Implemented and Optimized Web Scraping and Data Export

2 min read

Implemented and Optimized Web Scraping and Data Export

  • Day: 2025-06-05
  • Time: 06:30 to 07:20
  • Project: Dev
  • Workspace: WP 2: Operational
  • Status: Completed
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Selenium, Python, JSONL, Data Processing, Web Scraping

Description

Session Goal

The session focused on setting up a Selenium-based web scraping pipeline, resolving clipboard issues on Linux, exporting data to JSONL format, and improving data processing scripts.

Key Activities

  • Selenium Web Scraping Setup: Implemented a Selenium-based web scraping pipeline to capture dynamic content from web pages using clipboard actions.
  • Clipboard Management: Addressed clipboard interaction issues on Linux with Pyperclip by installing xclip or xsel.
  • Data Export: Exported DataFrame to JSONL format, evaluated JSONL for job data storage, and implemented batch processing and hashing for JSONL exports.
  • Pandas File Operations: Managed JSONL and CSV file operations using pandas, ensuring consistent naming conventions and organizing output files.
  • CSV Review and Script Updates: Reviewed CSV structure, suggested improvements, and updated scripts for SERP data processing, including HTML decoding and CSV output consistency.
  • Code Refactoring: Refactored batch processing logic to eliminate code duplication and improve clarity.

Achievements

Pending Tasks

  • Further evaluate the effectiveness of JSONL format for other data types.
  • Continue refining data processing scripts for efficiency and clarity.

Evidence

  • source_file=2025-06-05.sessions.jsonl, line_number=4, event_count=0, session_id=026f90be3913e9c6e6c033a5e233cc2c75d0bc3a34501f918f636a6a99c7e563
  • event_ids: []

Graph View

Backlinks