📅 2025-07-07 — Session: Implemented and Debugged Job Data Pipeline
🕒 02:05–02:55
🏷️ Labels: SERP, Promptflow, Python, Scraping, Pipeline
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The primary objective of this session was to implement and debug a job data pipeline using SERP and PromptFlow technologies.
Key Activities
- Updated SERP query logic to replace stub functions with real SerpAPI scraping logic.
- Developed a scraping flow for job offers using PromptFlow and Spider.cloud, aiming to process CSV files and generate JSONL files for annotation.
- Implemented a structured pipeline for Spider.cloud, detailing steps with inputs, outputs, and command diagnostics.
- Completed and refined the
01_fetch_serp.pyscript for Spider API integration, including logging and data output management. - Provided a comprehensive overview of the job posting automation pipeline.
- Fixed column mapping issues in YAML configuration files, addressing duplicate keys and mismatched JSONL field names.
- Resolved PromptFlow column mapping errors by normalizing JSONL fields and updating configurations.
- Debugged Python scripts to handle JSONL field name mismatches and output handling issues in PromptFlow.
Achievements
- Successfully replaced mock queries with real implementations in the job data pipeline.
- Corrected configuration errors and ensured compatibility between JSONL and YAML files.
- Enhanced PromptFlow scripts to handle outputs more effectively.
Pending Tasks
- Further testing of the pipeline with diverse datasets to ensure robustness.
- Continuous monitoring and adjustment of the pipeline for optimal performance.