Enhanced INDEC Data Pipeline with Modular Functions

• Day: 2025-09-09
• Time: 18:25 to 19:00
• Project: Dev
• Workspace: WP 2: Operational
• Status: In Progress
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Python, Data Pipeline, Modularization, Error Handling, File Management

Description

Session Goal

The session aimed to enhance the data pipeline for downloading and organizing INDEC data, focusing on modularizing functions for better maintainability and robustness.

Key Activities

• Implemented a Python function to download and organize INDEC data by year and quarter, handling ZIP/RAR files.
• Modularized the download_quarter function to include size filtering, support for ZIP and RAR formats, and clear messaging.
• Defined Python functions for fetching quarterly data and cleaning up downloaded files, including renaming and removing empty directories.
• Developed a cleanup_download_folder function to normalize the download directory, suggested for integration into cli.py.
• Updated error handling in the download_quarter() function for RAR files to improve pipeline robustness.
• Created a function to convert .dbf files to .txt, managing backups and cleaning up directories.

Achievements

• Successfully modularized the data download and organization functions, improving code clarity and robustness.
• Enhanced error handling for ZIP and RAR file extraction, allowing the pipeline to continue despite extraction issues.
• Provided comprehensive function definitions for data fetching and cleanup, ready for integration.

Pending Tasks

• Integrate the cleanup_download_folder function into the cli.py script after the fetch_range command.
• Test the full data pipeline with the new modular functions to ensure smooth operation.

Evidence

• source_file=2025-09-09.sessions.jsonl, line_number=0, event_count=0, session_id=5d4b23b53a325b33b33eaea8406c3d5bd9f758f360e52cef24fe4ab9081852d1
• event_ids: []