
During February 2026, Chant Xu focused on backend reliability for the jxxghp/MoviePilot repository, addressing two complex bugs that improved data accuracy and user experience. Chant enhanced the TV show season display logic in Python, ensuring special episodes labeled as season 0 are now correctly visible by refining how None values are handled in season parsing. Additionally, Chant strengthened the RSS feed and web scraping pipeline by implementing namespace-aware date parsing and normalization, which improved the consistency of publication dates across diverse sources. This work leveraged Python, data parsing, and web scraping skills, resulting in more accurate content indexing and reduced user confusion.
February 2026 monthly summary for jxxghp/MoviePilot: Delivered two high-impact bug fixes that improve user experience and data reliability. Key improvements include: (1) TV Show Seasons Display Fix ensures season 0 (special episodes) appears correctly by properly handling None in season visibility logic, restoring visibility of all relevant seasons; (2) Robust RSS/Date Handling enhances date extraction for RSS feeds and web scraping by supporting namespaced date tags and normalizing non-standard date formats, increasing reliability of publication dates. These changes reduce user confusion, improve content indexing accuracy, and strengthen data pipelines for search and recommendations. Technologies used include Python-based RSS parsing, date handling utilities, and namespace-aware parsing. Business value: more accurate show listings, consistent feeds, and fewer support tickets related to missing or misdated content.
February 2026 monthly summary for jxxghp/MoviePilot: Delivered two high-impact bug fixes that improve user experience and data reliability. Key improvements include: (1) TV Show Seasons Display Fix ensures season 0 (special episodes) appears correctly by properly handling None in season visibility logic, restoring visibility of all relevant seasons; (2) Robust RSS/Date Handling enhances date extraction for RSS feeds and web scraping by supporting namespaced date tags and normalizing non-standard date formats, increasing reliability of publication dates. These changes reduce user confusion, improve content indexing accuracy, and strengthen data pipelines for search and recommendations. Technologies used include Python-based RSS parsing, date handling utilities, and namespace-aware parsing. Business value: more accurate show listings, consistent feeds, and fewer support tickets related to missing or misdated content.

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