Code

The Code node executes custom Python or JavaScript to handle complex data transformations, calculations, and logic within your workflow. Use it when preset nodes aren’t sufficient for your specific processing needs.

Configuration

Define Input Variables to access data from other nodes in your workflow, then reference these variables in your code. Your function must return a dictionary containing the Output Variables you’ve declared.

def main(input_variable: str) -> dict:
    # Process the input
    result = input_variable.upper()
    return {
        'output_variable': result
    }

Language Support

Choose between Python and JavaScript based on your needs and familiarity. Both languages run in secure sandboxes with access to common libraries for data processing.

Python
JavaScript

Python includes standard libraries like json, math, datetime, and re. Ideal for data analysis, mathematical operations, and text processing.

def main(data: list) -> dict:
    import json
    import math
    
    average = sum(data) / len(data)
    return {'result': math.ceil(average)}

JavaScript provides standard built-in objects and methods. Good for JSON manipulation and string operations.

function main(data) {
    const processed = data.map(item => item.toUpperCase());
    return { result: processed };
}

Error Handling and Retries

Configure automatic retry behavior for failed code executions and define fallback strategies when code encounters errors.

Retry on failure allows up to 10 automatic retries with configurable intervals (maximum 5000ms). Enable this for handling temporary processing issues. Error Handling lets you define fallback paths when code execution fails, allowing your workflow to continue running even when the code encounters problems.

Output Limits

An output that exceeds any of these limits fails the node:

Output	Limit
String length	400,000 characters
Numbers	±9,223,372,036,854,775,807. Return larger numbers, such as very long IDs, as strings.
Decimal places	20
Nested objects inside an `object` output	3 levels (arrays don’t count)
Items in an `array[string]`, `array[object]`, or `array[number]` output	500

Trim or split long strings and arrays, and flatten deep objects, before returning them.

Security Considerations

Code runs in an isolated sandbox that blocks file system access and system commands. The sandbox keeps execution separated from the underlying infrastructure while still giving you the flexibility of writing custom code. Avoid reading system files or running shell commands; restructure your logic to work with the input variables and libraries available inside the sandbox instead.

Dependencies Support

Code nodes support external dependencies for both Python and JavaScript:

# Python: Import numpy, pandas, requests, etc.
import numpy as np
import pandas as pd

def main(data: list) -> dict:
    df = pd.DataFrame(data)
    return {'mean': float(np.mean(df['values']))}

// JavaScript: Import lodash, moment, etc.
const _ = require('lodash');

function main(data) {
    return { unique: _.uniq(data) };
}

A standard set of packages is pre-installed in the sandbox environment. Imports outside that set will fail at execution time.

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