Transform Node

The Transform node is used to transform and process data between workflow steps using expressions. It provides a concise way to perform data transformation operations without writing complete code.

Use Cases

Typical Applications

Data Format Conversion - Convert data from one format to another
Field Mapping - Rename, reorganize, or extract data fields
Data Filtering - Filter arrays or objects using expressions
Calculated Fields - Calculate new fields based on existing data
Data Merging - Merge multiple data sources
Type Conversion - Convert between strings, numbers, booleans, etc.
Data Cleaning - Clean and normalize data

Node Configuration

Basic Settings (Parameters Panel)

Expression (expression)

Expression used to transform data.

Field Properties:

Required field
Supports expression syntax
Supports multi-line expressions
Can use all features of workflow expression engine

Configuration Examples:

javascript

// 1. Simple field extraction
$('HTTP Request').body.userId

// 2. Field renaming and reorganization
{
  id: $('HTTP Request').body.userId,
  name: $('HTTP Request').body.userName,
  email: $('HTTP Request').body.userEmail
}

// 3. Data transformation and calculation
{
  originalPrice: $('HTTP Request').body.price,
  discount: 0.1,
  finalPrice: $('HTTP Request').body.price * 0.9,
  currency: "USD"
}

// 4. Array processing
$('HTTP Request').body.items.map(item => ({
  id: item.id,
  name: item.name,
  price: item.price * 0.9  // Apply discount
}))

// 5. Conditional transformation
$('HTTP Request').body.status === "active"
  ? { status: "Enabled", enabled: true }
  : { status: "Disabled", enabled: false }

// 6. Multi-line expression (returning object)
{
  userId: $('Chat Trigger').userId,
  message: $('Chat Trigger').message,
  timestamp: new Date().toISOString(),
  processedMessage: $('Chat Trigger').message.toUpperCase()
}

// 7. String formatting
`Order ID: ${$('HTTP Request').body.orderId}
Amount: $${$('HTTP Request').body.amount}
Status: ${$('HTTP Request').body.status}`

// 8. Array filtering and transformation
$('HTTP Request').body.products
  .filter(p => p.inStock === true)
  .map(p => ({
    name: p.name,
    price: p.price,
    category: p.category
  }))

Expression Methods:

The Transform node supports all expression methods, including:

Array methods: map(), filter(), find(), reduce(), slice(), sort(), etc.
String methods: toUpperCase(), toLowerCase(), replace(), split(), trim(), etc.
Number methods: toFixed(), round(), floor(), ceil(), etc.
Object methods: keys(), values(), entries(), etc.

Advanced Settings (Settings Panel)

Always Output (alwaysOutput)

Whether to output an empty item when output is empty.

Default: false

Purpose: Prevents workflow from terminating at this node, ensuring subsequent nodes can execute.

Execute Once (executeOnce)

Whether to execute only once using data from the first item received.

Default: false

Purpose:

When upstream node returns multiple items, defaults to executing transformation for each item
After enabling this option, only executes for first item, improving performance

Retry on Fail (retryOnFail)

Whether to automatically retry on transformation failure.

Default: false

Max Tries (maxTries)

Maximum retries after failure.

Default: 3

Wait Between Tries (waitBetweenTries)

Wait time between retries (milliseconds).

Default: 1000 (1 second)

Error Handling (onError)

How to handle transformation failures.

Available Values:

stopWorkflow - Stop entire workflow (default)
continueRegularOutput - Continue execution
continueErrorOutput - Continue execution, use error output

Node Description (nodeDescription)

Add custom description for the node.

yaml

nodeDescription: "Transform order data to standard format"

Output Data

The Transform node returns the result of expression evaluation. The returned data type depends on the expression's calculation result.

