DataBeak

Instructions

Implementation Reference

• src/databeak/servers/row_operations_server.py:509-550 (handler)

  The core handler function implementing the delete_row tool. It validates the row index, captures the deleted row's data, removes the row from the DataFrame, updates the session, and returns a detailed result.

  def delete_row(
      ctx: Annotated[Context, Field(description="FastMCP context for session access")],
      row_index: Annotated[int, Field(description="Row index (0-based) to delete")],
  ) -> DeleteRowResult:
      """Delete row at specified index with comprehensive tracking.
  
      Captures deleted data for undo operations. Returns operation result with before/after
      statistics.
      """
      session_id = ctx.session_id
      session, df = get_session_data(session_id)
      rows_before = len(df)
  
      # Validate row index
      if row_index < 0 or row_index >= len(df):
          msg = f"Row index {row_index} out of range (0-{len(df) - 1})"
          raise ToolError(msg)
  
      # Get the data that will be deleted for tracking
      deleted_data = df.iloc[row_index].to_dict()
  
      # Handle pandas/numpy types for JSON serialization
      for key, value in deleted_data.items():
          if pd.isna(value):
              deleted_data[key] = None
          elif hasattr(value, "item"):  # numpy scalar
              deleted_data[key] = value.item()
  
      # Delete the row
      df_new = df.drop(df.index[row_index]).reset_index(drop=True)
  
      # Update session data
      session.df = df_new
  
      # No longer recording operations (simplified MCP architecture)
  
      return DeleteRowResult(
          row_index=row_index,
          rows_before=rows_before,
          rows_after=len(df_new),
          deleted_data=deleted_data,
      )

• src/databeak/models/tool_responses.py:155-162 (schema)

  Pydantic model defining the output schema and structure for the delete_row tool response.

  class DeleteRowResult(BaseToolResponse):
      """Response model for row deletion operations."""
  
      operation: str = Field(default="delete_row", description="Operation type identifier")
      row_index: int = Field(description="Index of deleted row")
      rows_before: int = Field(description="Row count before deletion")
      rows_after: int = Field(description="Row count after deletion")
      deleted_data: dict[str, CsvCellValue] = Field(description="Data from the deleted row")

• src/databeak/servers/row_operations_server.py:650-650 (registration)

  Registers the delete_row function as an MCP tool with the name 'delete_row' on the row_operations_server.

  row_operations_server.tool(name="delete_row")(delete_row)