Python Code Node (Beta)
Expert guidance for writing Python code in n8n Code nodes.
⚠️ Important: JavaScript First
Recommendation: Use JavaScript for 95% of use cases. Only use Python when:
- You need specific Python standard library functions
- You're significantly more comfortable with Python syntax
- You're doing data transformations better suited to Python
Why JavaScript is preferred:
- Full n8n helper functions ($helpers.httpRequest, etc.)
- Luxon DateTime library for advanced date/time operations
- No external library limitations
- Better n8n documentation and community support
Quick Start
items = _input.all()
processed = []
for item in items:
processed.append({
"json": {
**item["json"],
"processed": True,
"timestamp": datetime.now().isoformat()
}
})
return processed
Essential Rules
- Consider JavaScript first - Use Python only when necessary
- Access data:
_input.all(), _input.first(), or _input.item
- CRITICAL: Must return
[{"json": {...}}] format
- CRITICAL: Webhook data is under
_json["body"] (not _json directly)
- CRITICAL LIMITATION: No external libraries (no requests, pandas, numpy)
- Standard library only: json, datetime, re, base64, hashlib, urllib.parse, math, random, statistics
Mode Selection Guide
Same as JavaScript - choose based on your use case:
Run Once for All Items (Recommended - Default)
Use this mode for: 95% of use cases
- How it works: Code executes once regardless of input count
- Data access:
_input.all() or _items array (Native mode)
- Best for: Aggregation, filtering, batch processing, transformations
- Performance: Faster for multiple items (single execution)
all_items = _input.all()
total = sum(item["json"].get("amount", 0) for item in all_items)
return [{
"json": {
"total": total,
"count": len(all_items),
"average": total / len(all_items) if all_items else 0
}
}]
Run Once for Each Item
Use this mode for: Specialized cases only
- How it works: Code executes separately for each input item
- Data access:
_input.item or _item (Native mode)
- Best for: Item-specific logic, independent operations, per-item validation
- Performance: Slower for large datasets (multiple executions)
item = _input.item
return [{
"json": {
**item["json"],
"processed": True,
"processed_at": datetime.now().isoformat()
}
}]
Python Modes: Beta vs Native
n8n offers two Python execution modes:
Python (Beta) - Recommended
- Use:
_input, _json, _node helper syntax
- Best for: Most Python use cases
- Helpers available:
_now, _today, _jmespath()
- Import:
from datetime import datetime
items = _input.all()
now = _now
return [{
"json": {
"count": len(items),
"timestamp": now.isoformat()
}
}]
Python (Native) (Beta)
- Use:
_items, _item variables only
- No helpers: No
_input, _now, etc.
- More limited: Standard Python only
- Use when: Need pure Python without n8n helpers
processed = []
for item in _items:
processed.append({
"json": {
"id": item["json"].get("id"),
"processed": True
}
})
return processed
Recommendation: Use Python (Beta) for better n8n integration.
Data Access Patterns
Pattern 1: _input.all() - Most Common
Use when: Processing arrays, batch operations, aggregations
all_items = _input.all()
valid = [item for item in all_items if item["json"].get("status") == "active"]
processed = []
for item in valid:
processed.append({
"json": {
"id": item["json"]["id"],
"name": item["json"]["name"]
}
})
return processed
Pattern 2: _input.first() - Very Common
Use when: Working with single objects, API responses
first_item = _input.first()
data = first_item["json"]
return [{
"json": {
"result": process_data(data),
"processed_at": datetime.now().isoformat()
}
}]
Pattern 3: _input.item - Each Item Mode Only
Use when: In "Run Once for Each Item" mode
current_item = _input.item
return [{
"json": {
**current_item["json"],
"item_processed": True
}
}]
Pattern 4: _node - Reference Other Nodes
Use when: Need data from specific nodes in workflow
webhook_data = _node["Webhook"]["json"]
http_data = _node["HTTP Request"]["json"]
return [{
"json": {
"combined": {
"webhook": webhook_data,
"api": http_data
}
}
}]
See: DATA_ACCESS.md for comprehensive guide
Critical: Webhook Data Structure
MOST COMMON MISTAKE: Webhook data is nested under ["body"]
name = _json["name"]
email = _json["email"]
name = _json["body"]["name"]
email = _json["body"]["email"]
webhook_data = _json.get("body", {
