feat(frontend): Support for UDF Ui Parameter

amber/src/main/python/core/models/schema/attribute_type.py

@@ -22,7 +22,6 @@
 from pyarrow import lib
 from core.models.type.large_binary import largebinary
 
-
 class AttributeType(Enum):
     """
     Types supported by PyTexera & PyAmber.
@@ -78,6 +77,17 @@ class AttributeType(Enum):
 }
 
 
+FROM_STRING_PARSER_MAPPING = {
+    AttributeType.STRING: str,
+    AttributeType.INT: int,
+    AttributeType.LONG: int,
+    AttributeType.DOUBLE: float,
+    AttributeType.BOOL: lambda v: str(v).strip().lower() in ("True", "true", "1", "yes"),
+    AttributeType.BINARY: lambda v: v if isinstance(v, bytes) else str(v).encode(),
+    AttributeType.TIMESTAMP: lambda v: datetime.datetime.fromisoformat(v),
+    AttributeType.LARGE_BINARY: largebinary,
+}
+
 # Only single-directional mapping.
 TO_PYOBJECT_MAPPING = {
     AttributeType.STRING: str,

amber/src/main/python/pyamber/__init__.py

@@ -27,6 +27,7 @@
     SourceOperator,
     TupleOperatorV2,
     State,
+    AttributeType,
 )
 
 __all__ = [
@@ -41,4 +42,5 @@
     "TupleOperatorV2",
     "SourceOperator",
     "State",
+    "AttributeType",
 ]

amber/src/main/python/pytexera/__init__.py

@@ -30,6 +30,7 @@
     UDFSourceOperator,
 )
 from core.models.type.large_binary import largebinary
+from core.models.schema.attribute_type import *
 
 __all__ = [
     "State",
@@ -53,4 +54,5 @@
     "Iterator",
     "Optional",
     "Union",
+    "AttributeType",
 ]

amber/src/main/python/pytexera/udf/udf_operator.py

@@ -16,12 +16,76 @@
 # under the License.
 
 from abc import abstractmethod
-from typing import Iterator, Optional, Union
-
-from pyamber import *
+from typing import Any, Dict, Iterator, Optional, Union
 
+import functools
 
-class UDFOperatorV2(TupleOperatorV2):
+from pyamber import *
+from core.models.schema.attribute_type import AttributeType, FROM_STRING_PARSER_MAPPING
+
+class _UiParameterSupport:
+    _ui_parameter_injected_values: Dict[str, Any] = {}
+    _ui_parameter_name_types: Dict[str, AttributeType] = {}
+
+    # Reserved hook name. Backend injector will generate this in the user's class.
+    def _texera_injected_ui_parameters(self) -> Dict[str, Any]:
+        return {}
+
+    def _texera_apply_injected_ui_parameters(self) -> None:
+        values = self._texera_injected_ui_parameters()
+        # Write to base class storage (not cls) because UiParameter reads from _UiParameterSupport directly
+        _UiParameterSupport._ui_parameter_injected_values = dict(values or {})
+        _UiParameterSupport._ui_parameter_name_types = {}
+
+    def __init_subclass__(cls, **kwargs):
+        super().__init_subclass__(**kwargs)
+
+        # Wrap only methods defined on this class (not inherited ones)
+        original_open = getattr(cls, "open", None)
+        if original_open is None:
+            return
+
+        # Avoid double wrapping
+        if getattr(original_open, "__texera_ui_params_wrapped__", False):
+            return
+
+        @functools.wraps(original_open)
+        def wrapped_open(self, *args, **kwargs):
+            self._texera_apply_injected_ui_parameters()
+            return original_open(self, *args, **kwargs)
+
+        setattr(wrapped_open, "__texera_ui_params_wrapped__", True)
+        cls.open = wrapped_open
+
+    class UiParameter:
+        def __init__(self, name: str, type: AttributeType):
+            if not isinstance(type, AttributeType):
+                raise TypeError(
+                    f"UiParameter.type must be an AttributeType, got {type!r}."
+                )
+
+            existing_type = _UiParameterSupport._ui_parameter_name_types.get(name)
+            if existing_type is not None and existing_type != type:
+                raise ValueError(
+                    f"Duplicate UiParameter name '{name}' with conflicting types: "
+                    f"{existing_type.name} vs {type.name}."
+                )
+
+            _UiParameterSupport._ui_parameter_name_types[name] = type
+            raw_value = _UiParameterSupport._ui_parameter_injected_values.get(name)
+            self.name = name
+            self.type = type
+            self.value = _UiParameterSupport._parse(raw_value, type)
+
+    @staticmethod
+    def _parse(value: Any, attr_type: AttributeType) -> Any:
+        if value is None:
+            return None
+
+        py_type = FROM_STRING_PARSER_MAPPING.get(attr_type)
+        return py_type(value)
+
+class UDFOperatorV2(_UiParameterSupport, TupleOperatorV2):
     """
     Base class for tuple-oriented user-defined operators. A concrete implementation must
     be provided upon using.
@@ -65,7 +129,7 @@ def close(self) -> None:
         pass
 
