Refactored Python CLI and Data Processing Pipeline

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šŸ“… 2025-09-18 ā€” Session: Refactored Python CLI and Data Processing Pipeline

šŸ•’ 01:00ā€“02:30
šŸ·ļø Labels: Python, CLI, Data Processing, Refactoring, JSON
šŸ“‚ Project: Dev
ā­ Priority: MEDIUM

Session Goal

The primary aim was to refactor and enhance the Python CLI and data processing pipeline to improve modularity, efficiency, and maintainability.

Key Activities

  • Refactoring JSON Handling: Improved the handling of JSON data by separating CLI from backend processes and resolving import issues.
  • Utility Function Development: Created a utility function expand_globs for efficient file loading using glob patterns.
  • DateTime Conversion Enhancement: Revised a Python function for converting timestamps to UTC datetime objects, fixing issues with offsets and ā€˜Zā€™ characters.
  • Command Structure Refactoring: Planned and initiated the reorganization of data processing commands into a core library of pure functions and CLI entry points.
  • Pipeline Deliverables: Outlined deliverables using KBCTL commands for data processing, including digests and summaries.
  • L2 Digests Function Implementation: Developed and implemented the build_l2_digests function for processing JSONL files and generating digests.
  • Indexing Events and Sessions: Built Python functions for indexing events and sessions, enhancing data accessibility and organization.

Achievements

  • Successfully refactored the CLI and backend processes, improving code separation and import resolution.
  • Developed utility functions for file handling and datetime conversion, enhancing the robustness of the pipeline.
  • Implemented new functions for data processing and indexing, contributing to a more organized and efficient workflow.

Pending Tasks

  • Complete the integration of the refactored command structure into the existing system.
  • Further testing and validation of the new indexing and digest functions to ensure reliability.

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