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feat: Complete Skill #7 - n8n Code Python

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Implements comprehensive Python Code node guidance with critical focus on "NO external libraries" limitation.

## Skill #7 - n8n Code Python

**Critical Message**: Use JavaScript for 95% of use cases.

Python in n8n has NO external libraries (no requests, pandas, numpy).

### Files Created

**Core Skill Files (6 files, 4,205 lines total)**:

1. **SKILL.md** (748 lines)
   - When to use Python vs JavaScript (95% JavaScript recommendation)
   - Critical limitation: NO external libraries
   - Mode selection (All Items vs Each Item)
   - Data access overview (_input, _json, _node)
   - Return format requirements
   - Standard library overview

2. **DATA_ACCESS.md** (702 lines)
   - _input.all() - Process all items
   - _input.first() - Get first item
   - _input.item - Current item (Each Item mode only)
   - _node["Name"] - Reference other nodes
   - Webhook body structure (data under ["body"])
   - Pattern selection guide
   - Python vs JavaScript comparison

3. **STANDARD_LIBRARY.md** (974 lines)
   - Complete reference for available modules
   - json - JSON parsing and generation
   - datetime - Date/time operations
   - re - Regular expressions
   - base64 - Encoding/decoding
   - hashlib - Hashing (MD5, SHA256)
   - urllib.parse - URL operations
   - math, random, statistics
   - What's NOT available (requests, pandas, numpy, etc.)
   - Workarounds for missing libraries

4. **COMMON_PATTERNS.md** (794 lines)
   - 10 production-tested Python patterns
   - Multi-source data aggregation
   - Regex-based filtering
   - Markdown to structured data
   - JSON object comparison
   - CRM data transformation
   - Release notes processing
   - Array transformation
   - Dictionary lookup
   - Top N filtering
   - String aggregation
   - Python vs JavaScript pattern comparison

5. **ERROR_PATTERNS.md** (601 lines)
   - Top 5 Python-specific errors with solutions
   - Error #1: ModuleNotFoundError (THE critical Python error)
   - Error #2: Empty code / missing return
   - Error #3: KeyError (use .get() instead)
   - Error #4: IndexError (check bounds first)
   - Error #5: Incorrect return format
   - Error prevention checklist
   - Quick fix reference table
   - Testing patterns

6. **README.md** (386 lines)
   - Skill metadata and activation triggers
   - "JavaScript First" recommendation prominent
   - What this skill teaches
   - File structure overview
   - Integration with other skills
   - Success metrics checklist
   - Quick reference guide
   - Common use cases
   - Limitations and workarounds
   - Best practices

**Evaluations (5 scenarios)**:

1. **eval-001-module-import-error.json**
   - Tests understanding of external library limitation
   - Scenario: ModuleNotFoundError with requests
   - Expected: Recommend JavaScript or HTTP Request node

2. **eval-002-dictionary-keyerror.json**
   - Tests safe dictionary access with .get()
   - Scenario: KeyError when accessing missing field
   - Expected: Use .get() with default values

3. **eval-003-webhook-body-gotcha.json**
   - Tests webhook data under ["body"] understanding
   - Scenario: KeyError when accessing webhook data directly
   - Expected: Access via data.get("body", {})

4. **eval-004-return-format-error.json**
   - Tests proper return format requirement
   - Scenario: Returning plain dict instead of array
   - Expected: Return [{"json": {...}}]

5. **eval-005-standard-library-usage.json**
   - Tests knowledge of available modules
   - Scenario: What modules for JSON, hashing, dates, regex
   - Expected: json, hashlib, datetime, re (standard library only)

### Key Features

**Critical Limitations Emphasized**:
- NO external libraries (no requests, pandas, numpy)
- JavaScript recommended for 95% of use cases
- Only standard library available
- ModuleNotFoundError is #1 Python error

**Python-Specific Syntax**:
- Underscore prefix: _input, _json, _node (vs $ in JavaScript)
- Dictionary access: _json["body"]["field"] (vs dot notation)
- Safe access: .get() method with defaults

**Complete Standard Library Coverage**:
- 15+ modules documented with examples
- json, datetime, re, base64, hashlib, urllib.parse
- math, random, statistics, collections
- Clear list of what's NOT available
- Workarounds for missing functionality

**Production Patterns**:
- 10 tested patterns adapted from JavaScript
- Python-specific implementations
- List comprehensions and dictionary operations
- Standard library usage examples

**Error Prevention Focus**:
- Top 5 errors cover majority of failures
- ModuleNotFoundError prominently featured
- Safe dictionary access (.get())
- Proper return format emphasized
- Error prevention checklist

### Integration

Works seamlessly with:
- **n8n Code JavaScript**: Compare approaches, know when to use which
- **n8n Expression Syntax**: Different from {{}} expressions
- **n8n MCP Tools Expert**: Validate Code node configurations
- **n8n Workflow Patterns**: Code nodes in larger workflows
- **n8n Node Configuration**: Configure mode and connections

### Statistics

- **6 skill files**: 4,205 lines total
- **5 evaluations**: Cover critical Python scenarios
- **10 patterns**: Production-tested Python code
- **15+ modules**: Standard library coverage
- **5 top errors**: Prevention and solutions

### Design Principles

1. **JavaScript First**: 95% recommendation throughout
2. **Critical Limitation**: NO external libraries emphasized everywhere
3. **Safe Patterns**: .get() for dicts, bounds checking for lists
4. **Proper Format**: [{"json": {...}}] return format
5. **Standard Library**: Complete reference with examples
6. **Error Prevention**: Top 5 errors with solutions

### Recommendation

**Use JavaScript Code node for 95% of use cases.**

Use Python only when:
- Complex Python-specific logic required
- Python standard library features needed
- Team more comfortable with Python than JavaScript

