Field Extraction Node
Overview
The Field Extraction Node extracts specific fields from objects, documents, or complex data structures within your flow. This node is essential for accessing nested data, array elements, or specific properties from structured inputs. It supports both simple field access and advanced dot notation for deep object traversal.
Usage cost: 0 credit
Configuration
Source Selection
Source Object* (dropdown): Select the object or variable to extract from
Only variables of type object, document, or any are available
Shows variable type and source node for easy identification
Extraction Configuration
Extraction Mode* (dropdown): Method for field access
Simple: Direct field access for top-level properties
Use field names like
"name"
,"email"
Use numeric indices for arrays like
"0"
,"1"
Dot Notation: Nested access for complex structures
Use paths like
"user.profile.name"
,"items.0.title"
Supports mixed object/array navigation
Field Key/Path* (text): The field identifier
Simple mode: Direct field name or array index
Dot notation mode: Full path using dot separation
Examples:
"name"
,"user.profile.email"
,"items.0.metadata.source"
Default Handling
Default Value (text): Value returned if field is not found
Supports variable interpolation for dynamic defaults
Leave empty to return
null
when field is missingCan reference other variables as fallback values
Output Ports
extracted_value
(any): The extracted field valueReturns the actual data type of the extracted field
Returns default value if field doesn't exist or is null
Preserves original data structure (strings, numbers, objects, arrays)
Best Practices
Field Path Design
Verify field names are exact matches (case-sensitive)
Use dot notation for accessing nested structures consistently
Test extraction paths with sample data before deployment
Default Value Strategy
Provide meaningful defaults for optional fields
Use variable references for dynamic fallback values
Consider downstream node requirements when setting defaults
Data Type Handling
Remember that extracted values maintain their original data types
Plan for different data types in downstream processing
Use appropriate type checking in subsequent nodes
Common Issues
Case sensitivity errors - Field names must match exactly including capitalization
Array index out of bounds - Verify array length before accessing specific indices
Nested path errors - Check that all intermediate objects exist in the path
Type mismatch expectations - Extracted values retain original data types
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