Expression¶
Class: ExpressionBlockV1
Source: inference.core.workflows.core_steps.formatters.expression.v1.ExpressionBlockV1
Create conditional logic and business rules in workflows using switch-case statements that evaluate conditions on input variables, optionally transform data with operations, and return different outputs based on which condition matches, enabling conditional execution, business logic implementation, rule-based decision making, and dynamic output generation workflows.
How This Block Works¶
This block implements conditional logic similar to switch-case or if-else-if statements in programming. The block:
- Receives input data as a dictionary of named variables from workflow steps
- Optionally applies data transformations using operations:
- Performs operations on data variables before condition evaluation
- Uses the same operation system as Property Definition block
- Transforms data (e.g., extract properties, filter, select) to prepare variables for conditions
- Stores transformed values as variables for use in conditions
- Evaluates switch-case statements sequentially:
- Tests each case condition in order until one matches
- Stops at the first matching case and returns its result
- If no case matches, returns the default result
- Evaluates conditions using a flexible expression system:
- Binary Statements: Compare two values using operators (==, !=, >, <, >=, <=, contains, startsWith, endsWith, in, any in, all in)
- Unary Statements: Test single values (Exists, DoesNotExist, is True, is False, is empty, is not empty)
- Statement Groups: Combine multiple statements with AND/OR operators for complex conditions
- Conditions can reference variables by name (DynamicOperand) or use literal values (StaticOperand)
- Returns results based on matched case:
Static Results: - Returns a fixed value defined in the case (e.g., "PASS", "FAIL", numeric values, strings)
Dynamic Results: - Returns a value from a variable (can reference any input variable) - Optionally applies operations to transform the variable before returning - Enables returning computed or extracted values as output
- Handles default case:
- If no case condition matches, returns the default result
- Default can be static or dynamic, just like case results
The block enables complex conditional logic by combining data transformation operations with flexible condition evaluation. Conditions can compare variables, test existence, check membership, perform string operations, and combine multiple conditions with logical operators. This makes it powerful for implementing business rules, validation logic, classification based on multiple criteria, and conditional data transformation.
Common Use Cases¶
- Business Logic Implementation: Implement conditional business rules and validation logic (e.g., validate detection matches reference, implement quality checks, enforce business rules), enabling business logic workflows
- Conditional Classification: Classify data based on multiple conditions and criteria (e.g., classify detections based on properties, categorize results by conditions, implement multi-criteria classification), enabling conditional classification workflows
- Validation and Quality Control: Validate data or predictions against reference values or thresholds (e.g., validate predictions match expected classes, check quality thresholds, verify compliance), enabling validation workflows
- Rule-Based Decision Making: Make decisions based on complex rule sets (e.g., approve/reject based on multiple criteria, route data based on conditions, make decisions using rule sets), enabling rule-based decision workflows
- Dynamic Output Generation: Generate different outputs based on input conditions (e.g., return different values based on conditions, generate conditional outputs, create dynamic results), enabling dynamic output workflows
- Multi-Condition Filtering: Implement complex filtering logic with multiple conditions (e.g., filter based on multiple criteria, apply complex conditional filters, implement multi-factor filtering), enabling conditional filtering workflows
Connecting to Other Blocks¶
This block receives data from workflow steps and produces conditional output:
- After model or analytics blocks to implement conditional logic on predictions or results (e.g., validate predictions, classify results, apply conditional rules), enabling conditional logic workflows
- After Property Definition blocks to use extracted properties in conditions (e.g., use extracted values in conditions, compare extracted properties, implement logic on extracted data), enabling property-to-condition workflows
- Before logic blocks like Continue If to provide conditional inputs (e.g., provide conditional values for filtering, supply conditional inputs for decisions), enabling expression-to-logic workflows
- Before data storage blocks to conditionally format or transform data for storage (e.g., conditionally format for storage, apply conditional transformations, prepare conditional outputs), enabling conditional storage workflows
- Before notification blocks to send conditional notifications (e.g., send conditional alerts, notify based on conditions, trigger conditional notifications), enabling conditional notification workflows
- In workflow outputs to provide conditional final outputs (e.g., conditional workflow outputs, dynamic result generation, conditional output formatting), enabling conditional output workflows
Requirements¶
This block requires input data as a dictionary where keys are variable names and values are data from workflow steps. The switch parameter defines cases with conditions and results. Conditions support binary comparisons (==, !=, >, <, >=, <=, contains, in, etc.), unary tests (Exists, is empty, etc.), and logical combinations (AND/OR). Data operations are optional and use the same operation system as Property Definition block. The block evaluates cases in order and returns the result of the first matching case, or the default result if no cases match. Results can be static values or dynamic values from variables (optionally with operations applied).
