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Andrea Petrocchi

PROFILE

Andrea Petrocchi

Andrea Petrocchi developed and standardized packaging recipes for the MaMMoS ecosystem within the conda-forge/staged-recipes repository, focusing on scientific computing workflows. Over two months, Andrea delivered recipes for magnetic units, ontology-linked entities, and five additional MaMMoS components, each with complete metadata, dependency management, and automated testing commands. Using Python and YAML, Andrea ensured cross-platform compatibility by refining build instructions, removing Windows-specific builds, and aligning dependencies for Linux, macOS, and Windows. This work improved installation reliability, reproducibility, and maintainability for downstream users, demonstrating a thorough approach to environment configuration, package management, and adherence to conda-forge best practices.

Overall Statistics

Feature vs Bugs

100%Features

Repository Contributions

11Total
Bugs
0
Commits
11
Features
4
Lines of code
340
Activity Months2

Work History

December 2025

9 Commits • 2 Features

Dec 1, 2025

December 2025 focused on expanding the Mammos ecosystem within conda-forge/staged-recipes and strengthening cross-platform packaging. Delivered five new recipes (mammos-dft, mammos-spindynamics, mammos-analysis, mammos-mumag, mammos-ai) with complete metadata, dependencies, build instructions, and testing commands. Standardized platform support by removing Windows builds, standardizing noarch dependencies, and scoping Unix-specific components (e.g., jax), resulting in Linux/macOS/Windows compatibility and more reproducible builds. This work improves installation reliability for end users, accelerates upstream integration, and demonstrates strong packaging discipline and adherence to conda-forge best practices.

November 2025

2 Commits • 2 Features

Nov 1, 2025

Month: 2025-11 — Delivered two packaging recipes for MaMMoS-related components in conda-forge/staged-recipes, enabling standardized distribution, testing, and onboarding for downstream users. Implemented magnetic units support and ontology-linked entities, with clear build/test metadata to ensure quality and reproducibility.

Activity

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Quality Metrics

Correctness98.2%
Maintainability96.4%
Architecture96.4%
Performance96.4%
AI Usage20.0%

Skills & Technologies

Programming Languages

PythonYAML

Technical Skills

AI integrationAstropyPythonPython developmentYAML configurationcondaconda recipescross-platform developmentdata analysisdependency managementdocumentationenvironment configurationmetadata managementpackage managementscientific computing

Repositories Contributed To

1 repo

Overview of all repositories you've contributed to across your timeline

conda-forge/staged-recipes

Nov 2025 Dec 2025
2 Months active

Languages Used

PythonYAML

Technical Skills

AstropyPythonPython developmentdependency managementpackage managementAI integration