n8n-code-python

# 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`, `_jme