📅 2025-12-30 — Session: Developed JSON Data Processing and Artifact Management
🕒 15:55–16:15
🏷️ Labels: JSON, Data Ingestion, Artifact Management, Python, Debugging
📂 Project: Dev
Session Goal
The session aimed to enhance data processing capabilities by loading JSON data, inspecting data structures, and planning an artifact management system.
Key Activities
- JSON Data Loading: Implemented a script to load JSON data from specified file paths, facilitating data ingestion and processing.
- Data Structure Inspection: Analyzed keys from ‘manifest.json’ and ‘ingest_manifest.json’ to understand partitions, aggregates, outputs, and modes.
- Artifact Management Planning: Developed a plan for managing data artifacts, including naming conventions and directory structures to optimize workflow.
- Python Project Architecture: Established a concrete architecture for a Python project, detailing filesystem layout, Makefile targets, and stage entry points.
- Debugging Reports Script: Addressed issues in the ‘reports.py’ script, focusing on argument parsing and identifying a bug in the summary_paths variable.
- Ingest Manifest Queries: Formulated queries regarding the ingestion of manifest JSON files, focusing on input hash and schema columns.
Achievements
- Successfully loaded and inspected JSON data structures.
- Outlined a comprehensive plan for artifact management.
- Defined a structured architecture for Python project development.
Pending Tasks
- Further debugging of the ‘reports.py’ script to resolve identified issues.
- Implementation of the artifact management system as per the outlined plan.