Refactored EDA pipeline for tag normalization

• Day: 2025-09-18
• Time: 16:45 to 18:12
• Project: Dev
• Workspace: WP 2: Operational
• Status: In Progress
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: EDA, Tag Normalization, Refactoring, Python, CLI

Description

Session Goal

The session aimed to enhance the exploratory data analysis (EDA) pipeline by addressing technical issues and improving the tag normalization process.

Key Activities

• Morning Session Review: Reflected on previous activities, focusing on technical troubleshooting and tool-building.
• EDA Execution: Implemented EDA on units from May to August using CLI tools, with detailed instructions for balanced, lax, and strict passes.
• Error Handling: Addressed an AttributeError in the EDA pipeline by patching the eda_bridge.py file to normalize input.
• Code Refactoring: Refactored the eda_bridge module and consolidated tag contracts in normalize.py to streamline tag parsing and canonicalization.
• Namespace Mapping: Decided on a namespace aliasing strategy to improve clarity and extensibility.
• Schema and Value Normalization: Developed a structured approach for normalizing schema and value drifts in data processing.
• Critical Code Review: Conducted a thorough review of the EDA process, identifying critical issues and recommending improvements.

Achievements

• Successfully refactored the EDA pipeline to improve tag normalization and error handling.
• Established a clear strategy for namespace aliasing and schema normalization.
• Improved code quality through critical reviews and refactoring.

Pending Tasks

• Further testing of the refactored pipeline to ensure robustness and performance.
• Implementation of suggested code improvements from the critical review.

Evidence

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• event_ids: []