step

python_function

Execute custom Python code to transform events with full programming flexibility.

Overview

Execute custom Python code to transform events with full programming flexibility. This step runs user-provided Python code in a secure Pyodide sandbox, allowing you to implement any custom transformation logic that built-in steps don't cover. Your code is loaded once at workflow startup, and the specified handler function is called for each event. The function receives the event as a dictionary and must return the modified event. You can use Python's standard library to manipulate data, perform calculations, call external functions, or implement complex business logic. The sandbox ensures isolation and security while giving you the full power of Python for data transformation.

Quick Start

steps:
- type: python_function
  code: <string>
  handler: <string>

Configuration

Parameter	Type	Required	Description
`code`	`string`	Yes	Python source code that defines your handler. The code runs once inside the sandboxed module namespace.
`handler`	`string`	Yes	Name of the function declared in 'code'. It must accept a dict event and return the transformed event (or None).

Examples

Combine and format fields

Create derived fields from existing data

type: python_function
code: |
  def process(event):
      event['full_name'] = f"{event['first_name']} {event['last_name']}"
      event['display_name'] = event['full_name'].title()
      return event
handler: process

Calculate totals and taxes

Perform financial calculations on order data

type: python_function
code: |
  def process(event):
      subtotal = event['quantity'] * event['price']
      tax_rate = 0.08
      tax = subtotal * tax_rate
      event['subtotal'] = round(subtotal, 2)
      event['tax'] = round(tax, 2)
      event['total'] = round(subtotal + tax, 2)
      return event
handler: process

Clean and normalize data

Remove sensitive fields and normalize formats

type: python_function
code: |
  def process(event):
      # Remove sensitive fields
      for field in ['password', 'ssn', 'credit_card']:
          event.pop(field, None)

      # Normalize email and phone
      if 'email' in event:
          event['email'] = event['email'].lower().strip()
      if 'phone' in event:
          event['phone'] = ''.join(filter(str.isdigit, event['phone']))

      return event
handler: process

Parse and transform dates

Convert date strings to different formats

type: python_function
code: |
  from datetime import datetime

  def process(event):
      if 'date_string' in event:
          dt = datetime.strptime(event['date_string'], '%Y-%m-%d')
          event['formatted_date'] = dt.strftime('%B %d, %Y')
          event['day_of_week'] = dt.strftime('%A')
          event['timestamp'] = int(dt.timestamp())
      return event
handler: process

Conditional logic and categorization

Apply business rules to categorize data

type: python_function
code: |
  def process(event):
      score = event.get('score', 0)

      if score >= 90:
          event['grade'] = 'A'
          event['category'] = 'excellent'
      elif score >= 80:
          event['grade'] = 'B'
          event['category'] = 'good'
      elif score >= 70:
          event['grade'] = 'C'
          event['category'] = 'average'
      else:
          event['grade'] = 'F'
          event['category'] = 'needs_improvement'

      event['passed'] = score >= 70
      return event
handler: process

Array and string manipulation

Process arrays and strings with Python methods

type: python_function
code: |
  def process(event):
      # Split comma-separated tags into list
      if 'tags' in event and isinstance(event['tags'], str):
          event['tags'] = [tag.strip() for tag in event['tags'].split(',')]

      # Create acronym from title
      if 'title' in event:
          words = event['title'].split()
          event['acronym'] = ''.join(w[0].upper() for w in words if w)

      # Count unique values
      if 'items' in event:
          event['unique_items'] = len(set(event['items']))

      return event
handler: process

Advanced Options

These options are available on all steps for error handling and retry logic:

Parameter	Type	Default	Description
`retries`	`integer`	`0`	Number of retry attempts (0-10)
`backoff_seconds`	`number`	`0`	Backoff (seconds) applied between retry attempts
`retry_propagate`	`boolean`	`false`	If True, raise last exception after exhausting retries; otherwise swallow.

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