Output Examples:

javascript

// Simple value
"user123"

// Object
{
  id: "user123",
  name: "John",
  email: "john@example.com"
}

// Array
[
  { id: 1, name: "Product A" },
  { id: 2, name: "Product B" }
]

// String
"Order ID: ORD-12345, Amount: $299.00"

Access Output:

javascript

// Get entire output
$('Transform').output

// Get object fields
$('Transform').id
$('Transform').name

// Get array elements
$('Transform')[0]
$('Transform')[0].name

// Get string
$('Transform')

Workflow Examples

Example 1: Field Renaming and Reorganization

HTTP Request
  → Transform Node
    Expression: {
      orderId: $('HTTP Request').body.order_id,
      customerName: $('HTTP Request').body.customer_name,
      totalAmount: $('HTTP Request').body.total_amount,
      status: $('HTTP Request').body.order_status
    }
  → Database Node
    Insert transformed data into database

Example 2: Price Calculation and Formatting

HTTP Request
  → Transform Node
    Expression: {
      originalPrice: $('HTTP Request').body.price,
      discountRate: 0.15,
      discountAmount: $('HTTP Request').body.price * 0.15,
      finalPrice: $('HTTP Request').body.price * 0.85,
      formattedPrice: `$${($('HTTP Request').body.price * 0.85).toFixed(2)}`
    }
  → Send Email Node
    Use formatted price information

Example 3: Array Filtering and Transformation

HTTP Request
  → Transform Node
    Expression: $('HTTP Request').body.products
      .filter(p => p.stock > 0 && p.price <= 1000)
      .map(p => ({
        id: p.product_id,
        name: p.product_name,
        price: p.price,
        discountPrice: p.price * 0.9
      }))
  → Batch Operation Node
    Process filtered product list

Example 4: Data Merging

HTTP Request A
  ↓
HTTP Request B ─→ Transform Node
                   Expression: {
                     user: {
                       id: $('HTTP Request A').body.userId,
                       name: $('HTTP Request A').body.userName
                     },
                     order: {
                       id: $('HTTP Request B').body.orderId,
                       items: $('HTTP Request B').body.items
                     },
                     timestamp: new Date().toISOString()
                   }
                  → Send Notification Node

Example 5: Conditional Transformation

AI Classifier
  → Transform Node
    Expression: $('AI Classifier').class === "urgent"
      ? {
          priority: "high",
          subject: `[Urgent] ${$('Chat Trigger').message}`,
          channel: "email"
        }
      : {
          priority: "normal",
          subject: $('Chat Trigger').message,
          channel: "chat"
        }
  → Conditional Branch
    Route to different processes based on priority

Best Practices

1. Keep Expressions Concise

Good Practice:

javascript

// Clear and concise
{
  id: $('HTTP Request').body.userId,
  name: $('HTTP Request').body.userName
}

Avoid:

javascript

// Too complex, should use Code node
$('HTTP Request').body.items
  .filter(i => i.price > 100)
  .map(i => ({...i, discount: i.price * 0.1}))
  .sort((a, b) => b.discount - a.discount)
  .slice(0, 10)
  .reduce((acc, cur) => ({...acc, [cur.id]: cur}), {})

2. Handle Null Values and Errors

javascript

// Use default values
{
  name: $('HTTP Request').body.name || "Unknown",
  email: $('HTTP Request').body.email || "",
  age: $('HTTP Request').body.age || 0
}

// Use optional chaining
$('HTTP Request').body?.user?.name || "Unknown"

3. Maintain Data Consistency

javascript

// Unified field naming style
{
  userId: $('HTTP Request').body.user_id,  // Unified to camelCase
  userName: $('HTTP Request').body.user_name,
  userEmail: $('HTTP Request').body.user_email
}

FAQ

Q1: What's the difference between Transform node and Code node?

Feature	Transform Node	Code Node
Syntax	Expression syntax	Python/JavaScript code
Complexity	Suitable for simple transformations	Suitable for complex logic
Performance	Faster	Slightly slower (needs code execution)
Debugging	Expression evaluation	Code execution
Use Case	Field mapping, simple calculations	Complex algorithms, business logic

Selection Advice:

Simple transformations (field renaming, simple calculations) → Use Transform node
Complex logic (loops, conditionals, complex algorithms) → Use Code node

Q2: How to handle array data?

