
Chris Mahoney developed comprehensive dashed marker line support for the plotly/plotly.js repository, enabling per-point dash customization and consistent dash styling across various scatter trace types, including 3D and geo variants. He implemented the marker.line.dash attribute with calcdata integration, ensuring both trace-level defaults and dynamic per-point styling. Using JavaScript and D3.js, Chris refactored the dash styling pipeline for improved maintainability, simplified stroke handling, and enhanced legend alignment. He also addressed CI robustness by fixing test gaps and ensuring reliable dash rendering. This work improved data visualization flexibility, reduced manual styling, and strengthened production reliability for front end charting applications.
December 2025: Implemented comprehensive dashed marker line support (marker.line.dash) across core and extended traces, enabling per-point dash customization, legend-aligned visuals, and Chart Studio Cloud integration. Fixed CI/test gaps for dash styling and simplified the stroke styling pipeline to improve maintainability and reliability. Extended dash styling to 3D and other scatter variants (scatter3d, scattergeo, scattergl, scatterternary, splom) with consistent defaults and constraints. Ensured blank points render without outlines, and added dashsrc for data-source references to enable dynamic styling. This work enhances visual storytelling, reduces manual styling work, and improves production reliability.
December 2025: Implemented comprehensive dashed marker line support (marker.line.dash) across core and extended traces, enabling per-point dash customization, legend-aligned visuals, and Chart Studio Cloud integration. Fixed CI/test gaps for dash styling and simplified the stroke styling pipeline to improve maintainability and reliability. Extended dash styling to 3D and other scatter variants (scatter3d, scattergeo, scattergl, scatterternary, splom) with consistent defaults and constraints. Ensured blank points render without outlines, and added dashsrc for data-source references to enable dynamic styling. This work enhances visual storytelling, reduces manual styling work, and improves production reliability.

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