Optimized and Executed Debt Management Scripts

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Optimized and Executed Debt Management Scripts

  • Day: 2026-03-27
  • Time: 22:30 to 22:50
  • Project: Dev
  • Workspace: WP 2: Operational
  • Status: In Progress
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Python, Debt Management, Script Optimization, Data Analysis

Description

Session Goal

The session aimed to optimize and execute scripts related to debt management, focusing on improving the efficiency of the resolve_internal_debt.py script, running accounting pipelines, and exploring debt datasets.

Key Activities

  • Script Optimization: Reorganized the resolve_internal_debt.py script to align with canonical ingestion workflows, enhancing import structures and column handling for better performance.
  • Pipeline Execution: Executed an accounting pipeline using Google Sheets, including live runs and local testing, with detailed command explanations.
  • Data Exploration: Imported and explored debt datasets using pandas, analyzing open items and repayment events.
  • Data Aggregation: Grouped and aggregated debt data by debtor, creditor, and currency, calculating counts and sums.
  • Algorithm Analysis: Reflected on debt management algorithm results, identifying issues with repayment allocations and proposing improvements.
  • Ledger Filtering Strategy: Developed a filtering strategy for financial ledgers to categorize debts and repayments based on transaction status.
  • Script Viewing and Extraction: Utilized bash and sed to view and extract specific lines from the resolve_internal_debt.py script.
  • Script Update: Updated the debt resolution script to improve debt categorization and added new output files.

Achievements

  • Successfully optimized the resolve_internal_debt.py script for better efficiency.
  • Executed the accounting pipeline with Google Sheets, verifying the integration and output.
  • Completed initial data exploration and aggregation of debt datasets.
  • Proposed actionable improvements for the debt management algorithm.

Pending Tasks

  • Further testing of the updated debt resolution script to ensure accuracy and performance enhancements.
  • Implementation of proposed improvements in the debt management algorithm.

Evidence

  • source_file=2026-03-27.sessions.jsonl, line_number=3, event_count=0, session_id=9dbd619a298ac219771d30ad1d267c3cf4d1d4007794eaf538bd39500e5f3cf1
  • event_ids: []

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