June 2025 monthly summary for prescient-design/lobster. Focused on introducing a deterministic, rank-based evaluation feature within the DyAbDataFrameLightningDataModule, along with the necessary parameterization to support lead-design comparisons and dataset adjustments. Key features delivered: - Implemented rank-based comparison in DyAbDataFrameLightningDataModule to compare data points against a specified lead design rather than random sampling. - Added parameters to specify lead design information and required dataset modifications to support ranking evaluations. - Verified integration with the existing data module flow, anchored by the commit that introduced the rank functionality: 20cfefcb48538a1bcd819598db3bb0b0db6e7269 ("add 'rank' which compares only to the lead instead of random selection"). Major bugs fixed: - No major bugs documented for this period; emphasis on feature delivery and stability of the ranking path. Overall impact and accomplishments: - Delivered a deterministic, lead-driven ranking workflow, reducing variance in evaluations and improving reproducibility across designs. - Lays groundwork for more reliable decision-making in design comparisons and faster iteration cycles. Technologies/skills demonstrated: - Python data module design and parameterization, data-structure updates for ranking logic, integration with DyAbDataFrameLightningDataModule. - Git-based collaboration and traceability through a descriptive commit. - Emphasis on business value through improved determinism, reproducibility, and clearer evaluation criteria.