There's a lot of important work that happens in python. Most of it isn't being done by software engineers. I think the idea of improving things for that group is plenty meaningful.
I like that python is trying to work with projects that have become large and essentially help support it, hopefully much good comes out of this like libraries being upgraded etc.
I read their about page and it seems they want to make Python dev more productive. Maybe they have a lot of projects using it and are tired of the tooling/packaging BS. I could definitely see someone making billions allocate under 1% of it towards fixing that.
Improving Python is especially cheap compared to the productivity that could be unleashed. Surprised it isn't done more often. Only microsoft has shown significant interest, which is a shame. Perhaps changing.
It seems to me that the opportunity cost of these improvements is not as big as it could be, as this team is separate from the other Python development folks.
Software isn't a finite problem that gets solved. We make what we can, given our resources.
Commercial software used to be painstakingly written in assembly, with little more than simple text editors. An average Python programmer today is 10x more productive than that, yet there are vastly more developers now.
Thank you. Yes it is good to see some projects stepping up the fill the gaps. I only wonder as time goes on how well socialized these will be...and if people who suddenly find themselves in the position of maintaining an old Python code base will be able to find out what to do.
Another big issue to keep in mind when critiquing Python, as opposed to e.g. JavaScript or Ruby, is that Python is used for so much more besides webdev/etc. stuff. So making changes that improve life for webdevs could suddenly make life worse for people using Python in high energy physics, or in chemical engineering, or in AI research, or a large number of other fields that a webdev might not even know exists. Every supercomputer on the planet runs Python code, scientific Python usage is a really big field, with enough passionate users to hold multiple conferences every year; orders of magnitude more in casual users.
I mean you're not wrong; they built working software in Python, solved a problem, scaled it, and learned about the problem it solved. Once they understood it, they could monitor it. Once they had numbers, they could look into improving it, taking their learnings on the problem and picking a different language / architecture to solve it.
It's not that hefty once they pitch this improvement to the many wealthy VC-funded companies whose business and data science divisions depend on Python.
Yeah it’s just that Python dominates some ecosystems like machine learning. There isn’t much of a choice, so making these code based more maintainable is a valiant effort
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