
Worked on the topmonks/hlidac-shopu repository to enhance price data extraction and reliability across three merchant scrapers, focusing on iglobus.cz, pilulka.cz, and mironet. Applied JavaScript and web scraping techniques to improve discount price handling, clean current price data, and ensure accurate extraction of original prices for discounts. Addressed a race condition in the data push process, which increased the reliability of downstream pricing analytics and customer-facing displays. Emphasized data cleaning to reduce manual reconciliation and pricing anomalies, establishing a more resilient foundation for future scrapes. The work leveraged front end development skills to support robust, timely price feeds.
April 2025 performance summary for topmonks/hlidac-shopu: Delivered a targeted price data extraction and reliability overhaul across three scrapers (iglobus.cz, pilulka.cz, mironet), resulting in more accurate and timely price feeds. Work included discount price handling, current price cleaning, correct original price extraction for discounts, and a race-condition fix in data push. These changes improve data integrity for downstream pricing analytics and customer-facing price displays, and establish a foundation for more resilient scrapes across additional merchants. Business impact includes reduced manual reconciliation, fewer pricing anomalies, and faster time-to-value for promotional pricing.
April 2025 performance summary for topmonks/hlidac-shopu: Delivered a targeted price data extraction and reliability overhaul across three scrapers (iglobus.cz, pilulka.cz, mironet), resulting in more accurate and timely price feeds. Work included discount price handling, current price cleaning, correct original price extraction for discounts, and a race-condition fix in data push. These changes improve data integrity for downstream pricing analytics and customer-facing price displays, and establish a foundation for more resilient scrapes across additional merchants. Business impact includes reduced manual reconciliation, fewer pricing anomalies, and faster time-to-value for promotional pricing.

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