How do I access data from a Webhook node in Python?

Webhook data is nested under the body property. Use _json['body'] or safer access like _json.get('body', {}) to retrieve your payload.

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

No, n8n Python nodes are limited to the Python standard library. For HTTP requests, use the native n8n HTTP Request node or switch to JavaScript which has built-in helpers.

What is the mandatory return format for n8n Python code?

You must always return a list of dictionaries where each dictionary contains a 'json' key, for example: return [{'json': {'my_data': 'value'}}].

When should I use Python instead of JavaScript in n8n?

JavaScript is recommended for 95% of cases due to better helper integration. Use Python only for specific standard library functions (like statistics) or if you have complex logic significantly easier to write in Python syntax.

n8n Python Code Expert

Name: n8n Python Code Expert
Author: thanhtoan105

bythanhtoan105

•

Productivity & Workflow

Provides expert guidance and implementation patterns for writing efficient Python code within n8n Code nodes.

About

This skill equips Claude with the specialized knowledge required to write production-ready Python code for n8n automation workflows, navigating the platform's unique architectural constraints and syntax helpers. It helps developers correctly use data access patterns like _input.all() and _node, ensures adherence to mandatory return formats, and provides standard-library workarounds for the platform's lack of external package support. Whether performing complex data transformations, statistical analysis, or custom regex filtering, this skill ensures Python scripts are optimized for the n8n execution environment.

Key Features

Expert n8n-specific Python syntax guidance for _input, _json, and _node helpers
Validation of mandatory return formats to prevent workflow execution failures
1 GitHub stars
Guidance on choosing between 'Run Once for All Items' and 'Run Once for Each Item' modes
Standard library pattern library for regex, statistics, and date manipulation
Error prevention for common pitfalls like nested webhook data structures

Use Cases

Running statistical analysis on workflow data using the Python statistics module
Cleaning and validating large datasets before sending them to external APIs or databases
Performing complex data aggregation and filtering using Python list comprehensions

About

Key Features

Expert n8n-specific Python syntax guidance for _input, _json, and _node helpers
Validation of mandatory return formats to prevent workflow execution failures
1 GitHub stars
Guidance on choosing between 'Run Once for All Items' and 'Run Once for Each Item' modes
Standard library pattern library for regex, statistics, and date manipulation
Error prevention for common pitfalls like nested webhook data structures

Use Cases

Running statistical analysis on workflow data using the Python statistics module
Cleaning and validating large datasets before sending them to external APIs or databases
Performing complex data aggregation and filtering using Python list comprehensions