Implemented and Debugged Python Data Processing Modules

📅 2025-09-15 — Session: Implemented and Debugged Python Data Processing Modules

🕒 14:50–16:30
🏷️ Labels: Python, Data Processing, Automation, Debugging, CLI
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal: The session aimed to implement and debug Python modules for data processing, specifically focusing on L3 selection, publishing, and EDA command troubleshooting.

Key Activities:

• Developed two Python modules: select_l3_daily for filtering and scoring units, and publish_l2 for mirroring validated MDX files.
• Conducted an end-to-end pilot for data ingestion and processing, including setting up a workflow for data ingestion, processing, and digest generation.
• Troubleshot issues with EDA commands in a Python CLI, addressing command naming conventions and ensuring non-empty input.
• Debugged a KeyError in the eda-tagpairs-from-units function due to an empty units file.
• Created bootstrap commands for generating tag-pair and session digests, bypassing existing pipeline issues.
• Resolved an error in event loading by applying code patches for compatibility with dataclass instances and dictionaries.
• Fixed a schema mismatch in the Unit dataclass by implementing a patch in the bags_pipeline/quick.py file.
• Developed a playbook for log processing, transforming trial-and-error methods into a streamlined workflow.

Achievements:

• Successfully implemented and debugged multiple Python modules and workflows for data processing.
• Enhanced the robustness of the data processing pipeline through targeted debugging and error resolution.

Pending Tasks:

• Further testing and validation of the implemented modules and workflows in a production environment.