January 2026 (2026-01) - scvi-tools focused on standardizing training configuration to improve reliability, reproducibility, and onboarding for experiments. Key work centered on introducing explicit configuration objects, expanding test coverage, and updating docs to reflect a clearer API for training pipelines. Key deliverables: - Key feature delivered: Structured Training Configuration via TrainingPlanConfig and TrainerConfig dataclasses to replace loose keyword arguments, with a shared merge helper and additive config semantics. Commit ec2ff107f8f6febd2e0b909d985f96fe1af4fb34 demonstrated end-to-end integration including plan_config/trainer_config wiring through TrainRunner and training wrappers, plus docs and unit tests. - Documentation and user onboarding improvements: API docs updates and a new user guide page to document the new configuration pattern. - Test coverage: Added unit tests for config merging behavior (tests/train/test_trainingplans.py and tests/train/test_config.py) to ensure stability of the new pattern. Major bugs fixed: No distinct major bugs reported this month for scvi-tools in this scope; focus was on feature delivery and strengthening test coverage for configuration patterns, with existing tests expanded to cover the new config objects. Overall impact and business value: - Improved reliability and reproducibility of training runs by standardizing configurations, reducing misconfiguration risk, and smoothing experiment onboarding for new users. - Increased maintainability and scalability of training pipelines through explicit config objects, which supports more robust experiments and easier collaboration across teams. Technologies/skills demonstrated: - Python dataclasses for explicit configuration objects (TrainingPlanConfig, TrainerConfig) - Config merging design patterns and additive configuration semantics - Integration testing and unit tests (pytest) for config behavior - Documentation and user-guides to enable adoption and reproducibility