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/expression@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
data_operations |
Dict[str, List[Union[ClassificationPropertyExtract, ConvertDictionaryToJSON, ConvertImageToBase64, ConvertImageToJPEG, DetectionsFilter, DetectionsOffset, DetectionsPropertyExtract, DetectionsRename, DetectionsSelection, DetectionsShift, DetectionsToDictionary, Divide, ExtractDetectionProperty, ExtractFrameMetadata, ExtractImageProperty, LookupTable, Multiply, NumberRound, NumericSequenceAggregate, PickDetectionsByParentClass, RandomNumber, SequenceAggregate, SequenceApply, SequenceElementsCount, SequenceLength, SequenceMap, SortDetections, StringMatches, StringSubSequence, StringToLowerCase, StringToUpperCase, TimestampToISOFormat, ToBoolean, ToNumber, ToString]]] |
Optional dictionary of operations to transform data variables before condition evaluation. Keys are variable names from data, values are lists of operations (same as Property Definition block). Operations are applied to transform variables before they are used in conditions. Useful for extracting properties, filtering, or transforming data before evaluation. Empty dictionary (default) means no transformations are applied.. | ❌ |
switch |
CasesDefinition |
Switch-case logic definition containing cases with conditions and results. Each case has a condition (StatementGroup with binary/unary statements) and a result (static value or dynamic variable). Cases are evaluated in order - first matching case's result is returned. Default result is returned if no cases match. Supports complex conditions with AND/OR operators, comparison operators (==, !=, >, <, >=, <=), string operations (contains, startsWith, endsWith), membership tests (in, any in, all in), and existence tests (Exists, is empty).. | ❌ |
The Refs column marks possibility to parametrise the property with dynamic values available
in workflow runtime. See Bindings for more info.
Available Connections¶
Compatible Blocks
Check what blocks you can connect to Expression in version v1.
- inputs:
Florence-2 Model,Detections Combine,Roboflow Dataset Upload,Trace Visualization,Delta Filter,Classification Label Visualization,Single-Label Classification Model,Line Counter,Clip Comparison,Ellipse Visualization,Qwen3-VL,Detections Stabilizer,Triangle Visualization,Morphological Transformation,Path Deviation,LMM,First Non Empty Or Default,SmolVLM2,Dimension Collapse,Barcode Detection,Local File Sink,VLM As Classifier,Icon Visualization,QR Code Generator,Stability AI Outpainting,OpenAI,Keypoint Detection Model,Moondream2,Florence-2 Model,Pixelate Visualization,Object Detection Model,Gaze Detection,Cosine Similarity,Background Color Visualization,Clip Comparison,Background Subtraction,Time in Zone,Keypoint Detection Model,Keypoint Visualization,Perception Encoder Embedding Model,Overlap Filter,EasyOCR,Image Blur,Anthropic Claude,Polygon Visualization,SIFT,Webhook Sink,Object Detection Model,Dominant Color,Cache Get,YOLO-World Model,Property Definition,Heatmap Visualization,Image Threshold,Multi-Label Classification Model,Google Gemini,Text Display,Detection Event Log,OpenAI,Instance Segmentation Model,Qwen2.5-VL,Continue If,Single-Label Classification Model,Anthropic Claude,Time in Zone,CSV Formatter,Path Deviation,Rate Limiter,Detections Consensus,Stability AI Inpainting,Roboflow Custom Metadata,QR Code Detection,Polygon Visualization,CogVLM,Velocity,Bounding Box Visualization,CLIP Embedding Model,Identify Outliers,Camera Focus,Llama 3.2 Vision,Email Notification,Dynamic Crop,Image Contours,Time in Zone,LMM For Classification,Buffer,Seg Preview,Segment Anything 2 Model,Stitch Images,Bounding Rectangle,Image Slicer,Line Counter,Byte Tracker,SAM 3,Distance Measurement,Crop Visualization,Grid Visualization,Roboflow Dataset Upload,Google Gemini,Stitch OCR Detections,Reference Path Visualization,Multi-Label Classification Model,Twilio SMS/MMS Notification,Data Aggregator,Image Slicer,Detections Classes Replacement,Detection Offset,Detections Transformation,Google Vision OCR,Camera Focus,Pixel Color Count,Model Comparison Visualization,Template Matching,Model Monitoring Inference Aggregator,Image Preprocessing,Twilio SMS Notification,Color Visualization,Polygon Zone Visualization,OpenAI,Halo Visualization,Instance Segmentation Model,Contrast Equalization,Mask Area Measurement,Google Gemini,Perspective Correction,Circle Visualization,Blur Visualization,Dot Visualization,Camera Calibration,Relative Static Crop,Email Notification,Depth Estimation,VLM As Detector,Mask Visualization,Dynamic Zone,Stability AI Image Generation,Detections Filter,Byte Tracker,Environment Secrets Store,Size Measurement,Halo Visualization,Absolute Static Crop,Detections Stitch,OCR Model,Label Visualization,Detections Merge,Motion Detection,Anthropic Claude,Corner Visualization,Cache Set,Image Convert Grayscale,Stitch OCR Detections,Expression,SIFT Comparison,SIFT Comparison,Detections List Roll-Up,SAM 3,VLM As Detector,Line Counter Visualization,SAM 3,VLM As Classifier,JSON Parser,PTZ Tracking (ONVIF),Slack Notification,Identify Changes,Byte Tracker,OpenAI - outputs:
