qubicsoft/qubic
Mar 2026 – Mar 2026
1 Month active
Languages Used
FortranPython
Technical Skills
Astronomy SoftwareData AnalysisDependency ManagementFortranPythonPython scripting
sofiaferazzoli
PROFILE
Sofiaferazzoli
Contributed to the qubicsoft/qubic repository by delivering major enhancements to the Observation Plan, focusing on dynamic source loading, sidereal plotting utilities, and a modular runner supporting CSV-based sources. Applied Python and Fortran to refactor input validation, improve time handling, and streamline configuration management, resulting in more reliable and configurable observation planning for astronomy campaigns. Centralized dependency management by cleaning up project configuration files, signaling a shift toward simplified maintenance. The work emphasized data analysis, scientific computing, and version control, providing a foundation for improved observability and campaign planning from March to December 2026 without introducing new bugs during the development period.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
2
Lines of code
874,942
Activity Months1
Your Network
12 peopleShared Repositories
12
Alexandre HuchetMember
ismailbekkaoui062Member
belenMember
Alexandre HuchetMember
Alexandre HuchetMember
Alexandre HuchetMember
TomLaclavereMember
LeonoraMember
Steve TORCHINSKYMember
Work History
March 2026
4 Commits • 2 Features
Mar 1, 2026March 2026: Delivered major enhancements to the Observation Plan in qubic and streamlined dependency management. Implemented dynamic source loading, sidereal plotting utilities, and a modular runner with CSV-based sources, improved input validation, and time handling. Cleanup of dependency config signals centralized dependency management for future releases. These changes improve reliability, configurability, and observability for upcoming campaigns (Mar–Dec 2026).
4 Commits • 2 Features
Mar 1, 2026March 2026: Delivered major enhancements to the Observation Plan in qubic and streamlined dependency management. Implemented dynamic source loading, sidereal plotting utilities, and a modular runner with CSV-based sources, improved input validation, and time handling. Cleanup of dependency config signals centralized dependency management for future releases. These changes improve reliability, configurability, and observability for upcoming campaigns (Mar–Dec 2026).
March 2026
Activity
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Quality Metrics
Correctness85.0%
Maintainability80.0%
Architecture80.0%
Performance85.0%
AI Usage30.0%
Skills & Technologies
Programming Languages
FortranPython
Technical Skills
Astronomy SoftwareData AnalysisDependency ManagementFortranPythonPython scriptingSoftware DevelopmentVersion Controlastronomydata analysisdata processingdata visualizationscientific computing
Repositories Contributed To
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