Refactored and Enhanced Ledger Normalization Function

• Day: 2026-03-27
• Time: 22:50 to 23:05
• Project: Dev
• Workspace: WP 2: Operational
• Status: In Progress
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Python, Dataframe, Refactoring, Ledger, Script, Error_Handling

Description

Session Goal

The primary goal of this session was to refactor and enhance the _normalize_ledger_columns function in a Python script to improve data normalization, handle duplicate columns, and ensure robust error handling in ledger processing.

Key Activities

• Utilized bash and sed commands to extract and number specific lines from a Python script for analysis.
• Implemented a Python script using pandas to read CSV column names, facilitating data processing tasks.
• Refactored the _normalize_ledger_columns function to improve alias handling and ensure required columns are present in the DataFrame.
• Addressed and resolved issues with duplicate column names in the DataFrame by correcting the renaming logic in the script.
• Conducted tests to verify the script’s functionality and correctness after refactoring.

Achievements

• Successfully refactored the _normalize_ledger_columns function, enhancing its robustness and efficiency.
• Resolved duplicate column issues, preventing potential errors in ledger processing.

Pending Tasks

• Further testing with diverse datasets to ensure the refactored function handles all edge cases effectively.
• Documentation updates to reflect changes in the script and usage instructions.

Evidence

• source_file=2026-03-27.sessions.jsonl, line_number=2, event_count=0, session_id=7db22dedeb09d6b080ed014867aa46de5b008d2b5cad2d082dcf22678e10b25c
• event_ids: []