A: Use array methods:

javascript

// Filter
$('HTTP Request').body.items.filter(item => item.stock > 0)

// Map transformation
$('HTTP Request').body.items.map(item => ({
  id: item.id,
  name: item.name,
  price: item.price * 0.9
}))

// Find
$('HTTP Request').body.items.find(item => item.id === "123")

// Slice
$('HTTP Request').body.items.slice(0, 10)

Q3: How to merge multiple data sources?

A: Reference multiple nodes in expression:

javascript

{
  userInfo: {
    id: $('HTTP Request A').body.userId,
    name: $('HTTP Request A').body.userName
  },
  orderInfo: {
    id: $('HTTP Request B').body.orderId,
    items: $('HTTP Request B').body.items
  },
  timestamp: new Date().toISOString()
}

Next Steps

Code Node - Learn about more complex data processing
Expression Syntax - Learn full expression capabilities
IF Node - Conditional branching based on transformation results

HTTP Request Node - Get data to transform
Database Node - Use transformed data

Trigger Nodes

Chat Trigger

Action Nodes

Control Nodes

Tool Nodes

Group Nodes

Transform Node

Use Cases

Typical Applications

Node Configuration

Basic Settings (Parameters Panel)

Expression (expression)

Advanced Settings (Settings Panel)

Always Output (alwaysOutput)

Execute Once (executeOnce)

Retry on Fail (retryOnFail)

Max Tries (maxTries)

Wait Between Tries (waitBetweenTries)

Error Handling (onError)

Node Description (nodeDescription)

Output Data

Workflow Examples

Example 1: Field Renaming and Reorganization

Example 2: Price Calculation and Formatting

Example 3: Array Filtering and Transformation

Example 4: Data Merging

Example 5: Conditional Transformation

Best Practices

1. Keep Expressions Concise

2. Handle Null Values and Errors

3. Maintain Data Consistency

FAQ

Q1: What's the difference between Transform node and Code node?

Q2: How to handle array data?

Q3: How to merge multiple data sources?

Next Steps

Chat Trigger

Transform Node ​

Use Cases ​

Typical Applications ​

Node Configuration ​

Basic Settings (Parameters Panel) ​

Expression (expression) ​

Advanced Settings (Settings Panel) ​

Always Output (alwaysOutput) ​

Execute Once (executeOnce) ​

Retry on Fail (retryOnFail) ​

Max Tries (maxTries) ​

Wait Between Tries (waitBetweenTries) ​

Error Handling (onError) ​

Node Description (nodeDescription) ​

Output Data ​

Workflow Examples ​

Example 1: Field Renaming and Reorganization ​

Example 2: Price Calculation and Formatting ​

Example 3: Array Filtering and Transformation ​

Example 4: Data Merging ​

Example 5: Conditional Transformation ​

Best Practices ​

1. Keep Expressions Concise ​

2. Handle Null Values and Errors ​

3. Maintain Data Consistency ​

FAQ ​

Q1: What's the difference between Transform node and Code node? ​

Q2: How to handle array data? ​

Q3: How to merge multiple data sources? ​

Next Steps ​

Related Resources ​

Transform Node

Use Cases

Typical Applications

Node Configuration

Basic Settings (Parameters Panel)

Expression (expression)

Advanced Settings (Settings Panel)

Always Output (alwaysOutput)

Execute Once (executeOnce)

Retry on Fail (retryOnFail)

Max Tries (maxTries)

Wait Between Tries (waitBetweenTries)

Error Handling (onError)

Node Description (nodeDescription)

Output Data

Workflow Examples

Example 1: Field Renaming and Reorganization

Example 2: Price Calculation and Formatting

Example 3: Array Filtering and Transformation

Example 4: Data Merging

Example 5: Conditional Transformation

Best Practices

1. Keep Expressions Concise

2. Handle Null Values and Errors

3. Maintain Data Consistency

FAQ

Q1: What's the difference between Transform node and Code node?

Q2: How to handle array data?

Q3: How to merge multiple data sources?

Next Steps

Related Resources