 
-class UDFSourceOperator(SourceOperator):
+class UDFSourceOperator(_UiParameterSupport, SourceOperator):
     def open(self) -> None:
         """
         Open a context of the operator. Usually can be used for loading/initiating some
@@ -90,7 +154,7 @@ def close(self) -> None:
         pass
 
 
-class UDFTableOperator(TableOperator):
+class UDFTableOperator(_UiParameterSupport, TableOperator):
     """
     Base class for table-oriented user-defined operators. A concrete implementation must
     be provided upon using.
@@ -123,7 +187,7 @@ def close(self) -> None:
         pass
 
 
-class UDFBatchOperator(BatchOperator):
+class UDFBatchOperator(_UiParameterSupport, BatchOperator):
     """
     Base class for batch-oriented user-defined operators. A concrete implementation must
     be provided upon using.

common/workflow-core/src/main/scala/org/apache/texera/amber/core/tuple/Attribute.java

@@ -21,6 +21,10 @@
 
 import com.fasterxml.jackson.annotation.JsonCreator;
 import com.fasterxml.jackson.annotation.JsonProperty;
+import org.apache.texera.amber.pybuilder.EncodableStringAnnotation;
+import org.apache.texera.amber.pybuilder.PyStringTypes;
+import org.apache.texera.amber.pybuilder.PyStringTypes.EncodableStringFactory$;
+
 
 import javax.validation.constraints.NotBlank;
 import javax.validation.constraints.NotNull;
@@ -49,6 +53,7 @@ public Attribute(
 
     @JsonProperty(value = "attributeName", required = true)
     @NotBlank(message = "Attribute name is required")
+    @EncodableStringAnnotation
     public String getName() {
         return attributeName;
     }

common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/udf/python/DualInputPortsPythonUDFOpDescV2.scala

@@ -77,6 +77,11 @@ class DualInputPortsPythonUDFOpDescV2 extends LogicalOp {
   )
   var outputColumns: List[Attribute] = List()
 
+  @JsonProperty
+  @JsonSchemaTitle("Parameters")
+  @JsonPropertyDescription("Parameters inferred from self.UiParameter(...) in Python script")
+  var uiParameters: List[UiUDFParameter] = List()
+
   override def getPhysicalOp(
       workflowId: WorkflowIdentity,
       executionId: ExecutionIdentity
@@ -88,7 +93,7 @@ class DualInputPortsPythonUDFOpDescV2 extends LogicalOp {
           workflowId,
           executionId,
           operatorIdentifier,
-          OpExecWithCode(code, "python")
+          OpExecWithCode(PythonUdfUiParameterInjector.inject(code, uiParameters), "python")
         )
         .withParallelizable(true)
         .withSuggestedWorkerNum(workers)
@@ -98,7 +103,7 @@ class DualInputPortsPythonUDFOpDescV2 extends LogicalOp {
           workflowId,
           executionId,
           operatorIdentifier,
-          OpExecWithCode(code, "python")
+          OpExecWithCode(PythonUdfUiParameterInjector.inject(code, uiParameters), "python")
         )
         .withParallelizable(false)
     }

common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/udf/python/PythonUDFOpDescV2.scala

@@ -79,6 +79,11 @@ class PythonUDFOpDescV2 extends LogicalOp {
   )
   var outputColumns: List[Attribute] = List()
 
+  @JsonProperty
+  @JsonSchemaTitle("Parameters")
+  @JsonPropertyDescription("Parameters inferred from self.UiParameter(...) in Python script")
+  var uiParameters: List[UiUDFParameter] = List()
+
   override def getPhysicalOp(
       workflowId: WorkflowIdentity,
       executionId: ExecutionIdentity
@@ -118,7 +123,7 @@ class PythonUDFOpDescV2 extends LogicalOp {
           workflowId,
           executionId,
           operatorIdentifier,
-          OpExecWithCode(code, "python")
+          OpExecWithCode(PythonUdfUiParameterInjector.inject(code, uiParameters), "python")
         )
         .withParallelizable(true)
         .withSuggestedWorkerNum(workers)
@@ -128,7 +133,7 @@ class PythonUDFOpDescV2 extends LogicalOp {
           workflowId,
           executionId,
           operatorIdentifier,
-          OpExecWithCode(code, "python")
+          OpExecWithCode(PythonUdfUiParameterInjector.inject(code, uiParameters), "python")
         )
         .withParallelizable(false)
     }