astro-datalab/notebooks-latest
Jan 2025 – Jan 2026
2 Months active
Languages Used
Python
Technical Skills
Data AnalysisDatabase QueryingJupyter NotebookPython scriptingdata analysis
David Herrera
PROFILE
David Herrera
Worked on the astro-datalab/notebooks-latest repository, focusing on enhancing the reliability and reproducibility of Jupyter notebook workflows for data analysis. Delivered a targeted improvement to the DESILegacyISv2 notebook by resetting execution state, cleaning up metadata, and tuning database query limits to improve data retrieval consistency. Addressed a critical bug in DESILegacySurveys.ipynb by correcting notebook version identification, which reduced the risk of workflow errors. Utilized Python scripting and database querying to implement these changes, emphasizing maintainability and disciplined debugging practices. The work supported more stable, reproducible analyses and streamlined version tracking within a notebook-centric codebase over two months.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
2Total
Bugs
1
Commits
2
Features
1
Lines of code
1,333
Activity Months2
Your Network
22 peopleSame Organization
@noirlab.edu12
Shared Repositories
10
Benjamin Alan WeaverMember
BrianMolinaMerinoMember
bmerino95Member
github-actionsMember
Icuras42Member
Astro-MorganMember
Robert NikuttaMember
rohinsantMember
Ragadeepika-PuchaMember
Work History
January 2026
1 Commits
Jan 1, 2026Monthly summary for 2026-01: Focused on reliability and maintainability of notebook version tracking in astro-datalab/notebooks-latest. Key features delivered: No new features released this month; stability improvements were achieved by addressing a critical notebook version identification bug. Major bugs fixed: Corrected the nbid notation in DESILegacySurveys.ipynb to ensure proper identification of the notebook version (commit 72571d339a885d4f75ad1abaa1fe074a311e0725). Overall impact and accomplishments: This change enhances reliability and reproducibility of notebook version tracking, reducing the risk of using incorrect notebook versions in workflows and improving maintenance of the notebooks-latest repository. Technologies/skills demonstrated: Python/Jupyter notebook debugging, nbid/versioning handling, Git-based change management, and disciplined bug-fix practices in a notebook-centric codebase.
1 Commits
Jan 1, 2026Monthly summary for 2026-01: Focused on reliability and maintainability of notebook version tracking in astro-datalab/notebooks-latest. Key features delivered: No new features released this month; stability improvements were achieved by addressing a critical notebook version identification bug. Major bugs fixed: Corrected the nbid notation in DESILegacySurveys.ipynb to ensure proper identification of the notebook version (commit 72571d339a885d4f75ad1abaa1fe074a311e0725). Overall impact and accomplishments: This change enhances reliability and reproducibility of notebook version tracking, reducing the risk of using incorrect notebook versions in workflows and improving maintenance of the notebooks-latest repository. Technologies/skills demonstrated: Python/Jupyter notebook debugging, nbid/versioning handling, Git-based change management, and disciplined bug-fix practices in a notebook-centric codebase.
January 2026
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 (2025-01) - Delivered a targeted improvement to the DESILegacyISv2 notebook workflow across astro-datalab/notebooks-latest. Implemented notebook initialization cleanup, cleared metadata from prior runs, bumped the DESILegacyISv2 version, and tuned a database query limit to enhance data retrieval performance and result consistency. This work reduces run-to-run variability and improves reproducibility for DESILegacyISv2 analyses, supporting faster, more reliable insights.
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 (2025-01) - Delivered a targeted improvement to the DESILegacyISv2 notebook workflow across astro-datalab/notebooks-latest. Implemented notebook initialization cleanup, cleared metadata from prior runs, bumped the DESILegacyISv2 version, and tuned a database query limit to enhance data retrieval performance and result consistency. This work reduces run-to-run variability and improves reproducibility for DESILegacyISv2 analyses, supporting faster, more reliable insights.
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Data AnalysisDatabase QueryingJupyter NotebookPython scriptingdata analysis
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