Developed Streamlit Job Search Application Pipeline

2 min read

📅 2025-07-09 — Session: Developed Streamlit Job Search Application Pipeline

🕒 21:15–21:55
🏷️ Labels: Streamlit, Job Search, Pipeline, App Development, Python
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session focused on developing and refining a job search application using Streamlit, aiming to establish a robust local-first app with a job search engine results page (SERP) pipeline.

Key Activities

  • Development Sprint Breakdown: Conducted a detailed 5-hour sprint to build the local-first app, outlining phases, goals, and components.
  • Handoff Message: Prepared a comprehensive handoff document for new assistants, clarifying script interfaces, folder organization, and UI expectations.
  • Specification Simulation: Simulated specifications for script development, detailing interfaces, dependencies, and output formats.
  • Inconsistency Clarification: Identified and addressed potential inconsistencies in the pipeline specification, focusing on metadata handling and UX considerations.
  • Metadata Management: Drafted a metadata.json format for run tracking, enhancing data management capabilities.
  • Frontend Structure: Created a modular frontend structure, ensuring clean separation of UI logic from the backend.
  • Module Definitions: Defined Python modules within the job query pipeline, detailing their interactions and functionalities.
  • Framework Comparison: Compared Streamlit and ShadCN for application development, providing recommendations for internal tools versus public apps.
  • Migration Strategy: Outlined best practices for Streamlit setup to facilitate future backend migration.
  • View Redesign: Redesigned Streamlit view files for the job search application, focusing on query, control, and results tabs.
  • Multi-Tab Interface: Provided an example of a Streamlit multi-tab interface for shared settings configuration.
  • Python Import Resolution: Resolved import issues in the project structure, ensuring proper module recognition.
  • Query Functionality Enhancement: Redesigned the render() function in query_tab.py to align with the main pipeline logic.
  • Function Implementation: Implemented the run_step() function in control_tab.py, focusing on subprocess management and UI feedback.

Achievements

  • Successfully established a comprehensive structure for the job search application pipeline.
  • Clarified and resolved specification inconsistencies, enhancing project stability.
  • Developed a modular and scalable frontend structure.

Pending Tasks

  • Further testing and refinement of the Streamlit application to ensure robustness and user-friendliness.
  • Continued development of backend migration strategies.
  • Exploration of additional UI enhancements and optimizations.

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