I can run simple workflow

src/workflow/engine.py

@@ -1,6 +1,9 @@
 from abc import ABC, abstractmethod
 from typing import Any, Generator
 
+from core.Expando import Expando
+from utils.Datahelper import DataHelper
+
 
 class DataProcessor(ABC):
   """Base class for all data processing components."""
@@ -47,6 +50,45 @@ class DataPresenter(DataProcessor):
     yield self.present(data)
 
 
+class TableDataProducer(DataProducer):
+  """Base class for data producers that emit data from a repository."""
+  
+  def __init__(self, session, settings_manager, repository_name, table_name):
+    self._session = session
+    self.settings_manager = settings_manager
+    self.repository_name = repository_name
+    self.table_name = table_name
+  
+  def emit(self, data: Any = None) -> Generator[Any, None, None]:
+    yield from DataHelper.get(self._session, self.settings_manager, self.repository_name, self.table_name, Expando)
+
+
+class DefaultDataPresenter(DataPresenter):
+  """Default data presenter that returns the input data unchanged."""
+  
+  def __init__(self, columns_as_str: str):
+    super().__init__()
+    if not columns_as_str or columns_as_str == "*":
+      self.mappings = None
+    
+    else:
+      
+      self.mappings = {}
+      temp_mappings = [col.strip() for col in columns_as_str.split(",")]
+      for mapping in temp_mappings:
+        if "=" in mapping:
+          key, value = mapping.split("=")
+          self.mappings[key] = value
+        else:
+          self.mappings[mapping] = mapping
+  
+  def present(self, data: Any) -> Any:
+    if self.mappings is None:
+      return data
+    
+    return Expando(data.to_dict(self.mappings))
+
+
 class WorkflowEngine:
   """Orchestrates the data processing pipeline using generators."""
   
@@ -93,4 +135,3 @@ class WorkflowEngine:
     Use this method when you need all results at once.
     """
     return list(self.run())
-