https://mail.python.org/archives/list/python-dev@python.org/...
(Mark Shannon has been a core dev since 2018-05-15: https://devguide.python.org/developers/ though his involvement dates back to 2011 according to git log.)
This is something that I feel that Python need to do to keep the relevance. .Net Core, Rust and GoLang are examples of modern languages that deliver on the performance front.
I love Python and it is what use everyday. But very often I feel the need to a better code generation. Numba and Cython feels like a glue. PyPy it is slow with extensions, and this is a huge part of Python ecosystem. Although HPy (https://github.com/hpyproject/hpy) is trying to change this.
I feel that this is a must to Python, and would love to contribute money to this task.
And yeah, I would be happy to pitch in too if CPython can be 50% faster reliably. It only takes 500 people each pitching in $100 to reach $50k.
Edit: somehow got $50k etched in mind when it says $500k. That’s more difficult from individual funding.
Hpy appears to be the right approach to fixing this, but there needs to be a concerted effort to migrate the ecosystem toward it and then deprecate the old expansive interface. And then at some point in the distant future we can expect things to be as nice as other ecosystems are today.
Python and Ruby are trapped in the C extensions spiral. Languages are slow so everything uses C bindings, which makes it hard to speed up the language
I do believe this will be hard to change, though: Coming from academia my first Python experience was as a front-end to actively developed Fortran code. In that segment, the easy link to external code is one of the main selling points of Python.
You can write fast native you. You can write fast code by calling into native. The two rarely cross.
If we were clever, we could even have one front-end and multiple backends to go into fast Python, CPython, Cython, embedded micropython, etc. If we were double-plus-clever, we'd add GPGPU, multicore, and compute cluster to the mix.
We'd need someone with deep pockets and high risk tolerance to pull it off. It's a big change. Big changes often fail. Still, when I look at the amount of Python at Google... Well, it'd sure be a pity if all of that became legacy code when we all jumped ship to Julia.
> > 1. I already have working code for the first stage.
> I don't mean to be negative, or hostile, but this sounds like you are saying "I have a patch for Python that will make it 1.5 times faster, but you will never see it unless you pay me!"
and
> Where is your working code for the first stage?
> I believe that's how business works ;)
> I have this thing, e.g an iPhone, if you want it you must pay me.
> I think that speeding CPython 50% is worth a few hundred iPhones.
I wonder if he considered publishing it under a restrictive license that doesn't allow real world use. Then people could scrutinize his claims but there would still be an incentive to pay up for him to relicense it.
50k is about 3 months worth of a single FAANG developers base salary. It’s well worth it for someone to pay for the code.
But in the new corporate Python world this might be the logical conclusion. The losers are the people who made Python what it is today, for free.
Why are they "losers"? Did they sign any contract that something is owned to them? They did it for fun/personal reasons/ideology, and what they created is used by millions.
If they wanted to get paid for doing it, they could very well have had as well - several core python contributors have worked in large companies doing Python (including core Python) work, most famous of all Guido.
I don't see the pattern that the core contributors who work for large companies do important work. A lot of it is churn and minor patches.
Most important work appears to have been done by people who contribute a large chunk of code and then often leave.
Or by people who don't work for large companies but did a lot of useful bug fixes.
The PSF couldn't merge the code until it has the right license.
Large tech companies like Google wouldn't be willing to use the code until it has the right license.
If releasing the code under "look, don't touch" terms helps convince them that paying is worth it then that seems like a good idea.
Why not release this super-dooper Python interpreter under a proprietary license? Just have people pay $1000 for it. If it works, then it’s a steal for people who use Python for business. “Well, you have to take me at my word and pay me first” is highly suspect.
I’ll use PyPy, thanks.