There’s a secondary pro and con to this pipeline: since the code is compiled, it avoids having to specify as many dependencies in Python itself; in this package’s case, Pillow for image manipulation in Python is optional and the Python package won’t break if Pillow changes its API. The con is that compiling the Rust code into Python wheels is difficult to automate especially for multiple OS targets: fortunately, GitHub provides runner VMs for this pipeline and a little bit of back-and-forth with Opus 4.5 created a GitHub Workflow which runs the build for all target OSes on publish, so there’s no extra effort needed on my end.
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Building this system requires understanding of Make.com's interface and basic automation concepts, but it's accessible to anyone willing to invest a few hours in setup. The difficulty level sits at intermediate—more complex than basic automation but far simpler than custom programming. Once configured, the system runs automatically on whatever schedule you set, collecting data and building a historical record of your AIO performance.