For HTTP requests, date operations, and most transformations → Use JavaScript.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Conceived by Romuald Członkowski - https://www.aiadvisors.pl/en
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---
name: n8n-code-python
description: Write Python code in n8n Code nodes. Use when writing Python in n8n, using _input/_json/_node syntax, working with standard library, or need to understand Python limitations in n8n Code nodes.
---
# 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
```python
# Basic template for Python Code nodes
items = _input.all()
# Process data
processed = []
for item in items:
processed.append({
"json": {
**item["json"],
"processed": True,
"timestamp": datetime.now().isoformat()
}
})
return processed
```
### Essential Rules
1. **Consider JavaScript first** - Use Python only when necessary
2. **Access data**: `_input.all()`, `_input.first()`, or `_input.item`
3. **CRITICAL**: Must return `[{"json": {...}}]` format
4. **CRITICAL**: Webhook data is under `_json["body"]` (not `_json` directly)
5. **CRITICAL LIMITATION**: **No external libraries** (no requests, pandas, numpy)
6. **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)
```python
# Example: Calculate total from all items
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)
```python
# Example: Add processing timestamp to each item
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`
```python
# Python (Beta) example
items = _input.all()
now = _now # Built-in datetime object
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
```python
# Python (Native) example
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
```python
# Get all items from previous node
all_items = _input.all()
# Filter, transform as needed
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
```python
# Get first item only
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
```python
# Current item in loop (Each Item mode only)
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
```python
# Get output from specific node
webhook_data = _node["Webhook"]["json"]
http_data = _node["HTTP Request"]["json"]
return [{
"json": {
"combined": {
"webhook": webhook_data,
"api": http_data
}
}
}]
```
**See**: [DATA_ACCESS.md](DATA_ACCESS.md) for comprehensive guide
---
## Critical: Webhook Data Structure
**MOST COMMON MISTAKE**: Webhook data is nested under `["body"]`
```python
# ❌ WRONG - Will raise KeyError
name = _json["name"]
email = _json["email"]
# ✅ CORRECT - Webhook data is under ["body"]
name = _json["body"]["name"]
email = _json["body"]["email"]
# ✅ SAFER - Use .get() for safe access
webhook_data = _json.get("body", {})
name = webhook_data.get("name")
```
**Why**: Webhook node wraps all request data under `body` property. This includes POST data, query parameters, and JSON payloads.
**See**: [DATA_ACCESS.md](DATA_ACCESS.md) for full webhook structure details
---
## Return Format Requirements
**CRITICAL RULE**: Always return list of dictionaries with `"json"` key
### Correct Return Formats
```python
# ✅ Single result
return [{
"json": {
"field1": value1,
"field2": value2
}
}]
# ✅ Multiple results
return [
{"json": {"id": 1, "data": "first"}},
{"json": {"id": 2, "data": "second"}}
]
# ✅ List comprehension
transformed = [
{"json": {"id": item["json"]["id"], "processed": True}}
for item in _input.all()
if item["json"].get("valid")
]
return transformed
# ✅ Empty result (when no data to return)
return []
# ✅ Conditional return
if should_process:
return [{"json": processed_data}]
else:
return []
```
### Incorrect Return Formats
```python
# ❌ WRONG: Dictionary without list wrapper
return {
"json": {"field": value}
}
# ❌ WRONG: List without json wrapper
return [{"field": value}]
# ❌ WRONG: Plain string
return "processed"
# ❌ WRONG: Incomplete structure
return [{"data": value}] # Should be {"json": value}
```
**Why it matters**: Next nodes expect list format. Incorrect format causes workflow execution to fail.
**See**: [ERROR_PATTERNS.md](ERROR_PATTERNS.md) #2 for detailed error solutions
---
## Critical Limitation: No External Libraries
**MOST IMPORTANT PYTHON LIMITATION**: Cannot import external packages
### What's NOT Available
```python
# ❌ NOT AVAILABLE - Will raise ModuleNotFoundError
import requests # ❌ No
import pandas # ❌ No
import numpy # ❌ No
import scipy # ❌ No
from bs4 import BeautifulSoup # ❌ No
import lxml # ❌ No
```
### What IS Available (Standard Library)
```python
# ✅ AVAILABLE - Standard library only
import json # ✅ JSON parsing
import datetime # ✅ Date/time operations
import re # ✅ Regular expressions
import base64 # ✅ Base64 encoding/decoding
import hashlib # ✅ Hashing functions
