Can I use external libraries like Pandas or Requests in n8n?

No, n8n Code nodes are limited to the Python standard library. You should use the HTTP Request node for API calls and standard library modules like statistics for data analysis.

How do I access webhook data in an n8n Python node?

Webhook data is nested under the 'body' key. You should access it using _json.get('body', {}) to avoid KeyErrors.

Why is my n8n Python node returning an error even if the logic is correct?

The most common reason is the return format. n8n requires a specific list of dictionaries format: return [{"json": {...}}]. Even a single result must be wrapped in a list and a 'json' key.

Should I use JavaScript or Python in n8n?

n8n recommends JavaScript for 95% of use cases because it has better helper functions and documentation. Use Python only for specific standard library needs or if you are significantly more comfortable with its syntax.

n8n Python Code Expert

Name: n8n Python Code Expert
Author: Gingi892

byGingi892

Productivity & Workflow

Provides expert guidance and implementation patterns for writing Python scripts within n8n workflow Code nodes.

About

This skill equips Claude with specialized knowledge for writing Python in n8n, ensuring scripts follow the platform's unique execution environment rules. It helps developers master data access patterns like _input and _node, enforce mandatory return structures, and navigate the constraints of the Python standard library without external packages. Whether you are performing complex data transformations or statistical analysis, this skill ensures your n8n Python nodes are efficient, bug-free, and properly integrated into your automation workflows.

Key Features

Validation of the mandatory [{"json": ...}] return format
Troubleshooting for common n8n-specific Python errors and limitations
0 GitHub stars
Guidance on using the Python standard library for complex transformations
Correct data access patterns for _input, _json, and _node helpers
Expert boilerplate for Python (Beta) and Python (Native) modes

Use Cases

Processing complex string data using Python's advanced regex capabilities
Performing statistical analysis using the built-in statistics and math modules
Transforming large datasets using Python list comprehensions and filtering

About

Key Features

Validation of the mandatory [{"json": ...}] return format
Troubleshooting for common n8n-specific Python errors and limitations
0 GitHub stars
Guidance on using the Python standard library for complex transformations
Correct data access patterns for _input, _json, and _node helpers
Expert boilerplate for Python (Beta) and Python (Native) modes

Use Cases

Processing complex string data using Python's advanced regex capabilities
Performing statistical analysis using the built-in statistics and math modules
Transforming large datasets using Python list comprehensions and filtering