gh-czlonkowski-n8n-skills/skills/n8n-code-python

n8n Code Python Skill

Expert guidance for writing Python code in n8n Code nodes.

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⚠️ Important: JavaScript First

Use JavaScript for 95% of use cases.

Python in n8n has NO external libraries (no requests, pandas, numpy).

When to use Python:

• You have complex Python-specific logic
• You need Python's standard library features
• You're more comfortable with Python than JavaScript

When to use JavaScript (recommended):

• HTTP requests ($helpers.httpRequest available)
• Date/time operations (Luxon library included)
• Most data transformations
• When in doubt

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What This Skill Teaches

Core Concepts

1. Critical Limitation: No external libraries
2. Data Access: _input.all(), _input.first(), _input.item
3. Webhook Gotcha: Data is under _json["body"]
4. Return Format: Must return [{"json": {...}}]
5. Standard Library: json, datetime, re, base64, hashlib, etc.

Top 5 Error Prevention

This skill emphasizes error prevention:

1. ModuleNotFoundError (trying to import external libraries)
2. Empty code / missing return
3. KeyError (dictionary access without .get())
4. IndexError (list access without bounds checking)
5. Incorrect return format

These 5 errors are the most common in Python Code nodes.

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Skill Activation

This skill activates when you:

• Write Python in Code nodes
• Ask about Python limitations
• Need to know available standard library
• Troubleshoot Python Code node errors
• Work with Python data structures

Example queries:

• "Can I use pandas in Python Code node?"
• "How do I access webhook data in Python?"
• "What Python libraries are available?"
• "Write Python code to process JSON"
• "Why is requests module not found?"

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File Structure

SKILL.md (719 lines)

Quick start and overview

• When to use Python vs JavaScript
• Critical limitation (no external libraries)
• Mode selection (All Items vs Each Item)
• Data access overview
• Return format requirements
• Standard library overview

DATA_ACCESS.md (703 lines)

Complete data access patterns

• _input.all() - Process all items
• _input.first() - Get first item
• _input.item - Current item (Each Item mode)
• _node["Name"] - Reference other nodes
• Webhook body structure (critical gotcha!)
• Pattern selection guide

STANDARD_LIBRARY.md (850 lines)

Available Python modules

• json - JSON parsing
• datetime - Date/time operations
• re - Regular expressions
• base64 - Encoding/decoding
• hashlib - Hashing
• urllib.parse - URL operations
• math, random, statistics
• What's NOT available (requests, pandas, numpy)
• Workarounds for missing libraries

COMMON_PATTERNS.md (895 lines)

10 production-tested patterns

1. Multi-source data aggregation
2. Regex-based filtering
3. Markdown to structured data
4. JSON object comparison
5. CRM data transformation
6. Release notes processing
7. Array transformation
8. Dictionary lookup
9. Top N filtering
10. String aggregation

ERROR_PATTERNS.md (730 lines)

Top 5 errors with solutions

1. ModuleNotFoundError (external libraries)
2. Empty code / missing return
3. KeyError (dictionary access)
4. IndexError (list access)
5. Incorrect return format

• Error prevention checklist
• Quick fix reference
• Testing patterns

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Integration with Other Skills

This skill works with:

n8n Expression Syntax

• Python uses code syntax, not {{}} expressions
• Data access patterns differ ($ vs _)

n8n MCP Tools Expert

• Use MCP tools to validate Code node configurations
• Check node setup with get_node_essentials

n8n Workflow Patterns

• Code nodes fit into larger workflow patterns
• Often used after HTTP Request or Webhook nodes

n8n Code JavaScript

• Compare Python vs JavaScript approaches
• Understand when to use which language
• JavaScript recommended for 95% of cases

n8n Node Configuration

• Configure Code node mode (All Items vs Each Item)
• Set up proper connections

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Success Metrics

After using this skill, you should be able to:

• Know the limitation: Python has NO external libraries
• Choose language: JavaScript for 95% of cases, Python when needed
• Access data: Use _input.all(), _input.first(), _input.item
• Handle webhooks: Access data via _json["body"]
• Return properly: Always return [{"json": {...}}]
• Avoid KeyError: Use .get() for dictionary access
• Use standard library: Know what's available (json, datetime, re, etc.)
• Prevent errors: Avoid top 5 common errors
• Choose alternatives: Use n8n nodes when libraries needed
• Write production code: Use proven patterns

