Monthly summary for March 2026 highlighting delivery of key features, stability work, and business impact for fpsim/fpsim. Focused on aligning the project with modern Python tooling to reduce friction in CI/CD and downstream adoption, while maintaining release hygiene.

February 2026 monthly summary for starsimhub/starsim: Delivered targeted feature enhancements, improved data handling, and release readiness, with a strong emphasis on test coverage and data integrity. Resulting improvements support more expressive data manipulation, robust time-series plotting, and more accurate health modeling, while aligning versioning with ongoing development.

January 2026 (2026-01) – Starsim project (starsimhub/starsim) Key features delivered: - Array subtraction feature added to support subtracting arrays, enabling more expressive data transformations. - Array durations operator support implemented (operators for array durations, not DateArray of durations). - Breastfeeding restructuring experimental changes explored to improve data handling for breastfeeding flow. Major bugs fixed: - Module runs: ensured modules execute without errors, improving pipeline reliability. - Update results method: corrected behavior to reflect accurate results. - Ending breastfeeding pairs: fixed logic to properly terminate pairs. - Backwards compatibility: removed pregnancy module check to improve compatibility with tests. - Delivery timing: fixed delivery calculation for annual timesteps and ensured delivery checks are consistent. - Operator safety: added type checks in __rsub__ and fixed operator delegation. - Time tests and changelog: added additional time tests and updated changelog. - Versioning/docs: updated to version 3.14 and updated deploy action; updated pandas day string for compatibility. - Breastfeeding module refactor and docs: extensive refactor including moving BreastfeedingNet to networks.py, cleaning inheritance, removing extraneous attributes, and exposing the module with improved documentation. - Upstream alignment: merged origin/rc3.1.0 changes to stay aligned with upstream RC. Overall impact and accomplishments: - Stabilized data workflows with new array operations and more robust breastfeeding data handling. - Improved reliability of module execution and CI/CD deployment, enabling smoother upgrades and upstream compatibility. - Expanded test coverage and updated documentation to reduce regression risk for downstream consumers. Technologies/skills demonstrated: - Python refactoring and modular design, including class inheritance adjustments and type safety. - Advanced data handling with array operations and duration logic. - Testing, changelog maintenance, and CI/CD updates (deploy action, versioning). - Documentation improvements and upstream RC alignment.

December 2025 monthly summary for starsim (starsimhub/starsim): Focused on reliability, accuracy, and maintainability to support stable production use and faster release cycles.

Month: 2025-11 — Delivered a focused set of features, stability improvements, and data interoperability enhancements across starsim, driving clearer visualizations, more robust time-series operations, and smoother data exchange with pandas. Plotting axis handling and rendering improvements ensure figures are created on the correct axes and render reliably for small plots. TimePar integration fixes delegate array operations correctly to TimePar operators, improving correctness of time-based workflows. Created duration instances directly from states to simplify duration construction. Strengthened pandas interoperability and added date converters and DateArray support to streamline parsing and formatting. Bug fixes addressed resampling issues and prevented doubling of product method calls, with tests added to cover regressions. These changes improve reliability, developer productivity, and end-user confidence in analytics and visualizations. Technologies demonstrated include Python, pandas integration, date/time tooling, and a focus on deterministic results and improved error messaging.

October 2025 monthly summary for starsimhub/starsim focusing on business value, stability, and release quality. Key features delivered: - Release automation for version 3.0.4: automated publication to PyPI and docs upon new tags; per-Python-version test reports and JUnit outputs; updated documentation and requirements for the 3.0.4 release. - CI/CD enhancements: improved reporting and versioning for 3.0.4, including separate reports per Python version and a streamlined release pipeline. Major bugs fixed: - Internal API cleanup and stability improvements across distributions, Module, RNG, and screening: simplified lognorm/lognormal initialization, tightened error handling, guarded screening outcomes, and RNG jump behavior to avoid spurious errors. - Improved error messaging and robustness, reducing post-release investigation and hotfixes. Overall impact and accomplishments: - Faster, more reliable releases for Python environments with clearer visibility into test outcomes and versioned artifacts. - Increased runtime stability in core modules, lowering post-release defect risk and improving user confidence. Technologies/skills demonstrated: - Python packaging and PyPI release automation, CI/CD pipeline enhancements, and test reporting (JUnit-like outputs). - API refactoring and error handling improvements, RNG state management, and improved logging. - Documentation and release process alignment with pyproject.toml, changelog maintenance, and requirements updates.

