
Worked on enhancing graph visualization and type safety in open-source Python projects. In pyg-team/pytorch_geometric, addressed a longstanding issue where directed edge arrows in graph visualizations did not accurately reflect underlying data, updating the arrowstyle in matplotlib’s FancyArrowPatch to match GraphViz conventions and improve diagnostic reliability. Later, contributed to python/typeshed by refactoring NetworkX type stubs, extracting types from docstrings and updating type annotations to improve code clarity and maintainability. Leveraged skills in Python, Matplotlib, and NetworkX, focusing on targeted, low-impact changes that improved both visual accuracy and type correctness for downstream users and development tooling.
February 2025 | Repository: python/typeshed Focused on strengthening NetworkX typing in the type stubs. Delivered a targeted feature enhancement that improves type hinting, code clarity, and maintainability for downstream usage and tooling.
February 2025 | Repository: python/typeshed Focused on strengthening NetworkX typing in the type stubs. Delivered a targeted feature enhancement that improves type hinting, code clarity, and maintainability for downstream usage and tooling.
Month 2024-11 focused on improving visualization fidelity for directed graphs in pyg-team/pytorch_geometric. Implemented a fix to edge direction in graph visualizations by adjusting arrowstyle in matplotlib.patches.FancyArrowPatch within _visualize_graph_via_networkx to match GraphViz output and the underlying data, preventing misleading graphs. This change enhances reliability of visual diagnostics and reduces debugging time for graph pipelines.
Month 2024-11 focused on improving visualization fidelity for directed graphs in pyg-team/pytorch_geometric. Implemented a fix to edge direction in graph visualizations by adjusting arrowstyle in matplotlib.patches.FancyArrowPatch within _visualize_graph_via_networkx to match GraphViz output and the underlying data, preventing misleading graphs. This change enhances reliability of visual diagnostics and reduces debugging time for graph pipelines.

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