import urllib.parse # ✅ URL parsing
import math # ✅ Math functions
import random # ✅ Random numbers
import statistics # ✅ Statistical functions
```
### Workarounds
**Need HTTP requests?**
- ✅ Use **HTTP Request node** before Code node
- ✅ Or switch to **JavaScript** and use `$helpers.httpRequest()`
**Need data analysis (pandas/numpy)?**
- ✅ Use Python **statistics** module for basic stats
- ✅ Or switch to **JavaScript** for most operations
- ✅ Manual calculations with lists and dictionaries
**Need web scraping (BeautifulSoup)?**
- ✅ Use **HTTP Request node** + **HTML Extract node**
- ✅ Or switch to **JavaScript** with regex/string methods
**See**: [STANDARD_LIBRARY.md](STANDARD_LIBRARY.md) for complete reference
---
## Common Patterns Overview
Based on production workflows, here are the most useful Python patterns:
### 1. Data Transformation
Transform all items with list comprehensions
```python
items = _input.all()
return [
{
"json": {
"id": item["json"].get("id"),
"name": item["json"].get("name", "Unknown").upper(),
"processed": True
}
}
for item in items
]
```
### 2. Filtering & Aggregation
Sum, filter, count with built-in functions
```python
items = _input.all()
total = sum(item["json"].get("amount", 0) for item in items)
valid_items = [item for item in items if item["json"].get("amount", 0) > 0]
return [{
"json": {
"total": total,
"count": len(valid_items)
}
}]
```
### 3. String Processing with Regex
Extract patterns from text
```python
import re
items = _input.all()
email_pattern = r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b'
all_emails = []
for item in items:
text = item["json"].get("text", "")
emails = re.findall(email_pattern, text)
all_emails.extend(emails)
# Remove duplicates
unique_emails = list(set(all_emails))
return [{
"json": {
"emails": unique_emails,
"count": len(unique_emails)
}
}]
```
### 4. Data Validation
Validate and clean data
```python
items = _input.all()
validated = []
for item in items:
data = item["json"]
errors = []
# Validate fields
if not data.get("email"):
errors.append("Email required")
if not data.get("name"):
errors.append("Name required")
validated.append({
"json": {
**data,
"valid": len(errors) == 0,
"errors": errors if errors else None
}
})
return validated
```
### 5. Statistical Analysis
Calculate statistics with statistics module
```python
from statistics import mean, median, stdev
items = _input.all()
values = [item["json"].get("value", 0) for item in items if "value" in item["json"]]
if values:
return [{
"json": {
"mean": mean(values),
"median": median(values),
"stdev": stdev(values) if len(values) > 1 else 0,
"min": min(values),
"max": max(values),
"count": len(values)
}
}]
else:
return [{"json": {"error": "No values found"}}]
```
**See**: [COMMON_PATTERNS.md](COMMON_PATTERNS.md) for 10 detailed Python patterns
---
## Error Prevention - Top 5 Mistakes
### #1: Importing External Libraries (Python-Specific!)
```python
# ❌ WRONG: Trying to import external library
import requests # ModuleNotFoundError!
# ✅ CORRECT: Use HTTP Request node or JavaScript
# Add HTTP Request node before Code node
# OR switch to JavaScript and use $helpers.httpRequest()
```
### #2: Empty Code or Missing Return
```python
# ❌ WRONG: No return statement
items = _input.all()
# Processing...
# Forgot to return!
# ✅ CORRECT: Always return data
items = _input.all()
# Processing...
return [{"json": item["json"]} for item in items]
```
### #3: Incorrect Return Format
```python
# ❌ WRONG: Returning dict instead of list
return {"json": {"result": "success"}}
# ✅ CORRECT: List wrapper required
return [{"json": {"result": "success"}}]
```
### #4: KeyError on Dictionary Access
```python
# ❌ WRONG: Direct access crashes if missing
name = _json["user"]["name"] # KeyError!
# ✅ CORRECT: Use .get() for safe access
name = _json.get("user", {}).get("name", "Unknown")
```
### #5: Webhook Body Nesting
```python
# ❌ WRONG: Direct access to webhook data
email = _json["email"] # KeyError!
# ✅ CORRECT: Webhook data under ["body"]
email = _json["body"]["email"]
# ✅ BETTER: Safe access with .get()
email = _json.get("body", {}).get("email", "no-email")
```
**See**: [ERROR_PATTERNS.md](ERROR_PATTERNS.md) for comprehensive error guide
---
## Standard Library Reference
### Most Useful Modules
```python
# JSON operations
import json
data = json.loads(json_string)
json_output = json.dumps({"key": "value"})
# Date/time
from datetime import datetime, timedelta
now = datetime.now()
tomorrow = now + timedelta(days=1)
formatted = now.strftime("%Y-%m-%d")
# Regular expressions
import re
matches = re.findall(r'\d+', text)
cleaned = re.sub(r'[^\w\s]', '', text)
# Base64 encoding
import base64
