📅 2025-12-27 — Session: Refactored Runner and Policy Modules for Intent Execution
🕒 21:30–22:20
🏷️ Labels: Runner Design, Intent Execution, Policy Management, Python, Automation
📂 Project: Dev
Session Goal
The session aimed to refine and enhance the design and functionality of data processing runners and policy modules, focusing on transitioning to an intent-based processing model.
Key Activities
- Refinement of Runner Design: Transitioned the runner from a row-targeted to an intent-targeted model, involving strategic decisions and structural adjustments.
- Policy Module Development: Created a Python module for managing project execution intents, including handling capabilities and scheduling.
- Runner Refactoring: Simplified the runner script to focus on intent execution and logging, ensuring stability in project metadata.
- Google Sheets API Integration: Developed a lean Python module for efficient interaction with the Google Sheets API.
- Adversarial Code Review: Conducted a review of the policy runner, identifying potential issues and recommending improvements.
- Debugging with compute_effective_runset: Implemented a verbose, instrumented version to track data flow and debug issues.
- Command Line Argument Parsing: Discussed the use of argparse for handling command line inputs in scripts.
- Policy and Metadata Integration: Addressed challenges in integrating policy and metadata, focusing on schema mismatches.
Achievements
- Completed the transition to an intent-based runner model.
- Developed and integrated policy modules for project management.
- Improved code stability and functionality through refactoring and review.
Pending Tasks
- Resolve schema mismatches in policy and metadata integration to prevent execution failures.