conda-forge/staged-recipes
Jan 2026 – Mar 2026
2 Months active
Languages Used
PythonYAML
Technical Skills
PythonPython developmentYAML configurationdata sciencedependency resolutionmachine learning
Andrew Ashford
PROFILE
Andrew Ashford
Contributed to the conda-forge/staged-recipes repository by delivering two core features over two months, focusing on packaging and automation for Python-based data science tools. Developed and maintained the Univi 0.3.7 package, ensuring installation integrity through precise checksum management and accurate dependency resolution using Python and YAML configuration. Established cross-platform CI pipelines with GitHub Actions, enabling automated builds and tests across Windows, macOS, and Linux. Introduced linting scripts and dependency management to standardize packaging workflows and improve reproducibility. The work emphasized clean commit practices, scalable CI/CD processes, and robust package management, supporting reliable collaboration within the conda-forge ecosystem.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
2
Lines of code
4,293
Activity Months2
Your Network
811 peopleSame Organization
@ohsu.edu2
Shared Repositories
809
Work History
March 2026
1 Commits • 1 Features
Mar 1, 2026In 2026-03, delivered cross-platform CI configuration, linting scripts, and Conda Forge dependency management for conda-forge/staged-recipes. This foundational work enables reliable builds across Windows, macOS, and Linux, improves code quality, and stabilizes environments for packaging. There were no major bugs fixed this month; the focus was on establishing scalable pipelines that reduce risk and accelerate future contributions. Overall, the changes enhance reliability, reproducibility, and collaboration with the conda-forge community.
1 Commits • 1 Features
Mar 1, 2026In 2026-03, delivered cross-platform CI configuration, linting scripts, and Conda Forge dependency management for conda-forge/staged-recipes. This foundational work enables reliable builds across Windows, macOS, and Linux, improves code quality, and stabilizes environments for packaging. There were no major bugs fixed this month; the focus was on establishing scalable pipelines that reduce risk and accelerate future contributions. Overall, the changes enhance reliability, reproducibility, and collaboration with the conda-forge community.
March 2026
January 2026
3 Commits • 1 Features
Jan 1, 2026January 2026 monthly summary for conda-forge/staged-recipes: Delivered Univi 0.3.7 packaging and integrity updates. Introduced new package 'univi' with build instructions; subsequent commits corrected and stabilized checksums and metadata to ensure reliable installation and correct dependencies.
January 2026
3 Commits • 1 Features
Jan 1, 2026January 2026 monthly summary for conda-forge/staged-recipes: Delivered Univi 0.3.7 packaging and integrity updates. Introduced new package 'univi' with build instructions; subsequent commits corrected and stabilized checksums and metadata to ensure reliable installation and correct dependencies.
Activity
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Quality Metrics
Correctness95.0%
Maintainability95.0%
Architecture95.0%
Performance95.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonYAML
Technical Skills
CI/CDConda PackagingGitHub ActionsPythonPython DevelopmentPython developmentYAML configurationdata sciencedependency resolutionmachine learningpackage management
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline