python-skill

name	python-skill
description	Execute Python code for calculations, data processing, and automation. Access to math, json, datetime, collections, and more.
allowed-tools	python_executor
metadata	{"author":"opencompany","version":"1.0","category":"code"}

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

Field	Type	Required	Description
code	string	Yes	Python code to execute

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.

Name	Reference Style	Description
math	math.sqrt(2)	Mathematical functions
json	json.loads(s) / json.dumps(d)	JSON encoding/decoding
datetime	datetime.datetime.now() (the module)	Date/time module
timedelta	timedelta(days=30)	Duration class (already unwrapped)
re	re.findall(pat, text)	Regular expressions
random	random.randint(1, 10)	Random number generation
Counter	Counter(items)	Count hashable objects (already unwrapped)
defaultdict	defaultdict(list)	Dictionary with defaults (already unwrapped)

Built-in Variables

Variable	Description
input_data	Data from connected workflow nodes (dict)
output	Set this to return a result

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: [e-mail] or [e-mail]'\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

Use Case	Approach
Math calculations	Use math library functions
Date/time operations	Use datetime and timedelta
Data analysis	Use list comprehensions, sum, len
Random generation	Use random library
Text parsing	Use re regular expressions
JSON manipulation	Use json.loads() and json.dumps()
Counting	Use Counter from collections

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