pypeit/PypeIt
Nov 2025 – Jan 2026
2 Months active
Languages Used
PythonYAML
Technical Skills
CI/CDGitHub ActionsPython DevelopmentPython programmingdata calibrationimage processing
feige
PROFILE
Feige
Fangge Wang contributed to the pypeit/PypeIt repository by enhancing automated testing infrastructure and stabilizing spectrograph operations. Over two months, Fangge implemented new CI workflows using GitHub Actions and YAML, increasing test coverage and reducing feedback time for code changes. This work ensured reproducible results and maintainable pipelines across branches. Additionally, Fangge delivered a targeted Python patch to calibrate and configure the MDMOSMOS spectrograph for its first TDE observation, adjusting calibration parameters and disabling non-essential image processing. The contributions demonstrated depth in CI/CD, Python development, and data calibration, addressing both infrastructure reliability and instrument readiness for scientific campaigns.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
2Total
Bugs
1
Commits
2
Features
1
Lines of code
3,128,148
Activity Months2
Your Network
19 peopleShared Repositories
19
Brad HoldenMember
Brad HoldenMember
Brad HoldenMember
Brad HoldenMember
Frederick DaviesMember
Debora PellicciaMember
Dusty ReichweinMember
Eric JeschkeMember
Frank VerdiMember
Work History
January 2026
1 Commits
Jan 1, 2026January 2026: Focused on enabling the MDMOS spectrograph for the first TDE by delivering a focused bug fix to calibrations and selective feature toggling. The patch stabilizes OSMOS operation for initial observations, minimizing risk of data gaps and ensuring readiness for the TDE campaign. This work demonstrates targeted calibration control, rapid response to instrument needs, and strong collaboration with the instrument team.
1 Commits
Jan 1, 2026January 2026: Focused on enabling the MDMOS spectrograph for the first TDE by delivering a focused bug fix to calibrations and selective feature toggling. The patch stabilizes OSMOS operation for initial observations, minimizing risk of data gaps and ensuring readiness for the TDE campaign. This work demonstrates targeted calibration control, rapid response to instrument needs, and strong collaboration with the instrument team.
January 2026
November 2025
1 Commits • 1 Features
Nov 1, 2025November 2025 monthly summary for pypeit/PypeIt focused on strengthening automated testing capabilities and CI reliability to accelerate delivery and ensure code quality across branches.
November 2025
1 Commits • 1 Features
Nov 1, 2025November 2025 monthly summary for pypeit/PypeIt focused on strengthening automated testing capabilities and CI reliability to accelerate delivery and ensure code quality across branches.
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage30.0%
Skills & Technologies
Programming Languages
PythonYAML
Technical Skills
CI/CDGitHub ActionsPython DevelopmentPython programmingdata calibrationimage processingspectroscopy
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