments, attempting to use the wrong tool or assuming state is shared between them.

To avoid this, add instructions to your system prompt that clarify the distinction:

When multiple code execution environments are available, be aware that:
- Variables, files, and state do NOT persist between different execution environments
- Use the code_execution tool for general-purpose computation in Anthropic's sandboxed environment
- Use client-provided execution tools (e.g., bash) when you need access to the user's local system, files, or data
- If you need to pass results between environments, explicitly include outputs in subsequent tool calls rather than assuming shared state

This is especially important when combining code execution with web search or web fetch, which enable code execution automatically. If your application already provides a client-side shell tool, the automatic code execution creates a second execution environment that Claude needs to distinguish between.

How to use the tool

Execute Bash commands

Ask Claude to check system information and install packages:

curl https://api.anthropic.com/v1/messages \
    --header "x-api-key: $ANTHROPIC_API_KEY" \
    --header "anthropic-version: 2023-06-01" \
    --header "content-type: application/json" \
    --data '{
        "model": "claude-opus-4-6",
        "max_tokens": 4096,
        "messages": [{
            "role": "user",
            "content": "Check the Python version and list installed packages"
        }],
        "tools": [{
            "type": "code_execution_20250825",
            "name": "code_execution"
        }]
    }'

Create and edit files directly

Claude can create, view, and edit files directly in the sandbox using the file manipulation capabilities:

curl https://api.anthropic.com/v1/messages \
    --header "x-api-key: $ANTHROPIC_API_KEY" \
    --header "anthropic-version: 2023-06-01" \
    --header "content-type: application/json" \
    --data '{
        "model": "claude-opus-4-6",
        "max_tokens": 4096,
        "messages": [{
            "role": "user",
            "content": "Create a config.yaml file with database settings, then update the port from 5432 to 3306"
        }],
        "tools": [{
            "type": "code_execution_20250825",
            "name": "code_execution"
        }]
    }'

Upload and analyze your own files

To analyze your own data files (CSV, Excel, images, etc.), upload them via the Files API and reference them in your request:

The Python environment can process various file types uploaded via the Files API, including:

• CSV
• Excel (.xlsx, .xls)
• JSON
• XML
• Images (JPEG, PNG, GIF, WebP)
• Text files (.txt, .md, .py, etc)

Upload and analyze files

1. Upload your file using the Files API
2. Reference the file in your message using a container_upload content block
3. Include the code execution tool in your API request

# First, upload a file
curl https://api.anthropic.com/v1/files \
    --header "x-api-key: $ANTHROPIC_API_KEY" \
    --header "anthropic-version: 2023-06-01" \
    --header "anthropic-beta: files-api-2025-04-14" \
    --form 'file=@"data.csv"' \

# Then use the file_id with code execution
curl https://api.anthropic.com/v1/messages \
    --header "x-api-key: $ANTHROPIC_API_KEY" \
    --header "anthropic-version: 2023-06-01" \
    --header "anthropic-beta: files-api-2025-04-14" \
    --header "content-type: application/json" \
    --data '{
        "model": "claude-opus-4-6",
        "max_tokens": 4096,
        "messages": [{
            "role": "user",
            "content": [
                {"type": "text", "text": "Analyze this CSV data"},
                {"type": "container_upload", "file_id": "file_abc123"}
            ]
        }],
        "tools": [{
            "type": "code_execution_20250825",
            "name": "code_execution"
        }]
    }'

Retrieve generated files

When Claude creates files during code execution, you can retrieve these files using the Files API:

# Initialize the client
client = Anthropic()

# Request code execution that creates files
response = client.beta.messages.create(
    model="claude-opus-4-6",
    betas=["files-api-2025-04-14"],
    max_tokens=4096,
    messages=[
        {
            "role": "user",
            "content": "Create a matplotlib visualization and save it as output.png",
        }
    ],
    tools=[{"type": "code_execution_20250825", "name": "code_execution"}],
)


