Smithsonian/layup
Mar 2025 – Mar 2025
1 Month active
Languages Used
C++Python
Technical Skills
API DevelopmentAstronomy Software DevelopmentC++C++ DevelopmentData StructuresModule Development
Kevin Napier
PROFILE
Kevin Napier
K.J. Napier worked on the Smithsonian/layup repository, focusing on enhancing the robustness and maintainability of orbital data models. They refactored the core Observation struct in C++ to use union-like variants and std::array for observer positions, improving data representation and reducing runtime ambiguity. Napier also developed Python bindings using pybind11, exposing Orbfit results and related structures to Python workflows for easier cross-language access. Their work included explicit data-type instantiation and optional error parameters, supporting more reliable analytics. By addressing interface correctness and preparing for future enhancements, Napier delivered foundational improvements that support stable, extensible astronomy software development and experimentation.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
9Total
Bugs
1
Commits
9
Features
2
Lines of code
596
Activity Months1
Your Network
207 peopleSame Organization
@umich.edu197
Avionics CompMember
Almo-oMember
Alexander SmartMember
Abby DukeMember
Adam DiehlMember
adfarthMember
Alex HansenMember
Aniket JivaniMember
Axel KerbecMember
Work History
March 2025
9 Commits • 2 Features
Mar 1, 2025March 2025 monthly highlights for Smithsonian/layup focused on data-model robustness, cross-language accessibility, and maintainability improvements that elevate reliability and ease of experimentation with orbital data. The work delivered prepares the ground for advanced analytics while ensuring stable interfaces for Python-based workflows.
9 Commits • 2 Features
Mar 1, 2025March 2025 monthly highlights for Smithsonian/layup focused on data-model robustness, cross-language accessibility, and maintainability improvements that elevate reliability and ease of experimentation with orbital data. The work delivered prepares the ground for advanced analytics while ensuring stable interfaces for Python-based workflows.
March 2025
Activity
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Quality Metrics
Correctness89.0%
Maintainability91.2%
Architecture84.4%
Performance84.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
API DevelopmentAstronomy Software DevelopmentC++C++ DevelopmentData StructuresModule DevelopmentObject-Oriented ProgrammingPybind11PythonRefactoringSoftware DesignSoftware DevelopmentSoftware Engineeringpybind11
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