let me do `pip install numpy2` and not have to worry about whether or not some other library in my project requires numpy<2.
From a project point of view, there are some pretty strong contra-indicators in the last 20 years of language development that make this plan suspect, or at least pretty scary — both Perl and Python had extremely rocky transitions around major versions; Perl’s ultimately failing and Python’s ultimately taking like 10 years. At least. I think the last time I needed Python 2 for something was a few months ago, and before that it had been a year or so. I’ve never needed Perl 6, but if I did I would be forced to read a lot of history while I downloaded and figured out which, if any, Perl 5 modules I’m looking for got ported.
I’d imagine the numpy devs probably don’t have the resources to support what would certainly become two competing forks that each have communities with their own needs.
My point, or at least the point I had in mind, was that the social and technical go together in a lot of subtle and sometimes surprising ways; in this case, I’d bet the idea of a second package name a) is a bad one because it’s likely to create differing community expectations about whether or not it’s okay to keep using the 1.0 package, and b) would let people feel okay not upgrading for a while / demanding security and bug fix point releases on 1.x longer than if the package itself just updates its major version.
raku has good package compatibility via Inline::Perl5 and Inline::Python and FFI to languages like Rust and Zig
among the many downsides of the transition, one upside is that raku is a clean sheet of paper and has some interesting new work for example in LLM support
I have started work on a new raku module called Dan::Polars and would welcome contributions from Numpy/Pandas folks with a vision of how to improve the APIs and abstractions … it’s a good place to make a real contribution, help make something new and better and get to grips with some raku and some rust.
just connect via https://github.com/librasteve/raku-Dan-Polars if you are interested and would like to know more
One huge pain point for me in perl 5 was just how incredibly slow CPAN was compared to `go import`, like two orders of magnitude slower. I remember putting up with those times in the ‘90s because package management was a kind of miracle over FTP sites, but it’s a big ask in today’s world.
What’s raku’s story here, out of curiosity?
the raku package manager - zef comes bundled with the rakudo compiler - I use https://rakubrew.org
https://raku.land is a directory of raku packages
I would say that zef is very good (it avoids the frustrations of Python package managers like pip and conda) like perl before it, raku was designed with packages and installers in mind with a concern for a healthy ecosystem
for example, all versions (via the META6.json payload descriptor) carry versioning and the module version descriptor is a built in language type https://docs.raku.org/type/Version that does stuff like this:
say v1.0.1 ~~ v1.*.1; # OUTPUT: «True»
zef install Dan::Pandas:ver<4.2.3>:auth<github:jane>:api<1>
use Dan::Pandas:ver<4.3.2+>:auth<github:jane>:api<1>;
So at least the migration path for python modules is clear: upgrade to be numpy 2 compatible, wait for critical mass, start adding numpy 2 features. Sounds way better than python2 -> python3 migration, for example.
However, the fact that I had to look at 3rd party page to find this out is IMHO a big documentation problem. It should be plastered in all announcements, on documentation and migration page: "there is a common subset for python code of numpy 1 and 2, so you can upgrade now, no need to wait for full adoption"