encoded = base64.b64encode(data).decode()
decoded = base64.b64decode(encoded)
# Hashing
import hashlib
hash_value = hashlib.sha256(text.encode()).hexdigest()
# URL parsing
import urllib.parse
params = urllib.parse.urlencode({"key": "value"})
parsed = urllib.parse.urlparse(url)
# Statistics
from statistics import mean, median, stdev
average = mean([1, 2, 3, 4, 5])
```
**See**: [STANDARD_LIBRARY.md](STANDARD_LIBRARY.md) for complete reference
---
## Best Practices
### 1. Always Use .get() for Dictionary Access
```python
# ✅ SAFE: Won't crash if field missing
value = item["json"].get("field", "default")
# ❌ RISKY: Crashes if field doesn't exist
value = item["json"]["field"]
```
### 2. Handle None/Null Values Explicitly
```python
# ✅ GOOD: Default to 0 if None
amount = item["json"].get("amount") or 0
# ✅ GOOD: Check for None explicitly
text = item["json"].get("text")
if text is None:
text = ""
```
### 3. Use List Comprehensions for Filtering
```python
# ✅ PYTHONIC: List comprehension
valid = [item for item in items if item["json"].get("active")]
# ❌ VERBOSE: Manual loop
valid = []
for item in items:
if item["json"].get("active"):
valid.append(item)
```
### 4. Return Consistent Structure
```python
# ✅ CONSISTENT: Always list with "json" key
return [{"json": result}] # Single result
return results # Multiple results (already formatted)
return [] # No results
```
### 5. Debug with print() Statements
```python
# Debug statements appear in browser console (F12)
items = _input.all()
print(f"Processing {len(items)} items")
print(f"First item: {items[0] if items else 'None'}")
```
---
## When to Use Python vs JavaScript
### Use Python When:
- ✅ You need `statistics` module for statistical operations
- ✅ You're significantly more comfortable with Python syntax
- ✅ Your logic maps well to list comprehensions
- ✅ You need specific standard library functions
### Use JavaScript When:
- ✅ You need HTTP requests ($helpers.httpRequest())
- ✅ You need advanced date/time (DateTime/Luxon)
- ✅ You want better n8n integration
- ✅ **For 95% of use cases** (recommended)
### Consider Other Nodes When:
- ❌ Simple field mapping → Use **Set** node
- ❌ Basic filtering → Use **Filter** node
- ❌ Simple conditionals → Use **IF** or **Switch** node
- ❌ HTTP requests only → Use **HTTP Request** node
---
## Integration with Other Skills
### Works With:
**n8n Expression Syntax**:
- Expressions use `{{ }}` syntax in other nodes
- Code nodes use Python directly (no `{{ }}`)
- When to use expressions vs code
**n8n MCP Tools Expert**:
- How to find Code node: `search_nodes({query: "code"})`
- Get configuration help: `get_node_essentials("nodes-base.code")`
- Validate code: `validate_node_operation()`
**n8n Node Configuration**:
- Mode selection (All Items vs Each Item)
- Language selection (Python vs JavaScript)
- Understanding property dependencies
**n8n Workflow Patterns**:
- Code nodes in transformation step
- When to use Python vs JavaScript in patterns
**n8n Validation Expert**:
- Validate Code node configuration
- Handle validation errors
- Auto-fix common issues
**n8n Code JavaScript**:
- When to use JavaScript instead
- Comparison of JavaScript vs Python features
- Migration from Python to JavaScript
---
## Quick Reference Checklist
Before deploying Python Code nodes, verify:
- [ ] **Considered JavaScript first** - Using Python only when necessary
- [ ] **Code is not empty** - Must have meaningful logic
- [ ] **Return statement exists** - Must return list of dictionaries
- [ ] **Proper return format** - Each item: `{"json": {...}}`
- [ ] **Data access correct** - Using `_input.all()`, `_input.first()`, or `_input.item`
- [ ] **No external imports** - Only standard library (json, datetime, re, etc.)
- [ ] **Safe dictionary access** - Using `.get()` to avoid KeyError
- [ ] **Webhook data** - Access via `["body"]` if from webhook
- [ ] **Mode selection** - "All Items" for most cases
- [ ] **Output consistent** - All code paths return same structure
---
## Additional Resources
### Related Files
- [DATA_ACCESS.md](DATA_ACCESS.md) - Comprehensive Python data access patterns
- [COMMON_PATTERNS.md](COMMON_PATTERNS.md) - 10 Python patterns for n8n
- [ERROR_PATTERNS.md](ERROR_PATTERNS.md) - Top 5 errors and solutions
- [STANDARD_LIBRARY.md](STANDARD_LIBRARY.md) - Complete standard library reference
### n8n Documentation
- Code Node Guide: https://docs.n8n.io/code/code-node/
- Python in n8n: https://docs.n8n.io/code/builtin/python-modules/
---
**Ready to write Python in n8n Code nodes - but consider JavaScript first!** Use Python for specific needs, reference the error patterns guide to avoid common mistakes, and leverage the standard library effectively.