Florence-2 Model,Detections Combine,Trace Visualization,Roboflow Dataset Upload,Delta Filter,Classification Label Visualization,Single-Label Classification Model,Line Counter,Clip Comparison,Ellipse Visualization,Qwen3-VL,Detections Stabilizer,Triangle Visualization,Path Deviation,Morphological Transformation,LMM,First Non Empty Or Default,SmolVLM2,Dimension Collapse,Barcode Detection,Local File Sink,VLM As Classifier,Icon Visualization,QR Code Generator,Stability AI Outpainting,OpenAI,Moondream2,Keypoint Detection Model,Florence-2 Model,Pixelate Visualization,Object Detection Model,Gaze Detection,Cosine Similarity,Clip Comparison,Background Color Visualization,Time in Zone,Background Subtraction,Keypoint Detection Model,Keypoint Visualization,Perception Encoder Embedding Model,Overlap Filter,EasyOCR,Image Blur,Polygon Visualization,Anthropic Claude,SIFT,Webhook Sink,Object Detection Model,Dominant Color,Cache Get,YOLO-World Model,Property Definition,Multi-Label Classification Model,Heatmap Visualization,Image Threshold,Google Gemini,Text Display,Detection Event Log,OpenAI,Instance Segmentation Model,Qwen2.5-VL,Continue If,Single-Label Classification Model,Anthropic Claude,Time in Zone,CSV Formatter,Path Deviation,Rate Limiter,Detections Consensus,Stability AI Inpainting,Roboflow Custom Metadata,QR Code Detection,Polygon Visualization,CogVLM,Velocity,Bounding Box Visualization,CLIP Embedding Model,Llama 3.2 Vision,Identify Outliers,Camera Focus,Email Notification,Dynamic Crop,Image Contours,Time in Zone,LMM For Classification,Buffer,Seg Preview,Segment Anything 2 Model,Stitch Images,Bounding Rectangle,Image Slicer,Line Counter,Byte Tracker,SAM 3,Distance Measurement,Crop Visualization,Roboflow Dataset Upload,Grid Visualization,Twilio SMS/MMS Notification,Multi-Label Classification Model,Stitch OCR Detections,Google Gemini,Reference Path Visualization,Image Slicer,Data Aggregator,Detections Classes Replacement,Detection Offset,Detections Transformation,Google Vision OCR,Pixel Color Count,Camera Focus,Model Comparison Visualization,Template Matching,Image Preprocessing,Twilio SMS Notification,Color Visualization,Polygon Zone Visualization,OpenAI,Halo Visualization,Instance Segmentation Model,Contrast Equalization,Byte Tracker,Mask Area Measurement,Google Gemini,Perspective Correction,Circle Visualization,Blur Visualization,Dot Visualization,Camera Calibration,Relative Static Crop,Email Notification,Depth Estimation,VLM As Detector,Mask Visualization,Stability AI Image Generation,Dynamic Zone,Detections Filter,Byte Tracker,Size Measurement,Halo Visualization,Absolute Static Crop,Detections Stitch,OCR Model,Label Visualization,Detections Merge,Motion Detection,Anthropic Claude,Stitch OCR Detections,Corner Visualization,Cache Set,Image Convert Grayscale,Expression,SIFT Comparison,SIFT Comparison,Detections List Roll-Up,SAM 3,VLM As Detector,Line Counter Visualization,SAM 3,VLM As Classifier,JSON Parser,PTZ Tracking (ONVIF),Slack Notification,Identify Changes,Model Monitoring Inference Aggregator,OpenAI
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Expression in version v1 has.
Bindings
-
input
data(*): Dictionary of named variables containing data from workflow steps. Variable names are used in conditions and results. Keys are variable names, values are selectors referencing workflow step outputs. Variables can be referenced in conditions and dynamic results. Example: {'predictions': '$steps.model.predictions', 'reference': '$inputs.reference_class_names'} creates variables 'predictions' and 'reference'..
-
output
output(*): Equivalent of any element.
Example JSON definition of step Expression in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/expression@v1",
"data": {
"predictions": "$steps.model.predictions",
"reference": "$inputs.reference_class_names"
},
"data_operations": {
"predictions": [
{
"property_name": "class_name",
"type": "DetectionsPropertyExtract"
}
]
},
"switch": {
"cases": [
{
"condition": {
"statements": [
{
"comparator": {
"type": "=="
},
"left_operand": {
"operand_name": "class_name",
"type": "DynamicOperand"
},
"right_operand": {
"operand_name": "reference",
"type": "DynamicOperand"
},
"type": "BinaryStatement"
}
],
"type": "StatementGroup"
},
"result": {
"type": "StaticCaseResult",
"value": "PASS"
},
"type": "CaseDefinition"
}
],
"default": {
"type": "StaticCaseResult",
"value": "FAIL"
},
"type": "CasesDefinition"
}
}