Developer-to-developer knowledge transfer
Clients interested in migrating to Zyte API can benefit from advisory services to ensure a smooth migration.
Basic orientation in Zyte API & Scrapy Cloud - highlighting key features and how to get started
Zyte API & Scrapy Cloud usage examples - how to use our APIs effectively
Troubleshooting processes - some basic tips on how to approach troubleshooting; e.g. checking if any anti-ban has been introduced or changed
Scaling Up - Essentials
Learn coding best practices for web scraping. Training in Python code style best practices - using tools like Black, Isort, Pre-commit, following PEP8 style, and using linters to ensure code adheres to industry standards and best practices.
Setup standardized tools -setup Black, Isort, pre-commit, Scrapy Cloud and Spidermon
Introduction to Spidermon - overview of Spidermon and basic monitoring
Workshop on Spidermon -usage, error checking, email notification, sentry (or similar), Scrapy stats, reporting and advanced monitoring
Scaling Up - Expert Review
A thorough analysis of your web scraping solution to identify potential points for optimization.
Audit of current web scraping - walkthrough of code and a full review of Crawling Strategy and Infrastructure
Report on audit findings to identify primary bottlenecks (e.g. velocity, parallel processes, etc.). Identify inconsistencies, risks, and cost-saving recommendations
Workshop on audit findings to optimize your web scraping solution
Data Quality - Essentials
Introduction to Data Quality Assurance and automated & manual data quality practices
Schema Validation - turning the inherent structured nature of your data into fast, whole-dataset validation per data point
Advanced data quality assurance with Python. Take data quality assurance further with advanced techniques to uncover issues and anomalies
Visualizing Data Quality - Turn advanced data quality assurance into charts and visualisations to highlight trends and tell the data quality story
Data Quality - Expert Review
A thorough analysis of your current Data Quality Assurance setup to identify potential opportunities for improvement.
Audit of current Data Quality setup. Walkthrough of code and tools accompanied by Zyte QA Engineer. Review of monitoring strategy AND response capabilities
Report on audit findings to identify processes and tooling inefficiencies, risks, and Data Quality improvement recommendations
Workshop on audit findings to optimize your data quality solution