One advantage I've noticed at least (having been a contributor to the Julia language itself), is that it at least makes contributing to the language very approachable. Granted you see lower quality proposals from time to time, but in general, I even question whether I myself would have gotten involved or been brave enough to propose language features if I would have had to do such a rigorous, formal PEP writeup. In some respects, you're restricting the pool of people who actually contribute ideas to the language.

I also have appreciated the "meritocratic" approach of Julia language features; if someone can show that an idea/approach/algorithm is fundamentally faster, more flexible, etc. it's generally been accepted, regardless if the proposer is a first-time contributor or not. That also makes contributing feel approachable and very fair, as opposed to just trying to please a single core developer or playing some politics game.

> if someone can show that an idea/approach/algorithm is fundamentally faster, more flexible, etc. it's generally been accepted, regardless if the proposer is a first-time contributor or not.

If you can submit a measurably faster csv implementation to cpython (without breaking existing code of course) I can guarantee it will be welcome whether you’re a first time contributor or not. Not sure about your definition of “more flexible”, if that entails breaking existing code then it may rightfully meet resistance.

Not sure why you’re implying other languages’ proposal processes are about pleasing a single core developer or playing some politics game. Sounds like either you have a lot more experience than I do and hence have been exposed to politics games or anything else non-meritocratic (that I haven’t sensed in CPython development, at least), or you just don’t have as much experience contributing to other languages.

(I'm a bit cranky today. Sorry if I sound aggressive.)

No worries, it doesn't come off that aggressive ;)

Yes, I've definitely been involved in other projects where a single core developer can do a little too much "imposing" of their will. i.e. if they happen to have a personal preference one way or another on things, they not accept or even entertain certain changes.

I wouldn't expect most large, mature projects to be this way (otherwise they probably wouldn't have grown as large or attracted enough of a community!), but it's certainly a problem with some projects.

> it's certainly a problem with some projects.

Projects, of course. Ages ago I quit a notable project partly because of maintainer team politics, so I'm no stranger. But I thought we were specifically talking about language improvement processes of non-niche programming languages (a specific one, even).

> If you can submit a measurably faster csv implementation to cpython (without breaking existing code of course) I can guarantee it will be welcome whether you’re a first time contributor or not.

I wouldn't be so sure. Search for `site:bugs.python.org "maintenance overhead"` on your favourite search engine.

8 results total, with exactly one entry that’s remotely relevant (i.e. performance related, patch provided) — bpo-21955. You could have just linked that. And this happens to be a patch from a core dev. And it’s not comparable to submitting a performant implementation of a PSL module like csv. You have chosen a pretty convincing example, I don’t know what I’m supposed to be convinced of though.

https://bugs.python.org/issue21955

On the other hand, many important things move at a grinding pace in Python. Packaging and performance are two major issues for just about everyone I’ve spoken with who uses Python in a serious capacity, and these have been notorious problems for decades with no end in sight. Most of this seems to boil down to an unwillingness to encourage the ecosystem towards a narrower packaging format (“sorry, downloading a package and running setup.py just to determine the dependency set is insane and we’re going to deprecate that going forward”) or a narrower C extension interface that would be compatible with more aggressive optimizations. There’s value in stability, but if the governance model can’t pass these kinds of slow, steady changes for paramount issues, then perhaps new languages shouldn’t look to Python as a model for a well-governed language.

I would suggest Rust—I’m not a fanboy by any means, but Rust is a large, rapidly growing project that is unparalleled with respect to its rate of improvement as far as I’m concerned. I know recommending Rust for things is a cliche (esp “rewrite it in Rust”), but I would defy anyone to find a better governed language.

I find Rust really difficult to get into :( Python, you're right has a bunch of problems with datetime and packages, etc. but when it comes to productivity, it is insane how amazing Python is. Also being able to hack internals of python library and "batteries included" philosophy is why it is the most popular language in the world now overtaking Java.

Rust does have a steep learning curve and Python is a very productive language... until you are the one responsible for builds and deploys, or performance, or concurrency, or quality, or etc. I think you’ll find that Go hits a nice sweet spit between all of those competing concerns even if it isn’t the best at any of them (in general; however, probably not for data science in particular).

Thanks, I am willing to try both Rust and Go.

> Python's PEP / RFCs

Is this process actually fundamentally better? There are so many PEPs that are up to the reader to interpret. There are so many PEPs that contradict each other (just read some of the early PEPs). The whole thing feels basically meaningless, and toothless at this point.

I think Go's proposal process nails balancing formalities and discussion/bikeshedding. They seem to be very productive at making the language better, thinking critically and avoiding regrets, rather than pandering to the very vocal and often misaligned minority of the community.

I can’t even tell if this is a bad faith attack or genuine cluelessness.

No, language features, standard library modules, infrastructure implementations, standard APIs, development and community processes, etc. etc. aren’t “up to the reader to interpret”, aren’t “basically meaningless”, aren’t “toothless”, especially not “at this point”. Informational PEPs are informational.

python-committers also aren’t a misaligned minority of the community. If you feel committers don’t serve your interest, step up and start contributing.

Can you provide some meaningless and toothless examples? Which PEPs disagree with which ones?

I think PEPs, RFCs, and formal processes are designed to keep structure and discipline. It may sound like unnecessary beauracracy but you see this in PostgreSQL development process as well. Vast number of critical pieces of software is developed by this process - from Linux to proprietary software in large companies such as Apple, Morgan Stanley and many many more.