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:
Detections Classes Replacement,Dominant Color,Contrast Equalization,Instance Segmentation Model,Google Vision OCR,ByteTrack Tracker,PTZ Tracking (ONVIF),Grid Visualization,Identify Changes,SIFT,Trace Visualization,Twilio SMS/MMS Notification,QR Code Generator,SAM 3,GLM-OCR,Delta Filter,SORT Tracker,Perception Encoder Embedding Model,OpenAI,OpenAI,Label Visualization,Pixelate Visualization,Identify Outliers,Twilio SMS Notification,Email Notification,Corner Visualization,Background Subtraction,Mask Area Measurement,Time in Zone,Morphological Transformation,Qwen2.5-VL,SAM 3,Path Deviation,Line Counter,OpenAI,Clip Comparison,Background Color Visualization,Camera Calibration,Stability AI Outpainting,Ellipse Visualization,Detections Stitch,Dynamic Zone,VLM As Classifier,Heatmap Visualization,Velocity,Property Definition,Image Convert Grayscale,Detections Consensus,Detections Filter,Size Measurement,Cache Get,Barcode Detection,Color Visualization,Camera Focus,Rate Limiter,Image Slicer,SmolVLM2,SAM 3,Detections Combine,Polygon Visualization,Motion Detection,Blur Visualization,Qwen3-VL,LMM,Bounding Rectangle,Slack Notification,Stability AI Inpainting,Detection Event Log,Perspective Correction,Florence-2 Model,Instance Segmentation Model,Anthropic Claude,Gaze Detection,Mask Visualization,Moondream2,QR Code Detection,Image Contours,Clip Comparison,Byte Tracker,YOLO-World Model,JSON Parser,Keypoint Detection Model,Object Detection Model,Pixel Color Count,VLM As Detector,Relative Static Crop,Dynamic Crop,Line Counter,Path Deviation,Byte Tracker,Email Notification,S3 Sink,Stability AI Image Generation,Model Comparison Visualization,Absolute Static Crop,Roboflow Dataset Upload,Keypoint Visualization,CLIP Embedding Model,Buffer,First Non Empty Or Default,Model Monitoring Inference Aggregator,Reference Path Visualization,Cache Set,Halo Visualization,OCR Model,SIFT Comparison,VLM As Classifier,Time in Zone,Detections Stabilizer,Expression,VLM As Detector,Image Preprocessing,Crop Visualization,Classification Label Visualization,Local File Sink,Qwen3.5-VL,Stitch OCR Detections,Stitch Images,Time in Zone,Stitch OCR Detections,LMM For Classification,Environment Secrets Store,EasyOCR,CSV Formatter,Image Threshold,Anthropic Claude,Single-Label Classification Model,Google Gemini,Halo Visualization,CogVLM,Roboflow Custom Metadata,OpenAI,Single-Label Classification Model,Triangle Visualization,Semantic Segmentation Model,Image Blur,Depth Estimation,Detections Transformation,Dimension Collapse,SIFT Comparison,Overlap Filter,Text Display,Data Aggregator,Anthropic Claude,Dot Visualization,Template Matching,Keypoint Detection Model,Florence-2 Model,Circle Visualization,Cosine Similarity,Multi-Label Classification Model,Google Gemini,Detections Merge,Detections List Roll-Up,Icon Visualization,Camera Focus,Detection Offset,Polygon Visualization,Webhook Sink,Polygon Zone Visualization,Google Gemini,Roboflow Dataset Upload,Distance Measurement,Llama 3.2 Vision,Seg Preview,Object Detection Model,Image Slicer,Byte Tracker,Line Counter Visualization,Continue If,Multi-Label Classification Model,OC-SORT Tracker,Bounding Box Visualization,Segment Anything 2 Model - outputs:
Detections Classes Replacement,Dominant Color,Instance Segmentation Model,ByteTrack Tracker,PTZ Tracking (ONVIF),Contrast Equalization,Google Vision OCR,Grid Visualization,Identify Changes,Trace Visualization,SIFT,Twilio SMS/MMS Notification,QR Code Generator,SAM 3,GLM-OCR,Delta Filter,SORT Tracker,Perception Encoder Embedding Model,OpenAI,OpenAI,Identify Outliers,Pixelate Visualization,Twilio SMS Notification,Label Visualization,Email Notification,Corner Visualization,Background Subtraction,Mask Area Measurement,Time in Zone,Qwen2.5-VL,Morphological Transformation,SAM 3,Path Deviation,Line Counter,OpenAI,Clip Comparison,Background Color Visualization,Camera Calibration,Stability AI Outpainting,Ellipse Visualization,Detections Stitch,Dynamic Zone,VLM As Classifier,Heatmap Visualization,Velocity,Image Convert Grayscale,Detections Consensus,Property Definition,Detections Filter,Size Measurement,Cache Get,Barcode Detection,Color Visualization,Camera Focus,Rate Limiter,Image Slicer,SmolVLM2,SAM 3,Detections Combine,Polygon Visualization,Motion Detection,Blur Visualization,Qwen3-VL,LMM,Bounding Rectangle,Slack Notification,Stability AI Inpainting,Detection Event Log,Instance Segmentation Model,Florence-2 Model,Perspective Correction,Anthropic Claude,Gaze Detection,Mask Visualization,Moondream2,QR Code Detection,Image Contours,Clip Comparison,Byte Tracker,YOLO-World Model,JSON Parser,Keypoint Detection Model,Object Detection Model,VLM As Detector,Pixel Color Count,Path Deviation,Dynamic Crop,Line Counter,Relative Static Crop,Byte Tracker,Email Notification,S3 Sink,Stability AI Image Generation,Model Comparison Visualization,Absolute Static Crop,Roboflow Dataset Upload,Keypoint Visualization,CLIP Embedding Model,Buffer,First Non Empty Or Default,Model Monitoring Inference Aggregator,Reference Path Visualization,Cache Set,Halo Visualization,OCR Model,SIFT Comparison,VLM As Classifier,Time in Zone,Detections Stabilizer,Expression,VLM As Detector,Image Preprocessing,Crop Visualization,Classification Label Visualization,Local File Sink,Qwen3.5-VL,Stitch OCR Detections,Stitch Images,Time in Zone,Stitch OCR Detections,LMM For Classification,EasyOCR,CSV Formatter,Single-Label Classification Model,Anthropic Claude,Image Threshold,Google Gemini,Halo Visualization,Roboflow Custom Metadata,CogVLM,OpenAI,Single-Label Classification Model,Triangle Visualization,Semantic Segmentation Model,Image Blur,Depth Estimation,Detections Transformation,Dimension Collapse,SIFT Comparison,Overlap Filter,Text Display,Data Aggregator,Anthropic Claude,Dot Visualization,Template Matching,Keypoint Detection Model,Florence-2 Model,Circle Visualization,Cosine Similarity,Multi-Label Classification Model,Google Gemini,Detections Merge,Icon Visualization,Detections List Roll-Up,Camera Focus,Detection Offset,Polygon Visualization,Webhook Sink,Polygon Zone Visualization,Google Gemini,Roboflow Dataset Upload,Distance Measurement,Llama 3.2 Vision,Seg Preview,Object Detection Model,Image Slicer,Byte Tracker,Line Counter Visualization,Continue If,Multi-Label Classification Model,OC-SORT Tracker,Bounding Box Visualization,Segment Anything 2 Model
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"
}
}