πŸ“… 2025-07-10 β€” Session: Refactored Streamlit App for Job Search Visualization

πŸ•’ 00:00–23:50
🏷️ Labels: Streamlit, Python, Data Visualization, Job Search, Refactoring
πŸ“‚ Project: Dev
⭐ Priority: MEDIUM

Session Goal

The primary goal of this session was to enhance the functionality and user experience of a Streamlit application designed for job search visualization. This involved refactoring the application structure, improving error handling, and integrating new features for data display and interactivity.

Key Activities

  • Streamlit Logging Best Practices: Reviewed methods to ensure visibility of print() statements and subprocess logs in the terminal during Streamlit app execution.
  • Structured Output for Job Recommendations: Planned a structured approach for displaying job recommendations using tables and heatmaps.
  • Streamlit App UX and Data Display: Implemented a structured approach for building a Streamlit app with features like file selection, data loading, and match summaries using JSONL files.
  • Configuration Error Resolution: Addressed a common Streamlit configuration error by adjusting the script order.
  • Refactoring with render_results_page() Function: Introduced a function to enhance clarity and functionality, focusing on modular design.
  • Compact Table View for Job Match Results: Developed a compact table view for job matches using DataFrame format.
  • Live Editing Jinja2 Template: Added a feature for live editing of Jinja2 templates within the Streamlit app.
  • JSON Editor Integration: Explored and implemented JSON editor alternatives for Streamlit, including schema-guided editable tabs.

Achievements

  • Successfully refactored the Streamlit application to improve maintainability and user experience.
  • Enhanced the application’s data visualization capabilities with new structured views and interactivity.
  • Resolved configuration errors and improved the app’s startup sequence.
  • Integrated a live editing feature for Jinja2 templates, enhancing flexibility for users.

Pending Tasks

  • Further testing and validation of the JSON editor integration.
  • Optimization of the job recommendation display logic to ensure clarity and usability.
  • Continued refinement of error handling and logging practices.