Python 3 Bokeh Heatmap Rect simple example not showing anything in plot

I'm trying to color code a simple categorical heatmap using python's Bokeh library. For example, given the following table, I would want to replace each 'A' with a red square and each 'B' with a blue square:

AAAABAAAAB
BBBAAAABBB

To start, I thought the following would produce 2 rows of 10 squares of the same color. but I just get a blank plot. I must be missing a core concept of how to create categorical heatmaps in bokeh. To start, I was trying to mimic an example on the bokeh site:

https://docs.bokeh.org/en/latest/docs/gallery/categorical.html

Does anyone see what I'm missing? (This is a simple example. I have many rows with hundreds of columns that I need to color by category.)

from bokeh.plotting import figure, show, output_file

hm = figure()
colors = ['#2765a3' for x in range(20)]
x_input = [x for x in range(10)]
y_input = ['a', 'b']
hm.rect(x_input, y_input, width = 1, height = 1, color = colors)
output_file('test.html)
show(hm)

You need to create specific coordinates for each rect. If there are 2 possible values on the y-axis, and 10 possible values on the x-axis, then there are 20 possible unique pairs of coordinates for all the rects (i.e. the cross product of those two lists). For example:

(0, 'A'), (0, 'B'), (1, 'A'), (1, 'B'), ...

If you split each of these tuples into an x-coordinate and y-coordinate, and collect x's and y's into their own lists, they you can see why there must be both 20 x-coordinates and 20 y-coordinates.

Additionally, for categorical coordinates, you have to tell figure what they are. Here is your code updated:

from bokeh.plotting import figure, show

colors = ['#2765a3' for x in range(20)]
x = list(range(10)) * 2
y = ['a'] * 10 +  ['b'] * 10

hm = figure(y_range=('a', 'b'))
hm.rect(x, y, width=1, height=1, fill_color=colors, line_color="white")

show(hm)

The User's Guide section on Categorical Data has much more information on how to use categoricals in Bokeh, including complete examples of heat maps