lsst/tutorial-notebooks
Sep 2025 – Sep 2025
1 Month active
Languages Used
JSONJupyter NotebookPython
Technical Skills
AstronomyAstropyData AccessData AnalysisDocumentationDocumentation Management
gloriafa
PROFILE
Gloriafa
Gloria Fonseca Alvarez developed a refined cross-match tutorial notebook for the lsst/tutorial-notebooks repository, focusing on Gaia data access via TAP services. She consolidated and clarified the tutorial steps, improved metadata management, and enhanced documentation to streamline onboarding and ensure reproducibility for users working with astronomical datasets. Using Python and Jupyter Notebooks, Gloria applied targeted code refactors, including renaming steps and cleaning outputs, to align with review feedback and maintain workflow hygiene through pre-commit checks. Her work addressed both technical and user-facing aspects, resulting in a more accessible, maintainable, and accurate resource for data analysis in astronomy education.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
6Total
Bugs
0
Commits
6
Features
1
Lines of code
700
Activity Months1
Your Network
16 people
Work History
September 2025
6 Commits • 1 Features
Sep 1, 2025September 2025 Monthly Summary – lsst/tutorial-notebooks This period focused on delivering a refined cross-match tutorial experience by integrating a TAP/Gaia cross-match notebook, tightening user-facing content, and reinforcing notebook quality through metadata cleanup and pre-commit hygiene. The work improves onboarding for new users and supports more accurate, reproducible tutorials for Gaia data cross-matching.
6 Commits • 1 Features
Sep 1, 2025September 2025 Monthly Summary – lsst/tutorial-notebooks This period focused on delivering a refined cross-match tutorial experience by integrating a TAP/Gaia cross-match notebook, tightening user-facing content, and reinforcing notebook quality through metadata cleanup and pre-commit hygiene. The work improves onboarding for new users and supports more accurate, reproducible tutorials for Gaia data cross-matching.
September 2025
Activity
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Quality Metrics
Correctness93.4%
Maintainability93.4%
Architecture90.0%
Performance90.0%
AI Usage26.6%
Skills & Technologies
Programming Languages
JSONJupyter NotebookPython
Technical Skills
AstronomyAstropyData AccessData AnalysisDocumentationDocumentation ManagementJupyter NotebooksMetadata ManagementPyVOTAP Service
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