Optimized Precios Claros Scraping Pipeline

📅 2024-10-28 — Session: Optimized Precios Claros Scraping Pipeline

🕒 16:45–17:45
🏷️ Labels: Scraping, Automation, Data_Pipeline, Precios Claros, ETL, Cloud_Computing
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The primary goal of this session was to enhance and optimize the Precios Claros scraping pipeline to improve efficiency in capturing and storing price data.

Key Activities

• Refinement of Scraping Pipeline: Enhanced the existing pipeline with structured directories and consolidation scripts to better manage datasets.
• Command Filtering: Utilized Unix grep commands to filter command history for scraping-related activities, focusing on scrapy and shub.
• Debugging Techniques: Implemented a debug-friendly command using Scrapy for efficient data collection and debugging.
• Automated Scraper Setup: Outlined a sustainable approach to automate web scraping using cloud infrastructure, error handling, and version control.
• Server Setup on GCP: Configured a cost-effective server on Google Cloud Platform for running web scrapers.
• CSV Management Automation: Developed a Python script for managing price data in CSV format, addressing price volatility and data enrichment.
• Daily ETL Optimization: Designed an advanced ETL process using Pandas for efficient price data management.
• Multiple Scrapers Execution: Set up multiple Scrapy spiders in VS Code notebooks for streamlined data processing.

Achievements

• Successfully optimized the Precios Claros scraping pipeline for daily price data capture.
• Improved data management and storage efficiency through automation and cloud solutions.
• Enhanced debugging capabilities with ipdb in various environments.

Pending Tasks

• Further testing and validation of the new ETL process.
• Continuous monitoring and logging enhancements for long-term maintenance.