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Pol Febrer Calabozo

PROFILE

Pol Febrer Calabozo

Over a two-month period, this developer enhanced data workflows and repository hygiene across metatensor/metatrain, metatensor/metatensor, and lab-cosmo/atomistic-cookbook. They introduced field-level data loading in Python for DiskDataset, reducing memory and I/O costs by allowing selective field access. In metatensor/metatensor, they enabled optional gradient metadata checks for tensor comparisons, improving flexibility for large models. For lab-cosmo/atomistic-cookbook, they improved CI/CD pipelines using GitHub Actions and YAML, ensuring authenticated artifact access for forked pull requests. Additionally, they maintained repository clarity by removing outdated documentation, demonstrating careful version control and a focus on maintainability and efficient, targeted engineering solutions.

Overall Statistics

Feature vs Bugs

75%Features

Repository Contributions

4Total
Bugs
1
Commits
4
Features
3
Lines of code
293
Activity Months2

Work History

April 2026

1 Commits

Apr 1, 2026

2026-04 monthly summary for lab-cosmo/atomistic-cookbook: No new features released this month; focus was on cleaning up repository documentation to improve maintainability and reduce risk. Major bug fix: Removed documentation files that were mistakenly added, including recipes grouped by software and topics related to simulation problems and modeling techniques. Commit reference: 9b4b9bd3dea88fff3dcb3b6da20c0f83e333bad2. This cleanup clarifies project scope and prevents outdated content from misleading users.

July 2025

3 Commits • 3 Features

Jul 1, 2025

July 2025 performance summary: Delivered three targeted enhancements across metatensor/metatrain, lab-cosmo/atomistic-cookbook, and metatensor/metatensor that drive faster model pipelines, more reliable fork PR builds, and flexible metadata validation. These changes deliver measurable business value: faster field-level data loading reduces memory and transfer costs; authenticated fork PR artifact access removes distribution bottlenecks; and optional gradient metadata checks streamline tensor comparisons for large models.

Activity

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Quality Metrics

Correctness95.0%
Maintainability95.0%
Architecture90.0%
Performance95.0%
AI Usage20.0%

Skills & Technologies

Programming Languages

PythonYAMLreStructuredText

Technical Skills

API DesignAPI IntegrationCI/CDData LoadingDataset ManagementGitHub ActionsMetatensorTensor OperationsUnit Testingdocumentationversion control

Repositories Contributed To

3 repos

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

lab-cosmo/atomistic-cookbook

Jul 2025 Apr 2026
2 Months active

Languages Used

PythonYAMLreStructuredText

Technical Skills

API IntegrationCI/CDGitHub Actionsdocumentationversion control

metatensor/metatrain

Jul 2025 Jul 2025
1 Month active

Languages Used

Python

Technical Skills

API DesignData LoadingDataset Management

metatensor/metatensor

Jul 2025 Jul 2025
1 Month active

Languages Used

Python

Technical Skills

MetatensorTensor OperationsUnit Testing