Comment by kzrdude

I just used this in the Jupyter notebook (toldya it was very simple, written today :).

It interoperates with python by being passed data to the draw call.

Usage like: c = Canvas(); c.draw(xs); xs is a numpy array of shape (N, 2), the points to draw on the canvas.

It's not fancy. But it drew animations faster than matplotlib (I ran this for thousands of frames, just to watch the simulation).

    import IPython.display as ipydisplay
    import json
    import numpy as np

    class Canvas:
        def __init__(self, canvas_id=None, width=500, height=500):
            self.display_id = None
            self._canvas_id = canvas_id or ('canvas_' + str(np.random.randint(0, 10000)))
            display(ipydisplay.HTML(f"""

            <canvas id="{self._canvas_id}" width="{width}" height="{height}" style="border:1px solid #d3d3d3;">
            Your browser does not support the HTML5 canvas tag.</canvas>
            """))

        def draw(self, xs, world_size):
            xs_string = json.dumps(xs.tolist())
            obj = ipydisplay.HTML(f"""
            <script>
            var c = document.getElementById("{self._canvas_id}");
            var ctx = c.getContext("2d");
            var xs = {xs_string};
            var size = {world_size};
            ctx.clearRect(0, 0, c.width, c.height);
            var scale = c.width / size;
            for (let i = 0; i < xs.length; i++) {{
                ctx.fillRect(xs[i][0] * scale, c.height - xs[i][1] * scale, 2, 2)
            }}
            </script>
            """)
            if self.display_id:
                ipydisplay.update_display(obj, display_id=self.display_id)
                return self.display_id
            self.display_id = display(obj, display_id=True).display_id