Ethan Akubilo developed and maintained the privacy-tech-lab/gpc-web-crawler repository, delivering a modular, containerized web crawling and data collection pipeline. He architected a multi-service deployment using Docker Compose, integrating Python and Node.js components for scalable crawling, robust error handling, and automated data persistence to MariaDB. Ethan implemented features such as a Python API for GPP string decoding, batch processing, and modular class-based architecture, while modernizing deployment tooling and logging. His work included decoupling services, expanding crawl coverage, and establishing Python packaging for future extensibility. The engineering demonstrated depth in backend development, automation, and system design, resulting in maintainable, reliable infrastructure.
April 2025 monthly summary for privacy-tech-lab/gpc-web-crawler. Focused on delivering Python-based GPP string decoding API and establishing Python packaging groundwork to enable scalable distribution and future feature work. No major bugs fixed this month. Delivered code and documentation, and prepared Docker Compose for new service images to support the updated architecture.
April 2025 monthly summary for privacy-tech-lab/gpc-web-crawler. Focused on delivering Python-based GPP string decoding API and establishing Python packaging groundwork to enable scalable distribution and future feature work. No major bugs fixed this month. Delivered code and documentation, and prepared Docker Compose for new service images to support the updated architecture.
March 2025 (2025-03) monthly summary for privacy-tech-lab/gpc-web-crawler. Focused on resilience, coverage, and tooling modernization. Key deliverables include robust error handling and logging for the web crawler, expansion of crawl targets with Yelp, and modernization of deployment and data tooling including docker compose adoption, refactored data saving paths, README improvements, and a new Makefile target to check docker compose status. Bug fixes include preventing crashes on unexpected errors and removing outdated status-code assumptions in failure handling. These efforts enhanced reliability, data completeness, and maintainability, delivering business value through more robust data collection and faster, safer deployments.
March 2025 (2025-03) monthly summary for privacy-tech-lab/gpc-web-crawler. Focused on resilience, coverage, and tooling modernization. Key deliverables include robust error handling and logging for the web crawler, expansion of crawl targets with Yelp, and modernization of deployment and data tooling including docker compose adoption, refactored data saving paths, README improvements, and a new Makefile target to check docker compose status. Bug fixes include preventing crashes on unexpected errors and removing outdated status-code assumptions in failure handling. These efforts enhanced reliability, data completeness, and maintainability, delivering business value through more robust data collection and faster, safer deployments.
February 2025 monthly summary for privacy-tech-lab/gpc-web-crawler focused on improving reliability, data quality, and maintainability. Key efforts centered on decoupling the well-known crawl from privacy crawl, expanding crawl coverage, and hardening the crawl pipeline and data management. Result is a more scalable, observable, and robust crawling workflow with clearer ownership and faster iteration.
February 2025 monthly summary for privacy-tech-lab/gpc-web-crawler focused on improving reliability, data quality, and maintainability. Key efforts centered on decoupling the well-known crawl from privacy crawl, expanding crawl coverage, and hardening the crawl pipeline and data management. Result is a more scalable, observable, and robust crawling workflow with clearer ownership and faster iteration.
January 2025 monthly summary for privacy-tech-lab/gpc-web-crawler: Delivered a major architecture overhaul and deployment improvements that materially increase reliability, scalability, and maintainability of the crawler pipeline. Implemented modular crawler architecture with separate classes, added retry policies for REST API and MariaDB, improved startup and error handling, and reduced wait times by removing hard-coded proxies to accelerate crawl cycles. Reworked deployment and backend integration to isolate crawling services within Docker Compose, added a robust MariaDB container, introduced a connection pool, and added container lifecycle scripts for automatic cleanup, improving deployment repeatability and resource utilization. Enhanced output persistence, target expansion, and log organization by persisting results and errors to dedicated directories, expanding crawl targets, and standardizing log storage. Addressed stability through maintenance tasks including reverting package-lock conflicts, cleaning Dockerfiles, and keeping VCS ignores up to date. Major bug fixes include correcting null site_id processing, hardening the DB checker, and fixing path issues across the crawler startup script. Overall impact: faster, more reliable data collection; easier deploys and maintenance; clearer traceability from commit activity to business value. Technologies/skills demonstrated: Docker/Docker Compose, MariaDB, REST API integration, connection pooling, modular software architecture, robust error handling, container lifecycle management, and build/stability discipline.
January 2025 monthly summary for privacy-tech-lab/gpc-web-crawler: Delivered a major architecture overhaul and deployment improvements that materially increase reliability, scalability, and maintainability of the crawler pipeline. Implemented modular crawler architecture with separate classes, added retry policies for REST API and MariaDB, improved startup and error handling, and reduced wait times by removing hard-coded proxies to accelerate crawl cycles. Reworked deployment and backend integration to isolate crawling services within Docker Compose, added a robust MariaDB container, introduced a connection pool, and added container lifecycle scripts for automatic cleanup, improving deployment repeatability and resource utilization. Enhanced output persistence, target expansion, and log organization by persisting results and errors to dedicated directories, expanding crawl targets, and standardizing log storage. Addressed stability through maintenance tasks including reverting package-lock conflicts, cleaning Dockerfiles, and keeping VCS ignores up to date. Major bug fixes include correcting null site_id processing, hardening the DB checker, and fixing path issues across the crawler startup script. Overall impact: faster, more reliable data collection; easier deploys and maintenance; clearer traceability from commit activity to business value. Technologies/skills demonstrated: Docker/Docker Compose, MariaDB, REST API integration, connection pooling, modular software architecture, robust error handling, container lifecycle management, and build/stability discipline.
December 2024 monthly summary for privacy-tech-lab/gpc-web-crawler. The team focused on delivering a scalable deployment architecture, improving crawler robustness, and stabilizing operations with critical logging fixes. Major changes include a multi-container docker-compose deployment, integration of GPC well-known endpoints, expanded crawl scope, and lifecycle tooling, resulting in improved data collection, reliability, and maintainability.
December 2024 monthly summary for privacy-tech-lab/gpc-web-crawler. The team focused on delivering a scalable deployment architecture, improving crawler robustness, and stabilizing operations with critical logging fixes. Major changes include a multi-container docker-compose deployment, integration of GPC well-known endpoints, expanded crawl scope, and lifecycle tooling, resulting in improved data collection, reliability, and maintainability.
Month 2024-11 — Delivered PHPMyAdmin integration for privacy-tech-lab/gpc-web-crawler Docker setup, enabling direct database UI access within the container. Updated Dockerfile to install Apache2 and phpMyAdmin, exposed port 80 in the container startup script, and configured supervisord to manage Apache2. This work streamlines database tasks, reduces setup time, and improves debugging and admin capabilities in local/deploy environments. No major bugs fixed this month; primary focus was feature delivery and stabilizing containerized workflow.
Month 2024-11 — Delivered PHPMyAdmin integration for privacy-tech-lab/gpc-web-crawler Docker setup, enabling direct database UI access within the container. Updated Dockerfile to install Apache2 and phpMyAdmin, exposed port 80 in the container startup script, and configured supervisord to manage Apache2. This work streamlines database tasks, reduces setup time, and improves debugging and admin capabilities in local/deploy environments. No major bugs fixed this month; primary focus was feature delivery and stabilizing containerized workflow.
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