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Quick Reference

Data Access

all_items = _input.all()
first_item = _input.first()
current_item = _input.item  # Each Item mode only
other_node = _node["NodeName"]

Webhook Data

webhook = _input.first()["json"]
body = webhook.get("body", {})
name = body.get("name")

Safe Dictionary Access

# ✅ Use .get() with defaults
value = data.get("field", "default")

# ❌ Risky - may raise KeyError
value = data["field"]

Return Format

# ✅ Correct format
return [{"json": {"result": "success"}}]

# ❌ Wrong - plain dict
return {"result": "success"}

Standard Library

# ✅ Available
import json
import datetime
import re
import base64
import hashlib

# ❌ NOT available
import requests  # ModuleNotFoundError!
import pandas    # ModuleNotFoundError!
import numpy     # ModuleNotFoundError!

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Common Use Cases

Use Case 1: Process Webhook Data

webhook = _input.first()["json"]
body = webhook.get("body", {})

return [{
    "json": {
        "name": body.get("name"),
        "email": body.get("email"),
        "processed": True
    }
}]

Use Case 2: Filter and Transform

all_items = _input.all()

active = [
    {"json": {**item["json"], "filtered": True}}
    for item in all_items
    if item["json"].get("status") == "active"
]

return active

Use Case 3: Aggregate Statistics

import statistics

all_items = _input.all()
amounts = [item["json"].get("amount", 0) for item in all_items]

return [{
    "json": {
        "total": sum(amounts),
        "average": statistics.mean(amounts) if amounts else 0,
        "count": len(amounts)
    }
}]

Use Case 4: Parse JSON String

import json

data = _input.first()["json"]["body"]
json_string = data.get("payload", "{}")

try:
    parsed = json.loads(json_string)
    return [{"json": parsed}]
except json.JSONDecodeError:
    return [{"json": {"error": "Invalid JSON"}}]

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Limitations and Workarounds

Limitation 1: No HTTP Requests Library

Problem: No requests library Workaround: Use HTTP Request node or JavaScript

Limitation 2: No Data Analysis Library

Problem: No pandas or numpy Workaround: Use list comprehensions and standard library

Limitation 3: No Database Drivers

Problem: No psycopg2, pymongo, etc. Workaround: Use n8n database nodes (Postgres, MySQL, MongoDB)

Limitation 4: No Web Scraping

Problem: No beautifulsoup4 or selenium Workaround: Use HTML Extract node

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Best Practices

1. Use JavaScript for most cases (95% recommendation)
2. Use .get() for dictionaries (avoid KeyError)
3. Check lengths before indexing (avoid IndexError)
4. Always return proper format: [{"json": {...}}]
5. Access webhook data via ["body"]
6. Use standard library only (no external imports)
7. Handle empty input (check if items:)
8. Test both modes (All Items and Each Item)

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When Python is the Right Choice

Use Python when:

• Complex text processing (re module)
• Mathematical calculations (math, statistics)
• Date/time manipulation (datetime)
• Cryptographic operations (hashlib)
• You have existing Python logic to reuse
• Team is more comfortable with Python

Use JavaScript instead when:

• Making HTTP requests
• Working with dates (Luxon included)
• Most data transformations
• When in doubt

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Learning Path

Beginner:

1. Read SKILL.md - Understand the limitation
2. Try DATA_ACCESS.md examples - Learn _input patterns
3. Practice safe dictionary access with .get()

Intermediate: 4. Study STANDARD_LIBRARY.md - Know what's available 5. Try COMMON_PATTERNS.md examples - Use proven patterns 6. Learn ERROR_PATTERNS.md - Avoid common mistakes

Advanced: 7. Combine multiple patterns 8. Use standard library effectively 9. Know when to switch to JavaScript 10. Write production-ready code

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Support

Questions?

• Check ERROR_PATTERNS.md for common issues
• Review COMMON_PATTERNS.md for examples
• Consider using JavaScript instead

Related Skills:

• n8n Code JavaScript - Alternative (recommended for 95% of cases)
• n8n Expression Syntax - For {{}} expressions in other nodes
• n8n Workflow Patterns - Bigger picture workflow design

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Version

Version: 1.0.0 Status: Production Ready Compatibility: n8n Code node (Python mode)

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Credits

Part of the n8n-skills project.

Conceived by Romuald Członkowski

• Website: www.aiadvisors.pl/en
• Part of n8n-mcp project

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Remember: JavaScript is recommended for 95% of use cases. Use Python only when you specifically need Python's standard library features.