# Extract file IDs from the response
def extract_file_ids(response):
    file_ids = []
    for item in response.content:
        if item.type == "bash_code_execution_tool_result":
            content_item = item.content
            if content_item.type == "bash_code_execution_result":
                for file in content_item.content:
                    if hasattr(file, "file_id"):
                        file_ids.append(file.file_id)
    return file_ids


# Download the created files
for file_id in extract_file_ids(response):
    file_metadata = client.beta.files.retrieve_metadata(file_id)
    file_content = client.beta.files.download(file_id)
    file_content.write_to_file(file_metadata.filename)
    print(f"Downloaded: {file_metadata.filename}")

Combine operations

A complex workflow using all capabilities:

# First, upload a file
curl https://api.anthropic.com/v1/files \
    --header "x-api-key: $ANTHROPIC_API_KEY" \
    --header "anthropic-version: 2023-06-01" \
    --header "anthropic-beta: files-api-2025-04-14" \
    --form 'file=@"data.csv"' \
    > file_response.json

# Extract file_id (using jq)
FILE_ID=$(jq -r '.id' file_response.json)

# Then use it with code execution
curl https://api.anthropic.com/v1/messages \
    --header "x-api-key: $ANTHROPIC_API_KEY" \
    --header "anthropic-version: 2023-06-01" \
    --header "anthropic-beta: files-api-2025-04-14" \
    --header "content-type: application/json" \
    --data '{
        "model": "claude-opus-4-6",
        "max_tokens": 4096,
        "messages": [{
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "Analyze this CSV data: create a summary report, save visualizations, and create a README with the findings"
                },
                {
                    "type": "container_upload",
                    "file_id": "'$FILE_ID'"
                }
            ]
        }],
        "tools": [{
            "type": "code_execution_20250825",
            "name": "code_execution"
        }]
    }'

Tool definition

The code execution tool requires no additional parameters:

{
  "type": "code_execution_20250825",
  "name": "code_execution"
}

When this tool is provided, Claude automatically gains access to two sub-tools:

• bash_code_execution: Run shell commands
• text_editor_code_execution: View, create, and edit files, including writing code

Response format

The code execution tool can return two types of results depending on the operation:

Bash command response

{
  "type": "server_tool_use",
  "id": "srvtoolu_01B3C4D5E6F7G8H9I0J1K2L3",
  "name": "bash_code_execution",
  "input": {
    "command": "ls -la | head -5"
  }
},
{
  "type": "bash_code_execution_tool_result",
  "tool_use_id": "srvtoolu_01B3C4D5E6F7G8H9I0J1K2L3",
  "content": {
    "type": "bash_code_execution_result",
    "stdout": "total 24\ndrwxr-xr-x 2 user user 4096 Jan 1 12:00 .\ndrwxr-xr-x 3 user user 4096 Jan 1 11:00 ..\n-rw-r--r-- 1 user user  220 Jan 1 12:00 data.csv\n-rw-r--r-- 1 user user  180 Jan 1 12:00 config.json",
    "stderr": "",
    "return_code": 0
  }
}

File operation responses

View file:

{
  "type": "server_tool_use",
  "id": "srvtoolu_01C4D5E6F7G8H9I0J1K2L3M4",
  "name": "text_editor_code_execution",
  "input": {
    "command": "view",
    "path": "config.json"
  }
},
{
  "type": "text_editor_code_execution_tool_result",
  "tool_use_id": "srvtoolu_01C4D5E6F7G8H9I0J1K2L3M4",
  "content": {
    "type": "text_editor_code_execution_result",
    "file_type": "text",
    "content": "{\n  \"setting\": \"value\",\n  \"debug\": true\n}",
    "numLines": 4,
    "startLine": 1,
    "totalLines": 4
  }
}

Create file:

{
  "type": "server_tool_use",
  "id": "srvtoolu_01D5E6F7G8H9I0J1K2L3M4N5",
  "name": "text_editor_code_execution",
  "input": {
    "command": "create",
    "path": "new_file.txt",
    "file_text": "Hello, World!"
  }
},
{
  "type": "text_editor_code_execution_tool_result",
  "tool_use_id": "srvtoolu_01D5E6F7G8H9I0J1K2L3M4N5",
  "content": {
    "type": "text_editor_code_execution_result",
    "is_file_update": false
  }
}

