Enhanced Precios Claros Scraping Pipeline

• Day: 2024-10-28
• Time: 16:45 to 17:45
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Scraping, Automation, Data_Pipeline, Debugging, Cloud_Infrastructure

Description

Session Goal

The session aimed to enhance the Precios Claros scraping pipeline to improve efficiency in capturing and storing daily price data.

Key Activities

• Refined and optimized the scraping pipeline with steps for automation, data consolidation, duplicate handling, and documentation.
• Utilized Unix grep commands to filter command history for scraping-related commands, focusing on scrapy and shub.
• Developed a debug-friendly scraping command using Scrapy for efficient debugging with specific store IDs.
• Employed ipdb for debugging Python scripts by inspecting variables and continuing execution.
• Set up an automated scraper using cloud infrastructure with error handling and long-term maintenance strategies.
• Configured a cost-effective server on Google Cloud Platform for running web scrapers, including VM configuration and scheduling.
• Analyzed recent scraping job results and proposed next steps for automation and data management enhancements.
• Automated CSV management for price data using a Python script (consolidar_precios.py) for efficient consolidation and historical data storage.
• Optimized daily ETL processes for time-series price data using advanced techniques like Change Data Capture and Delta Encoding.
• Proposed a lightweight ETL process using Pandas for efficient management of price data changes.
• Structured multiple Scrapy spiders execution from a Jupyter notebook in VS Code, processing data with Pandas.
• Executed sequential Scrapy spiders for an ETL pipeline using Bash commands.
• Provided instructions for using ipdb in non-cursor environments like Jupyter and VS Code.

Achievements

• Successfully optimized the Precios Claros scraping pipeline and improved automation and data management processes.
• Enhanced debugging capabilities using ipdb and improved server setup on GCP.

Pending Tasks

• Further refinement of ETL processes for better efficiency and data handling.
• Continuous monitoring and maintenance of the automated scraper setup.

Evidence

• source_file=2024-10-28.sessions.jsonl, line_number=4, event_count=0, session_id=24d2c04fa3dc8e1caec027bac36bca68158a8c4a60c5e229d805488b0dc4099b
• event_ids: []