June 2026: Reliability improvement in core math for mxcubecore. Fixed handling of zero-valued kappa and kappa_phi by treating 0 as a valid position, preventing incorrect exclusions in calculations. The change improves correctness for edge cases, reducing downstream data inconsistencies and improving trust in results used by downstream modules. Commit d7ca11dcf4786588ebaf38cb2ef259cb441794b0 (PR #1627), co-authored by Antonia Beteva.

February 2026 focused on dependency modernization for mxcubeweb. The main deliverable was upgrading the mxcubecore dependency to unlock latest features and improvements, with an initial bump to 2.1.0 and a subsequent requirement upgrade to >=2.4.0. Changes were limited to dependency metadata (pyproject.toml), preserving existing functionality while enabling future enhancements. This work improves build reproducibility, compatibility with downstream components, and positions the project to leverage upcoming capabilities from mxcubecore.

January 2026, mxcubecore: Focused stabilization with a targeted bug fix; no new features released this month. Major bugs fixed: Corrected a public API typo in the Beamline module from get_value_mototrs to get_value_motors, preventing potential runtime errors and API misuse. The fix was implemented in commit da2bd5970daa4d2272371a8eec97689cc6164736 (Update Beamline.py; Fix typo).

December 2025 — mxcubecore: Delivered the Diffractometer API refactor with standardized methods and motor configurations, supplemented by documentation updates clarifying AbstractDiffractometer usage and sample_view centring motors. Introduced breaking changes with clear migration guidance. Result: improved API consistency, reduced integration risk, and a solid foundation for future motor configuration enhancements. Key commits include updates to abstract_diffractometer_breaking_changes.md and diffractometer.md, with co-authorship by Rasmus H. Fogh.

September 2025 focused on delivering energy scan data acquisition and handling enhancements within ICATLIMS (mxcubecore). The work included a code refactor for maintainability, security cleanups removing temporary files, Python version compatibility fixes, and the addition of store_common_data to optimize data handling.

April 2025 monthly summary for mxcube/mxcubecore: Focused on stabilizing configuration loading and device communication. Delivered YAML-compatible configuration loading, refactored data reading across hardware objects, and enhanced XMLRPCServer logging for improved diagnostics. Fixed critical robustness issues in Tango name retrieval and video_mode access within polling, and improved Defreezing Gripper state logging with a shorter, more reliable unload path by removing redundant wait. These changes improve reliability, reduce troubleshooting time, and support YAML-based configuration workflows.

March 2025 monthly performance summary for mxcube/mxcubecore: Reliability and maintainability enhancements in hardware configuration loading and energy scanning workflows. Delivered the ability to load the same HardwareObject configuration multiple times without errors and modernized the energy scan module with a simplified class structure, centralized control logic, and direct HardwareRepository usage for hardware access. These changes reduce configuration friction, improve maintainability, and lay groundwork for extensible hardware integrations.

February 2025 (mxcube/mxcubecore): Focused on improving user guidance and documentation for TangoShutter configuration. Delivered a concrete XML configuration example to streamline setup and reduce support overhead, aligned with code changes in TangoShutter.py. No major bug fixes reported this month in the repository scope.

January 2025 — Delivered two focused improvements in mxcubecore: (1) API cleanup via MiniDiff Name Property Refactor and (2) Codebase Cleanup with Hardware Access Refactor. Also addressed YAML configuration stability and removed obsolete config files, reducing configuration drift and maintenance overhead. Result: simpler API, more reliable hardware interactions, a leaner repository, and faster onboarding. Demonstrated Python property usage, targeted refactoring, and robust config management.

This monthly summary captures the 2024-09 work focused on improving code maintainability and ensuring robust initialization patterns in ESRFEnergyScan within the mxcube/mxcubecore repository. The month emphasized clean, extensible design, targeting reduced maintenance costs and lower defect risk in core energy scan functionality.

Monthly summary for 2024-08: Delivered Detector Cover Open Control via Diffractometer in mxcubecore, enabling opening the detector cover through the diffractometer with robust error handling and logging to improve reliability of experimental hardware control. This work reduces manual intervention and improves automation in experimental workflows.

July 2024 monthly summary for mxcube/mxcubecore: Focused on improving beam size retrieval accuracy by implementing a more comprehensive data retrieval approach. Delivered a targeted feature with clear commit trace and measurable impact on data quality.

April 2024 (mxcubecore): Focused on reliability and observability. Delivered a critical bug fix for Chooch executable path configuration and enhanced logging for directory creation failures, reducing startup errors and improving troubleshooting. Impact: improved startup reliability and operational troubleshooting with clearer logs, minimizing deployment-related downtime. Technologies/skills demonstrated: Python path resolution logic, structured logging and error handling, and maintainability practices.