+1 to just using conda for all basic infrastructure packages if the host 
doesn't have them. Just put a conda env in the PATH and done.

In my experience these work really well. I've only gotten issues with conda 
when you veer off the trodden path too much, e.g. I've had nothing but 
trouble installing ruby from conda-forge and then trying to build gems on 
top of that (ruby has various hard-coded compiler configuration paths, some 
of which point to the wrong place). 


On Saturday, April 29, 2023 at 1:25:26 AM UTC+2 Matthias Koeppe wrote:

> On Thursday, April 27, 2023 at 1:24:01 AM UTC-7 Dima Pasechnik wrote:
>
> The next in line will be jupyter and friends.
>
>
> I agree with this point; specifically the front-end parts of 
> Jupyter/JupyterLab, which run in a separate Python process (and therefore 
> can be installed in a completely separate tree / venv). For this idea, we 
> have the the long-open metaticket 
> https://github.com/sagemath/sage/issues/30306 
>
> But this observation can be generalized. 
>
> For any package from which we only use executables or data, not a shared 
> library, we can install it in any way we want -- without compromising the 
> Sage distribution's ability to use already installed system packages.
> So we can switch from our own installation scripts to using conda-forge 
> for these!
>
> I've written up the details in 
> https://github.com/sagemath/sage/issues/35583
>
> I'm counting about 40 packages (not counting the Jupyter frontend 
> components) for which we can make a safe and easy withdrawal from packaging 
> activities, WITHOUT making the Sage distribution harder to install, and 
> avoiding the "concave cost" along the path that I mentioned.
>
> (Note that gcc/gfortran do not fall into this category of packages because 
> of their runtime library components.)
>
>

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