Python Skill

Python Code Execution Tool

Execute Python code for calculations, data processing, and automation tasks.

How It Works

This skill provides instructions for the Python Executor tool node. Connect the Python Executor node to Zeenie's input-tools handle to enable Python code execution.

python_code Tool

Execute Python code and return results.

Schema Fields

Available Libraries

All modules below are pre-injected as names in the sandbox. Do not use import statements — they will fail (ImportError: __import__ not found). Reference each name directly.

Built-in Variables

Output Methods

1. Set output variable: Returns structured data to the workflow
2. Use print(): Captured as console output

Examples

Basic calculation:

{
  "code": "result = 25 * 4 + 10\nprint(f'Result: {result}')\noutput = result"
}

Calculate tip:

{
  "code": "bill = 85.50\ntip_percent = 15\ntip = bill * (tip_percent / 100)\ntotal = bill + tip\nprint(f'Tip: ${tip:.2f}')\nprint(f'Total: ${total:.2f}')\noutput = {'tip': tip, 'total': total}"
}

Generate random numbers:

{
  "code": "numbers = [random.randint(1, 100) for _ in range(5)]\nprint(f'Random numbers: {numbers}')\noutput = numbers"
}

Date calculations:

{
  "code": "today = datetime.datetime.now()\nfuture = today + timedelta(days=30)\nresult = future.strftime('%Y-%m-%d')\nprint(f'30 days from now: {result}')\noutput = result"
}

Process data:

{
  "code": "data = input_data.get('numbers', [1, 2, 3, 4, 5])\ntotal = sum(data)\naverage = total / len(data)\nprint(f'Total: {total}, Average: {average}')\noutput = {'total': total, 'average': average}"
}

Parse JSON:

{
  "code": "json_str = '{\"name\": \"John\", \"age\": 30}'\ndata = json.loads(json_str)\nprint(f'Name: {data[\"name\"]}')\noutput = data"
}

Count items:

{
  "code": "items = ['apple', 'banana', 'apple', 'cherry', 'banana', 'apple']\ncounts = dict(Counter(items))\nprint(f'Counts: {counts}')\noutput = counts"
}

Text processing:

{
  "code": "text = 'Contact: john@example.com or jane@test.org'\nemails = re.findall(r'\\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\\.[A-Z|a-z]{2,}\\b', text)\nprint(f'Found emails: {emails}')\noutput = emails"
}

Response Format

Success:

{
  "success": true,
  "result": {"tip": 12.825, "total": 98.325},
  "output": "Tip: $12.83\nTotal: $98.33"
}

Error:

{
  "error": "name 'undefined_var' is not defined"
}

Use Cases

Guidelines

1. Always set output: This returns data to the workflow
2. Use print() for debugging: Output is captured and returned
3. Keep code focused: One task per execution
4. Handle errors: Use try/except for robust code
5. No network access: Use http-skill for web requests
6. No file system access: Restricted to safe operations
7. Timeout: Default 30 seconds max execution time

Security Restrictions

• No network/socket operations
• No file system access outside designated areas
• No subprocess/shell commands
• Limited execution time (30 seconds)
• Sandboxed environment

Setup Requirements

1. Connect the Python Executor node to Zeenie's input-tools handle
2. Python must be installed on the server