July 2025 monthly summary for starsim hub focusing on stability and bug fixes in the infection simulation path. No new features shipped; major bug fix was implemented to Infection.route.net_beta to ensure correct argument passing and prevent runtime errors, improving reliability for end-to-end simulations and downstream analytics.

Monthly Summary — May 2025 (starsimhub/starsim) Key features delivered - Simulation API stability and time handling improvements: Stabilized and modernized the simulation API by removing deprecated unit attributes, enforcing keyword arguments for disease constructors, and clarifying time step handling and initialization. Result: clearer API surface, easier onboarding for users, and reduced maintenance burden. - User input handling and error messaging improvements: Strengthened input validation for demographics rates and time-duration calculations, added warnings for bare numeric rates, and provided clearer, actionable error messages. Result: safer user configurations and improved user experience. - TimeProb/RateProb functionality enhancements: Extended time-probability functionality with new to_prob/scale methods, improved arithmetic behavior, and added tests for TimeProb/RateProb calculations. Result: more robust probabilistic modeling and safer composition of probability utilities. - Performance optimizations and modeling enhancements: Implemented float-casting optimizations, faster death-probability calculations, and stochastic durations in MFNet to boost throughput and realism. Result: faster simulations with more realistic duration modeling. - Testing data and baseline configuration updates: Updated test suites and baselines to reflect new behavior and ensure consistent expectations across models. Result: improved regression protection and reliability of results. Major bugs fixed - Removed residual deprecated attributes and cleaned initialization paths in the Simulation API to prevent runtime errors and confusion. - Fixed a type bug in TimeProb/RateProb arithmetic and added support for unary minus operator to ensure correct negative value handling. - Improved input validation: addressed missing arguments and enhanced error messaging for demographic rates and time-related calculations. - Updated testing baselines and data to align with new behavior (e.g., dt units in tests), ensuring stable expectations across models. Overall impact and accomplishments - The May 2025 release delivers tangible business value through a more reliable, faster, and easier-to-use simulation platform. End users benefit from safer configurations, clearer feedback, and quicker iteration cycles. Technical improvements reduce maintenance cost and improve model fidelity, enabling more accurate scenario planning and risk assessment. Technologies/skills demonstrated - Python API design and refactoring, time management in simulations, probabilistic modeling (TimeProb/RateProb), performance optimization, test-driven development, and baseline/data maintenance. Committed across repository starsimhub/starsim: - Implemented across five feature areas addressing API stability, input validation, probabilistic arithmetic, performance, and test data updates.

April 2025 monthly summary for the starsim module. Focused on reliability and data-access efficiency, delivering two core updates: (1) boolean indexing in the Arr class, and (2) Time.now robustness with improved handling for negative time indices and Dur-based stop scenarios. These changes reduce edge-case failures, improve data selection fidelity, and strengthen the time API for simulations and analytics.

March 2025 monthly summary for starsim (starsimhub/starsim). Highlights include core bug fixes and compatibility improvements across core calculations, plotting capabilities enhancements, and the addition of a distance-time (dt) factor, all contributing to more reliable simulations. The month also advanced transmission functionality, expanded feature support (bare-number backward compatibility, act rates in sexual networks, and GAVI work), and strengthened code quality through refactoring, test stabilization, and maintenance work. Overall, the work reduces risk, improves accuracy and usability for downstream users, and positions the project for upcoming features and long-term maintainability.

February 2025 monthly summary focused on delivering a foundational feature refactor for time-dependent parameters across Starsim, with progress toward standardization of rates, durations, and start dates. The work emphasizes accuracy, robustness, and maintainability in time-varying simulations, aligning with business value goals.

January 2025 performance summary for starsimhub/starsim. Focused on advancing core simulation capabilities, improving numerical time handling, expanding network-based disease transmission modeling, and restoring test coverage to ensure reliability. The work strengthens the foundation for accurate, scalable simulations and supports client-facing offerings with more robust vaccine initialization and API semantics.

December 2024 monthly summary for starsimhub/starsim focused on strengthening API resilience and time modeling. Delivered enhancements to the Samples API to gracefully handle missing identifiers and updated identifier handling semantics to improve reliability. Introduced a robust Time/Date model with new types (Date, Dur, YearDur, DateDur) and updated Time to support both absolute and relative time vectors, enabling more precise scheduling and analytics. These changes improve data integrity, reduce edge-case failures, and provide a foundation for more advanced time-based features.