[korijn]

I have worked with poetry professionally for about 5 years now and I am not looking back. It is exceptionally good. Dependency resolution speed is not an issue beyond the first run since all that hard to acquire metadata is actually cached in a local index.

And even that first run is not particularly slow - _unless_ you depend on packages that are not available as wheels, which last I checked is not nearly as common nowadays as it was 10 years ago. However it can still happen: for example, if you are working with python 3.8 and you are using the latest version of some fancy library, they may have already stopped building wheels for that version of python. That means the package manager has to fall back to the sdist, and actually run the build scripts to acquire the metadata.

On top of all this, private package feeds (like the one provided by azure devops) sometimes don't provide a metadata API at all, meaning the package manager has to download every single package just to get the metadata.

The important bit of my little wall of text here though is that this is all true for all the other package managers as well. You can't necessarily attribute slow dependency resolution to a solver being written in C++ or pure python, given all of these other compounding factors which are often overlooked.

[odie5533]

Try uv. You will be shocked how much faster it is.

[korijn]

I will! I'm sure it's faster when the data is available. But when it's not, in the common circumstances described above, network and disk IO are still the same unchanged bottlenecks, for any package manager.

In conversations like this, we are all too quick to project our experiences on the package managers and not sharing in what circumstances we are using them.