Enhanced GitHub Actions and Data Processing

• Day: 2024-05-26
• Time: 12:50 to 14:05
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Github Actions, Python, Automation, Data Processing, Machine Learning

Description

Session Goal

The session aimed to enhance automation workflows using GitHub Actions and improve data processing techniques in Python scripts.

Key Activities

• Implemented a solution for creating temporary directories in GitHub Actions to support file operations.
• Addressed Git push errors by integrating a workflow to pull remote changes before pushing local updates.
• Explored Git branch merge strategies, including merge, rebase, and fast-forward.
• Enhanced logging in Python data processing scripts to facilitate debugging and progress tracking.
• Updated GitHub Actions workflows to manage Python script outputs, ensuring data persistence.
• Configured Git settings within GitHub Actions for accurate commit tracking.
• Developed regression models incorporating pooled urban areas using scikit-learn.
• Simulated city code 0 in datasets using pandas and scikit-learn for better data representation.
• Created a GitHub Actions workflow to check file sizes and commit files under 50 MB.
• Automated error handling and model training processes using GitHub Actions.

Achievements

• Successfully implemented and tested multiple GitHub Actions workflows for automation.
• Improved data processing scripts with enhanced logging and error handling.
• Developed strategies for efficient dataset management and model training.

Pending Tasks

• Further refinement of GitHub Actions workflows to optimize automation processes.
• Continued development of machine learning models for the ‘Encuestador de Hogares’ project.

Evidence

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• event_ids: []