mojo-asciichart v1.1.0 
ASCII line charts for Mojo with colors and proven performance gains
from asciichart import plot, ChartColors, Config
var latencies = collect_api_latencies() # Monitor ML serving
var config = Config()
config.colors = ChartColors.fire()
print(plot(latencies, config))
Output:
101.90 ├ ╭╮
74.78 ├ ╭╮ ││ ││
47.66 ├ │ │ ╭─╮ ╭╯╰╮ ││ ││
20.54 ┤───╯ ╰──╯ ╰──────────────╯╰─────╯╰─╯╰──╯╰──╯
📊 Mean=25.3ms | P95=63.7ms | Max=101.9ms
- Output didn’t survive cut n paste / markdown formatting?!
v1.1.0 Highlights
6 color themes (matrix, fire, ocean, blue, rainbow, default)
1.4-4.3x faster than Python asciichartpy
ML serving example - realistic production monitoring
Benchmarked with my prototype BenchSuite (auto-generated reports)
29 tests - pixel-perfect Python compatibility
CI/CD - automated .mojopkgbuilds
Quick Start
git clone https://github.com/DataBooth/mojo-asciichart.git
cd mojo-asciichart
pixi install
pixi run example-ml-serving # See realistic use case!
Links
GitHub (Apache 2.0)
Detailed Announcement
Note also CREDITS.md
Personal Note 
This wraps up my intensive “Month of Mojo” learning journey! It’s been good although hectic. Now off to enjoy the Australian summer at the beach! ![]()
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Repos remain monitored - issues and contributions welcome!