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:
Contrast Equalization,Clip Comparison,Detections Transformation,VLM as Detector,Polygon Visualization,Image Blur,SIFT Comparison,First Non Empty Or Default,Text Display,SIFT,Moondream2,Qwen3-VL,Google Vision OCR,Pixelate Visualization,Time in Zone,VLM as Classifier,Detection Offset,Detections Filter,Instance Segmentation Model,Perspective Correction,Halo Visualization,Image Threshold,Path Deviation,Keypoint Detection Model,CSV Formatter,Florence-2 Model,Detections Stabilizer,Twilio SMS Notification,Image Convert Grayscale,Perception Encoder Embedding Model,Corner Visualization,Dynamic Zone,Identify Changes,Icon Visualization,Expression,SAM 3,Qwen2.5-VL,Detections Consensus,Multi-Label Classification Model,Detections Stitch,Dynamic Crop,QR Code Detection,Continue If,Bounding Box Visualization,YOLO-World Model,Detection Event Log,Detections Classes Replacement,Blur Visualization,Camera Calibration,Line Counter,Dominant Color,Path Deviation,OpenAI,Camera Focus,CogVLM,Trace Visualization,Image Slicer,Absolute Static Crop,Dot Visualization,Label Visualization,Slack Notification,Google Gemini,Object Detection Model,LMM For Classification,Stitch OCR Detections,OpenAI,Classification Label Visualization,Stitch OCR Detections,Byte Tracker,Velocity,Twilio SMS/MMS Notification,Anthropic Claude,Clip Comparison,Gaze Detection,VLM as Detector,Webhook Sink,Llama 3.2 Vision,SIFT Comparison,Anthropic Claude,Delta Filter,Time in Zone,Local File Sink,QR Code Generator,SmolVLM2,Email Notification,CLIP Embedding Model,Roboflow Dataset Upload,Motion Detection,Model Comparison Visualization,Camera Focus,PTZ Tracking (ONVIF).md),LMM,Byte Tracker,Single-Label Classification Model,Mask Visualization,Anthropic Claude,Relative Static Crop,Cosine Similarity,SAM 3,Detections Merge,Object Detection Model,Keypoint Detection Model,Circle Visualization,Seg Preview,Property Definition,EasyOCR,Stability AI Inpainting,Multi-Label Classification Model,Reference Path Visualization,Time in Zone,Detections Combine,Crop Visualization,Ellipse Visualization,Overlap Filter,Line Counter,Image Preprocessing,Barcode Detection,Environment Secrets Store,Detections List Roll-Up,Background Subtraction,Segment Anything 2 Model,Image Contours,Image Slicer,Cache Set,Depth Estimation,Pixel Color Count,Stitch Images,VLM as Classifier,Cache Get,Model Monitoring Inference Aggregator,Instance Segmentation Model,Line Counter Visualization,Morphological Transformation,Polygon Zone Visualization,Single-Label Classification Model,Email Notification,OCR Model,Distance Measurement,Roboflow Custom Metadata,Google Gemini,Keypoint Visualization,OpenAI,Size Measurement,Color Visualization,Data Aggregator,Byte Tracker,Identify Outliers,Buffer,Florence-2 Model,Google Gemini,JSON Parser,Grid Visualization,Rate Limiter,OpenAI,Template Matching,Dimension Collapse,Bounding Rectangle,Background Color Visualization,Roboflow Dataset Upload,SAM 3,Stability AI Outpainting,Triangle Visualization,Stability AI Image Generation - outputs:
Contrast Equalization,Clip Comparison,VLM as Detector,Detections Transformation,Polygon Visualization,Image Blur,SIFT Comparison,First Non Empty Or Default,Text Display,SIFT,Moondream2,Qwen3-VL,Google Vision OCR,Pixelate Visualization,Time in Zone,VLM as Classifier,Detection Offset,Detections Filter,Instance Segmentation Model,Perspective Correction,Halo Visualization,Image Threshold,Path Deviation,Keypoint Detection Model,CSV Formatter,Florence-2 Model,Detections Stabilizer,Twilio SMS Notification,Image Convert Grayscale,Perception Encoder Embedding Model,Corner Visualization,Dynamic Zone,Identify Changes,Icon Visualization,Expression,SAM 3,Qwen2.5-VL,Detections Consensus,Multi-Label Classification Model,Detections Stitch,QR Code Detection,Dynamic Crop,Continue If,Bounding Box Visualization,YOLO-World Model,Detection Event Log,Detections Classes Replacement,Blur Visualization,Camera Calibration,Line Counter,Dominant Color,Path Deviation,OpenAI,Camera Focus,CogVLM,Trace Visualization,Image Slicer,Absolute Static Crop,Dot Visualization,Label Visualization,Slack Notification,Google Gemini,Object Detection Model,LMM For Classification,Stitch OCR Detections,OpenAI,Stitch OCR Detections,Classification Label Visualization,Byte Tracker,Twilio SMS/MMS Notification,Velocity,Gaze Detection,Anthropic Claude,Clip Comparison,VLM as Detector,Webhook Sink,Llama 3.2 Vision,SIFT Comparison,Anthropic Claude,Delta Filter,Local File Sink,QR Code Generator,Time in Zone,SmolVLM2,Email Notification,CLIP Embedding Model,Roboflow Dataset Upload,Motion Detection,Model Comparison Visualization,Camera Focus,PTZ Tracking (ONVIF).md),LMM,Byte Tracker,Single-Label Classification Model,Mask Visualization,Anthropic Claude,Relative Static Crop,Cosine Similarity,Object Detection Model,SAM 3,Detections Merge,Keypoint Detection Model,Circle Visualization,Seg Preview,Property Definition,EasyOCR,Stability AI Inpainting,Multi-Label Classification Model,Reference Path Visualization,Time in Zone,Detections Combine,Crop Visualization,Ellipse Visualization,Overlap Filter,Line Counter,Image Preprocessing,Barcode Detection,Detections List Roll-Up,Segment Anything 2 Model,Background Subtraction,Image Slicer,Image Contours,Cache Set,Depth Estimation,Pixel Color Count,Stitch Images,VLM as Classifier,Model Monitoring Inference Aggregator,Cache Get,Instance Segmentation Model,Line Counter Visualization,Morphological Transformation,Polygon Zone Visualization,Single-Label Classification Model,Email Notification,Keypoint Visualization,OCR Model,Roboflow Custom Metadata,Google Gemini,Distance Measurement,OpenAI,Color Visualization,Size Measurement,Data Aggregator,Byte Tracker,Identify Outliers,Buffer,Florence-2 Model,Google Gemini,JSON Parser,Grid Visualization,Rate Limiter,Template Matching,OpenAI,Dimension Collapse,Bounding Rectangle,Background Color Visualization,Roboflow Dataset Upload,Stability AI Outpainting,SAM 3,Triangle Visualization,Stability AI Image Generation
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"
}
}