Monthly summary for 2026-01 focusing on work in spack/spack-packages. Implemented a Zfit dependency upgrade and compatibility enhancements, updating dependencies to ensure compatibility with Python and TensorFlow. Changes were implemented via commit 660aecd67cf0d8ea3e30551e45d8af5475ab296c and are aimed at improving build stability and downstream compatibility in the spack-packages repo.

July 2025 monthly summary for the spack/spack-packages repository focused on packaging modernization and build tooling alignment. Key deliverables include a major dependency upgrade to zfit 0.26.0, versioning updates, and alignment of build dependencies with modern tooling. This work enhances compatibility with newer toolchains, improves build reproducibility, and reduces maintenance risk for downstream users. No major bug fixes were required this month; activity centered on stabilizing the packaging surface and preparing for future upgrades.

June 2025 monthly summary focused on delivering a coordinated upgrade of the zfit package across the Spack ecosystem, with packaging modernization and dependency alignment to ensure stability and forward compatibility. Key features delivered: - Zfit 0.26.0 upgrade implemented across spack/spack-packages and spack/spack, updating version definitions, SHA256 checksums, and build dependencies. - Packaging modernization to hatchling and hatch-vcs for versions >= 0.26, while preserving setuptools and setuptools-scm for older environments; ensured consistent packaging semantics across repos. - Dependency alignment to TensorFlow and TensorFlow Probability to match the new zfit release, reducing compatibility risks and runtime conflicts. Major bugs fixed (through dependency and packaging stabilizations): - Resolved drift between tooling and zfit 0.26 packaging requirements by updating build tooling and constraints; improved reproducibility and install reliability. Overall impact and accomplishments: - Enabled downstream teams to rely on a stable, modernized packaging flow with the latest zfit release, improving install reliability and upgrade paths. - Established a repeatable release pattern for zfit upgrades, including version, SHA256, and dependency constraints, across multiple repos. Technologies/skills demonstrated: - Packaging modernization (hatchling, hatch-vcs) and semantic versioning, SHA256 management. - Dependency management and alignment with TensorFlow TF/TF Probability. - Commit-level traceability and cross-repo coordination for release delivery.

May 2025 monthly summary focused on improving packaging readiness for the formulate package via Conda, along with metadata quality and documentation hygiene in the staging repository. Key outcomes include delivering a complete Conda recipe for formulate (version 1.0.0) with proper build/test/runtime requirements, adding the BSD-3-Clause license, and cleaning up metadata in meta.yaml. Systematic typo fixes were performed to enhance recipe robustness. This work improves distribution readiness, license compliance, and reproducible builds across conda-forge.

April 2025 monthly summary for the Spack ecosystem focused on delivering ML-ready Python packages and improving packaging for TensorFlow workflows. Across spack/spack and spack/spack-packages, the month delivered new packages, updated dependencies to support newer TensorFlow versions, and refined package metadata to improve discoverability and maintainability. The work strengthens support for ML tooling in Spack and reduces friction for users adopting tf-keras workflows and physics-oriented Python packages.