I have been building Trustcheck, a small Python tool that helps developers verify the trust and integrity of Python packages before installing or using them. Trustcheck gathers signals from sources like PyPI metadata, artifact signatures, publisher credibility, GitHub repo, and other trust indicators, and summarizes them so developers (in report form) and machines (in JSON form) can quickly evaluate whether a dependency looks safe to use.
Right now, the project is in really advanced BETA stage, and I am looking for feedback from developers who install Python packages frequently or care about supply-chain security, in order to push this package to a production-grade level.
Due to the limitations of the dependencies used, this package "trustcheck" can work only on standard python environments like Linux, Windows and MacOS. Android-Termux is not supported. When the dependency "cryptography" adds Termux support, trustcheck can work on that environment too.
I built trustcheck, a Python CLI that evaluates the trust posture of a PyPI release before it is installed, promoted or approved.
trustcheck is currently in BETA and I am looking for real-world testing and feedback to help move it toward production-grade stability. If you are working with PyPI packages, supply-chain security or CI pipelines, I would really appreciate you trying it out and sharing your experience.
I really appreciate the idea and effort you put into building an Artemis 2 tracker dashboard. As an aerospace engineering student, I genuinely appreciate the information, the idea, and the effort that went into building this. The trajectory shape itself is technically a bit off, but honestly that doesn’t really matter here because the vast majority of people using the site aren’t aerospace engineers and aren’t looking for a perfectly modelled trajectory. They are looking for an accessible way to understand all the relevant information.
Also, it’s pretty common to see people immediately label projects as “AI slop.” There are quite a few folks who react that way right away, like @jug did here. That reaction is somewhat expected given how quickly AI has taken off and the existential/job-security concerns many computer engineers are dealing with right now, including the massive layoffs at Google 1-2 years ago.
At the end of the day, using AI to help write code is not that different from hiring a freelancer or contractor to implement parts of a project. The core idea, the decision to build it in the first place, the design choices, the testing, and the overall direction still come from humans. Those parts require thought, effort, and ownership, and that deserves appreciation. Either way, I think projects like this are valuable for sparking curiosity and making technical ideas more approachable to common people, which is always a good thing.