What is the mandatory return format for Python in n8n?

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

How do I access data from previous nodes in the Python node?

The most common way is using _input.all() to get all items, _input.first() for the first item, or _node['Node Name'] to reference a specific node's output.

Can I use external Python libraries like pandas or requests in n8n?

No, n8n Code nodes are restricted to the Python standard library. For HTTP requests, use the native n8n HTTP Request node, and for data analysis, utilize the built-in 'statistics' or 'math' modules.

Why is my webhook data causing a KeyError in Python?

In n8n, webhook data is nested under the 'body' key. Instead of _json['name'], you should use _json['body']['name'] or safer access like _json.get('body', {}).get('name').

n8n Python Code Node Assistant

Name: n8n Python Code Node Assistant
Author: sromeroubisos

bysromeroubisos

0•

Productividad y Flujo de Trabajo

Optimizes Python script development within n8n Code nodes by providing best practices, data access patterns, and syntax guidance.

This skill empowers developers to write effective Python scripts within n8n automation workflows, bridging the gap between n8n's visual logic and Python's data processing capabilities. It provides immediate expert guidance on navigating the specific constraints of the n8n Python environment, such as the lack of external libraries and the mandatory JSON-wrapped return structure. Whether you are performing complex data transformations, filtering arrays using list comprehensions, or conducting statistical analysis with the standard library, this skill ensures your code integrates seamlessly with n8n's architecture.

Características Principales

01Webhook data structure navigation and troubleshooting

020 GitHub stars

03Guided Python (Beta) and Python (Native) mode selection

04Standard library usage patterns for regex, math, and statistics

05Validation of mandatory n8n return formats

06Standardized data access patterns using _input and _json syntax

Casos de Uso

01Performing statistical calculations on workflow data using the Python standard library

02Transforming complex JSON payloads from API responses into structured lists

03Implementing advanced data filtering and validation logic via list comprehensions

Características Principales

01Webhook data structure navigation and troubleshooting

020 GitHub stars

03Guided Python (Beta) and Python (Native) mode selection

04Standard library usage patterns for regex, math, and statistics

05Validation of mandatory n8n return formats

06Standardized data access patterns using _input and _json syntax

Casos de Uso

01Performing statistical calculations on workflow data using the Python standard library

02Transforming complex JSON payloads from API responses into structured lists

03Implementing advanced data filtering and validation logic via list comprehensions