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palaks-1

PROFILE

Palaks-1

Palak Sharma contributed to the KotatsuApp/kotatsu-parsers repository by developing and refining backend parsers that expanded content coverage and improved metadata accuracy for NHentai sites. Using Java and Kotlin, Palak introduced a unified, type-safe search system and upgraded the data model to support multiple authors, streamlining future integrations. They enhanced parser reliability by implementing robust error handling and fallback mechanisms for image loading, reducing broken renders in user feeds. Palak’s work included refactoring CSS selectors and standardizing URL construction utilities, which improved maintainability and search reliability. The engineering demonstrated thoughtful data modeling and a focus on scalable, resilient web scraping solutions.

Overall Statistics

Feature vs Bugs

67%Features

Repository Contributions

8Total
Bugs
2
Commits
8
Features
4
Lines of code
3,387
Activity Months3

Work History

April 2025

1 Commits

Apr 1, 2025

April 2025 monthly summary for KotatsuApp/kotatsu-parsers focusing on reliability improvements in NHentai image loading. Delivered a fallback mechanism to alternate image formats when the original NHentai URL fails, improving content rendering stability across NHentai sources. The change is isolated to the NHentai image loading path and traceable to a single commit for easy review and rollback.

March 2025

1 Commits • 1 Features

Mar 1, 2025

Month: 2025-03 — KotatsuApp/kotatsu-parsers Concise monthly summary focusing on key accomplishments, major fixes, and impact.

February 2025

6 Commits • 3 Features

Feb 1, 2025

February 2025 — KotatsuApp/kotatsu-parsers delivered meaningful business value by expanding content coverage, improving data quality, and hardening cross-site search. Implemented NHentai.to and NHentai.xxx parsers with integrated search across NHentai sites; fixed metadata extraction accuracy for NHentai.xxx; introduced a unified MangaSearchQuery system for robust, type-safe cross-site searches; upgraded the author data model to support multiple authors and updated parsers accordingly. These changes increase content coverage and metadata accuracy across NHentai sites, reduce maintenance cost for adding new sources, and improve search reliability and attribution in metadata.

Activity

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Quality Metrics

Correctness87.6%
Maintainability88.8%
Architecture90.0%
Performance80.0%
AI Usage20.0%

Skills & Technologies

Programming Languages

JavaKotlin

Technical Skills

API IntegrationBackend DevelopmentCSS SelectorsData ModelingError HandlingHTML ParsingJavaKotlinObject-Oriented ProgrammingParser DevelopmentRefactoringWeb Scraping

Repositories Contributed To

1 repo

Overview of all repositories you've contributed to across your timeline

KotatsuApp/kotatsu-parsers

Feb 2025 Apr 2025
3 Months active

Languages Used

JavaKotlin

Technical Skills

API IntegrationBackend DevelopmentCSS SelectorsData ModelingHTML ParsingJava

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