n8n-code-python

name	n8n-code-python
description	Write Python code in n8n Code nodes. Use when writing Python for n8n, using Python libraries, pandas data processing, or preferring Python over JavaScript in workflows. Use when this capability is needed.
metadata	{"author":"fazer-ai"}

n8n Code Python

Expert guidance for writing Python in n8n Code nodes.

Based on n8n-skills by Romuald Członkowski

Python Code Node Basics

n8n supports Python in Code nodes with some differences from JavaScript.

Run Once for All Items

# Access all input items
items = _input.all()

# Process and return
return [{"json": {**item.json, "processed": True}} for item in items]

Run Once for Each Item

# Access current item
data = _input.item.json

# Return single item
return {"json": {**data, "processed": True}}

Accessing Data

Current Node Input

# All items
items = _input.all()

# First item
first = _input.first()

# Current item (in "each item" mode)
current = _input.item

# JSON data
data = _input.first().json

Execution Context

# Note: Limited compared to JavaScript
# Access via items or hardcoded values

Common Patterns

Transform All Items

items = _input.all()

return [
    {
        "json": {
            "id": item.json["id"],
            "name": item.json["name"].upper(),
            "processed": True
        }
    }
    for item in items
]

Filter Items

items = _input.all()

return [
    {"json": item.json}
    for item in items
    if item.json.get("status") == "active"
]

Aggregate Data

items = _input.all()

total = sum(item.json.get("amount", 0) for item in items)
count = len(items)

return [{
    "json": {
        "total": total,
        "count": count,
        "average": total / count if count > 0 else 0
    }
}]

Group By

from collections import defaultdict

items = _input.all()
grouped = defaultdict(list)

for item in items:
    key = item.json.get("category", "unknown")
    grouped[key].append(item.json)

return [
    {"json": {"category": k, "items": v, "count": len(v)}}
    for k, v in grouped.items()
]

JSON Parsing

import json

items = _input.all()

return [
    {
        "json": {
            "parsed": json.loads(item.json.get("rawData", "{}"))
        }
    }
    for item in items
]

Error Handling

import json

items = _input.all()
results = []

for item in items:
    try:
        parsed = json.loads(item.json.get("rawData", "{}"))
        results.append({"json": {"success": True, "data": parsed}})
    except Exception as e:
        results.append({"json": {"success": False, "error": str(e)}})

return results

Date/Time Handling

from datetime import datetime, timedelta

# Current time
now = datetime.now()

# Parse ISO date
date = datetime.fromisoformat("2024-01-15T10:30:00")

# Format
formatted = now.strftime("%Y-%m-%d %H:%M:%S")

# Add/subtract
next_week = now + timedelta(days=7)
yesterday = now - timedelta(days=1)

# Return with dates
return [{
    "json": {
        "now": now.isoformat(),
        "formatted": formatted,
        "nextWeek": next_week.isoformat()
    }
}]

Working with Pandas

⚠️ Note: pandas may not be available in all n8n installations. Check your environment.

import pandas as pd

items = _input.all()

# Convert to DataFrame
data = [item.json for item in items]
df = pd.DataFrame(data)

# Process with pandas
df["total"] = df["price"] * df["quantity"]
df_grouped = df.groupby("category").agg({"total": "sum"}).reset_index()

# Convert back to n8n format
return [{"json": row} for row in df_grouped.to_dict(orient="records")]

Webhook Data Access

CRITICAL: Webhook data is under .body:

# ❌ Wrong
message = _input.first().json.get("message")

# ✅ Correct - webhook data is in body
body = _input.first().json.get("body", {})
message = body.get("message")
headers = _input.first().json.get("headers", {})
query = _input.first().json.get("query", {})

Available Libraries

Standard Python libraries typically available:

• json - JSON parsing
• datetime - Date/time handling
• re - Regular expressions
• collections - Data structures
• math - Mathematical functions
• base64 - Encoding
• hashlib - Hashing

import json
import re
import hashlib
from datetime import datetime
from collections import defaultdict

# Use hashlib
hash_value = hashlib.sha256(data.encode()).hexdigest()

# Use regex
matches = re.findall(r"\d+", text)

Common Mistakes

1. Wrong Return Format

# ❌ Wrong - must return list of dicts with "json" key
return {"name": "John"}

# ✅ Correct
return [{"json": {"name": "John"}}]

2. Using dot notation for dict access

# ❌ Wrong - Python dicts use brackets
name = item.json.name

# ✅ Correct
name = item.json["name"]
# or safer:
name = item.json.get("name", "default")

3. Not Handling Missing Keys

# ❌ Wrong - KeyError if missing
value = item.json["optional_field"]

# ✅ Correct
value = item.json.get("optional_field", "default")

4. Returning dict instead of list

# ❌ Wrong in "all items" mode
return {"json": {"result": "data"}}

# ✅ Correct - always return list
return [{"json": {"result": "data"}}]

Python vs JavaScript in n8n

Feature	Python	JavaScript
Input access	_input	$input
Node access	Limited	$node["Name"]
Env vars	Limited	$env.VAR
Async/await	No	Yes
Libraries	Standard + limited	Luxon, Lodash

Best Practices

1. Always return list of {"json": {...}} dicts
2. Use .get() for safe dict access
3. Handle exceptions with try/except
4. Import at top of code block
5. Test with simple data first
6. Access webhook data via .body

Quick Reference

Need	Code
All items	_input.all()
First item	_input.first()
Current item	_input.item (each mode)
Item JSON	item.json
Dict value	item.json.get("key", default)
Webhook body	item.json.get("body", {})
Return item	{"json": {...}}
Return many	[{"json": {...}}, ...]

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_{Based on n8n-skills by Romuald Członkowski • Adapted for Moltbot by fazer.ai}

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Source: fazer-ai/moltbot-skill-n8n — distributed by TomeVault.