π 2025-07-07 β Session: Enhanced Data Processing Pipeline
π 05:35β06:25
π·οΈ Labels: Data_Pipeline, Automation, Python, Error_Handling, Integration
π Project: Dev
β Priority: MEDIUM
Session Goal
To improve and integrate various components of a data processing pipeline, ensuring robustness, compatibility, and efficiency.
Key Activities
- Pipeline Fixes: Addressed column name mismatches and directory misalignments to ensure smooth script execution.
- Error Handling: Implemented strategies to prevent the creation of empty CSV files, modifying three scripts for better error handling.
- Integration: Merged a JSONL exporter with a Selenium scraper, allowing for seamless data export without overwriting existing files.
- Workflow Refinement: Transitioned job scraping and classification to a selective model, improving efficiency by scraping only high-quality job postings.
- Orchestrator Design: Developed a modular orchestrator for pipeline execution, transforming existing scripts into a flexible driver with configurable paths.
- Script Enhancement: Updated the
02_label_and_score.py
script for orchestrator compatibility usingargparse
and functional wrapping. - Pipeline Integration: Integrated a JSONL export step, updating the orchestratorβs workflow to convert CSV data into JSONL format.
Achievements
- Successfully integrated and enhanced multiple components of the data processing pipeline.
- Improved error handling and compatibility across scripts.
Pending Tasks
- Further testing and validation of the integrated pipeline components.
- Exploration of additional enhancements for future scalability.