Edit file (str_replace):

{
  "type": "server_tool_use",
  "id": "srvtoolu_01E6F7G8H9I0J1K2L3M4N5O6",
  "name": "text_editor_code_execution",
  "input": {
    "command": "str_replace",
    "path": "config.json",
    "old_str": "\"debug\": true",
    "new_str": "\"debug\": false"
  }
},
{
  "type": "text_editor_code_execution_tool_result",
  "tool_use_id": "srvtoolu_01E6F7G8H9I0J1K2L3M4N5O6",
  "content": {
    "type": "text_editor_code_execution_result",
    "oldStart": 3,
    "oldLines": 1,
    "newStart": 3,
    "newLines": 1,
    "lines": ["-  \"debug\": true", "+  \"debug\": false"]
  }
}

Results

All execution results include:

• stdout: Output from successful execution
• stderr: Error messages if execution fails
• return_code: 0 for success, non-zero for failure

Additional fields for file operations:

• View: file_type, content, numLines, startLine, totalLines
• Create: is_file_update (whether file already existed)
• Edit: oldStart, oldLines, newStart, newLines, lines (diff format)

Errors

Each tool type can return specific errors:

Common errors (all tools):

{
  "type": "bash_code_execution_tool_result",
  "tool_use_id": "srvtoolu_01VfmxgZ46TiHbmXgy928hQR",
  "content": {
    "type": "bash_code_execution_tool_result_error",
    "error_code": "unavailable"
  }
}

Error codes by tool type:

pause_turn stop reason

The response may include a pause_turn stop reason, which indicates that the API paused a long-running turn. You may provide the response back as-is in a subsequent request to let Claude continue its turn, or modify the content if you wish to interrupt the conversation.

Containers

The code execution tool runs in a secure, containerized environment designed specifically for code execution, with a higher focus on Python.

Runtime environment

• Python version: 3.11.12
• Operating system: Linux-based container
• Architecture: x86_64 (AMD64)

Resource limits

• Memory: 5GiB RAM
• Disk space: 5GiB workspace storage
• CPU: 1 CPU

Networking and security

• Internet access: Completely disabled for security
• External connections: No outbound network requests permitted
• Sandbox isolation: Full isolation from host system and other containers
• File access: Limited to workspace directory only
• Workspace scoping: Like Files, containers are scoped to the workspace of the API key
• Expiration: Containers expire 30 days after creation

Pre-installed libraries

The sandboxed Python environment includes these commonly used libraries:

• Data Science: pandas, numpy, scipy, scikit-learn, statsmodels
• Visualization: matplotlib, seaborn
• File Processing: pyarrow, openpyxl, xlsxwriter, xlrd, pillow, python-pptx, python-docx, pypdf, pdfplumber, pypdfium2, pdf2image, pdfkit, tabula-py, reportlab[pycairo], Img2pdf
• Math & Computing: sympy, mpmath
• Utilities: tqdm, python-dateutil, pytz, joblib, unzip, unrar, 7zip, bc, rg (ripgrep), fd, sqlite

Container reuse

You can reuse an existing container across multiple API requests by providing the container ID from a previous response. This allows you to maintain created files between requests.

Example

# First request: Create a file with a random number
curl https://api.anthropic.com/v1/messages \
    --header "x-api-key: $ANTHROPIC_API_KEY" \
    --header "anthropic-version: 2023-06-01" \
    --header "content-type: application/json" \
    --data '{
        "model": "claude-opus-4-6",
        "max_tokens": 4096,
        "messages": [{
            "role": "user",
            "content": "Write a file with a random number and save it to \"/tmp/number.txt\""
        }],
        "tools": [{
            "type": "code_execution_20250825",
            "name": "code_execution"
        }]
    }' > response1.json

