TheAnonymous-stack/numi-scraper
Jul 2025 – Jul 2025
1 Month active
Languages Used
JSONPython
Technical Skills
Content CreationData EngineeringData ExtractionPythonWeb Scraping
Nina Low
PROFILE
Nina Low
During July 2025, contributed to the TheAnonymous-stack/numi-scraper repository by developing a Math Problems Dataset for grades 4 and 8, delivering two JSON files covering number sense, fractions, decimals, geometry, and financial literacy for an educational platform. Addressed a critical issue in the scraping pipeline by enhancing tag and question number handling, which improved the reliability and accuracy of data extraction. Leveraged Python for both content creation and web scraping, focusing on robust data engineering practices. These efforts resulted in higher quality data feeds, reduced manual curation, and enabled faster integration of educational content into the platform’s workflow.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
2Total
Bugs
1
Commits
2
Features
1
Lines of code
5,411
Activity Months1
Your Network
21 peopleShared Repositories
9
Work History
July 2025
2 Commits • 1 Features
Jul 1, 2025Concise monthly summary for 2025-07: Key features delivered include the Math Problems Dataset for Grades 4 and 8 and a major scraper reliability fix. The dataset adds two JSON files with problems across number sense, fractions, decimals, geometry, and financial literacy for use in the educational platform. The scraper bug fix—Robust Tag and Question Number Handling in Scraper—resolves inconsistencies in tag and question number processing, improving data extraction reliability and accuracy. Overall impact: higher quality data feeds for the educational platform, reduced manual data curation, and faster content provisioning. Technologies demonstrated: data extraction reliability, JSON dataset creation, and version-control-traceable changes in a scraping pipeline.
2 Commits • 1 Features
Jul 1, 2025Concise monthly summary for 2025-07: Key features delivered include the Math Problems Dataset for Grades 4 and 8 and a major scraper reliability fix. The dataset adds two JSON files with problems across number sense, fractions, decimals, geometry, and financial literacy for use in the educational platform. The scraper bug fix—Robust Tag and Question Number Handling in Scraper—resolves inconsistencies in tag and question number processing, improving data extraction reliability and accuracy. Overall impact: higher quality data feeds for the educational platform, reduced manual data curation, and faster content provisioning. Technologies demonstrated: data extraction reliability, JSON dataset creation, and version-control-traceable changes in a scraping pipeline.
July 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
JSONPython
Technical Skills
Content CreationData EngineeringData ExtractionPythonWeb Scraping
Repositories Contributed To
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