Excel Processors

Note

Excel processors are deprecated and should not be used for new models. Use Data Processors instead, which supersede excel processors with a more general transformation model that works across all supported data sources.

Overview

Excel processors are Excel workbooks that take the data from the model and transform it into a form the model can consume directly. A processor embeds Excel formulas into its output sheets so that each cell’s value is resolved at import time.

Setting up a Processor

Use ExcelTransformConfig from daitum_configuration to declare an Excel data source. Each instance maps one or more source sheets in the uploaded workbook to target sheets in the model.

import daitum_configuration as cg

example_processor = cg.ExcelTransformConfig(
     file_key="Processor",
     file_name="Processor.xlsx",
     sheet_mapping=[
         ("Sheet_Name_1", "Model_Table_Name_1"),
         ("Sheet_Name_2", "Model_Table_Name_2"),
     ],
 )
 example_processor.set_manual_sheet_names(True)
 example_processor.set_debug_file(True)

Each element of sheet_mapping is a (source_sheet, target_sheet) pair. The source sheet name is the tab in the uploaded workbook; the target sheet name is the model table that receives the rows.

set_manual_sheet_names(True) tells the platform to resolve tab names literally rather than through its auto-discovery logic.

set_debug_file(True) enables debugging of the processor calculations.

Migration

If you have an existing model that relies on excel processors, migrate to data processors:

Replace excel processor definitions with the equivalent data processor configuration.
Update input mappings to reference the standard data source bindings rather than Excel-specific ones.
Re-validate downstream tables to confirm processed outputs match the previous behaviour.

See the Data Processors tutorial for the current approach.

Next Steps

Continue with the Data Processors tutorial to learn the current data transformation workflow.