# Extract container ID from the response (using jq)
CONTAINER_ID=$(jq -r '.container.id' response1.json)

# Second request: Reuse the container to read the file
curl https://api.anthropic.com/v1/messages \
    --header "x-api-key: $ANTHROPIC_API_KEY" \
    --header "anthropic-version: 2023-06-01" \
    --header "content-type: application/json" \
    --data '{
        "container": "'$CONTAINER_ID'",
        "model": "claude-opus-4-6",
        "max_tokens": 4096,
        "messages": [{
            "role": "user",
            "content": "Read the number from \"/tmp/number.txt\" and calculate its square"
        }],
        "tools": [{
            "type": "code_execution_20250825",
            "name": "code_execution"
        }]
    }'

Streaming

With streaming enabled, you'll receive code execution events as they occur:

event: content_block_start
data: {"type": "content_block_start", "index": 1, "content_block": {"type": "server_tool_use", "id": "srvtoolu_xyz789", "name": "code_execution"}}

// Code execution streamed
event: content_block_delta
data: {"type": "content_block_delta", "index": 1, "delta": {"type": "input_json_delta", "partial_json": "{\"code\":\"import pandas as pd\\ndf = pd.read_csv('data.csv')\\nprint(df.head())\"}"}}

// Pause while code executes

// Execution results streamed
event: content_block_start
data: {"type": "content_block_start", "index": 2, "content_block": {"type": "code_execution_tool_result", "tool_use_id": "srvtoolu_xyz789", "content": {"stdout": "   A  B  C\n0  1  2  3\n1  4  5  6", "stderr": ""}}}

Batch requests

You can include the code execution tool in the Messages Batches API. Code execution tool calls through the Messages Batches API are priced the same as those in regular Messages API requests.

Usage and pricing

Code execution is free when used with web search or web fetch. When web_search_20260209 or web_fetch_20260209 is included in your API request, there are no additional charges for code execution tool calls beyond the standard input and output token costs.

When used without these tools, code execution is billed by execution time, tracked separately from token usage:

• Execution time has a minimum of 5 minutes
• Each organization receives 1,550 free hours of usage per month
• Additional usage beyond 1,550 hours is billed at $0.05 per hour, per container
• If files are included in the request, execution time is billed even if the tool is not invoked, due to files being preloaded onto the container

Code execution usage is tracked in the response:

"usage": {
  "input_tokens": 105,
  "output_tokens": 239,
  "server_tool_use": {
    "code_execution_requests": 1
  }
}

Upgrade to latest tool version

By upgrading to code-execution-2025-08-25, you get access to file manipulation and Bash capabilities, including code in multiple languages. There is no price difference.

What's changed

Backward compatibility

• All existing Python code execution continues to work exactly as before
• No changes required to existing Python-only workflows

Upgrade steps

To upgrade, update the tool type in your API requests:

- "type": "code_execution_20250522"
+ "type": "code_execution_20250825"

Review response handling (if parsing responses programmatically):

• The previous blocks for Python execution responses will no longer be sent
• Instead, new response types for Bash and file operations will be sent (see Response Format section)

Programmatic tool calling

The code execution tool powers programmatic tool calling, which allows Claude to write code that calls your custom tools programmatically within the execution container. This enables efficient multi-tool workflows, data filtering before reaching Claude's context, and complex conditional logic.

# Enable programmatic calling for your tools
response = client.messages.create(
    model="claude-opus-4-6",
    max_tokens=4096,
    messages=[
        {"role": "user", "content": "Get weather for 5 cities and find the warmest"}
    ],
    tools=[
        {"type": "code_execution_20250825", "name": "code_execution"},
        {
            "name": "get_weather",
            "description": "Get weather for a city",
            "input_schema": {...},
            "allowed_callers": [
                "code_execution_20250825"
            ],  # Enable programmatic calling
        },
    ],
)

Learn more in the Programmatic tool calling documentation.

Using code execution with Agent Skills

The code execution tool enables Claude to use Agent Skills. Skills are modular capabilities consisting of instructions, scripts, and resources that extend Claude's functionality.

Learn more in the Agent Skills documentation and Agent Skills API guide.