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