A tool for making excalidraw figures procedurally from python.
Its very easy to visualize excalidraw files either from web (just load the file at excalidraw.com) or with a vs-code plugin (simply open a .excalidraw file in vscode).

• removed setup.py, migrated to poetry
• changed folder structure
• added own examples

You need poetry installed.
Then simply run poetry install

Then you can create excalidraw files as follows:

from procXD import SketchBuilder, Text
sketch_builder = SketchBuilder()
text_elem = Text(text="Hello, World!")
# Helper example: create bounding boxes
bbox_elem = sketch_builder.create_bounding_element(text_elem, return_group=False)
sketch_builder.draw_objs.extend([bbox_elem, text_elem])
save_path = "temp.excalidraw"
sketch_builder.export_to_file(save_path=save_path)

If you have large configurations, it might be useful to visualize the configuration tree. Helpful for debugging and to confirm variations between different ablations. Detailed example in examples/config_vis.py.

We can visualize configuration (YACS objects) as below using SketchBuilder.render_stack_sketch.

Alternatively, we can also compare different configurations with SketchBuilder.render_comparitive_stack_sketch

You may want to create a excalidraw graph procedurally for precision. Some examples in examples/proc_figures.py.

It might also be useful for converting arbitrary graphs from networkx to excalidraw figures. The benefits are two-folds: SVG format helps manage resolution, and the arrows are bounded between elements which means you can move the graph around!

1. Support Images.

2. Converter for SVG: Will be nice to convert datasets like FIGR-8 into excalidraw format. That way, output of SVG optimization works (such as Vector-Fusion) can be viewed in excalidraw as well!

1. Versioning
2. Exact text bounding box size - as a result the text bounding box sizes are adjusted in the file when the file is opened with excalidraw.

I used ChatGPT while creating this tool. It was helpful in many ways, but also misleading at times (especially for visual math functions).