Either pay for the product, or use stuff that isn't dependent on VC money, this is always how it ends.
Maybe you use non-transitive pure Python dependencies, but it's likely that your tools and dependencies still rely on stuff in Rust or C (e.g.: py-cryptography and Python itself respectively).
As mentioned multiple times, since my experience with Tcl and continuously rewriting stuff in C, I tend to avoid languages that don't come with JIT, or AOT, in the reference tooling.
I tend to work with Java, .NET, node, C++, for application code.
Naturally AI now changes that, still I tend to focus on approaches that are more classical Python with pip, venv, stuff written in C or C++ that is around for years.
Consider ffmpeg. You can donate via https://www.ffmpeg.org/spi.html
How much money do they make from donations? I don't know but "In practice we frequently payed for travel and hardware."
Translation: nothing at all.
If such a fundamental project that is a revenue driver for so many companies, including midas-level rich companies like Google, can't even pay decent salaries for core devs from donations, then open source model doesn't work in terms of funding the work even at the smallest possible levels of "pay a reasonable market rate for devs".
You either get people who just work for free or businesses built around free work by providing something in addition to free software (which is hard to pull off, as we've seen with Bun and Astral and Deno and Node).
At worst, it's just Anaconda II AI Boogaloo. The ecosystems will evolve and overcome, or will die and different ecosystems rise to meet the need going forward.
I anticipate OpenAI will get bored and ignore Astral's tools. Software entropy will do its thing and we will remember an actively developed uv as the good old days until something similar to cargo gets adopted as part of Python's standard distribution.