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Show HN: 1M rows/s from Postgres to Python

magic.io

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Re: Show HN: 1M rows/s from Postgres to Python

#91
post #65

Earlier quoted context omitted.

It's possible to make a really nice async sqlalchemy core too, and even some of the ORM. huge amount of work, i started on just the connection pool. Would be nice but require all its own test coverage and everything. If i was the CEO of sqlalchemy inc, it would have been done. But that's not where my salary comes from :)

SQLAlchemy is clearly one of the best ORMs (maybe there is something in Java-land that I don't know). It is beyond me how you are not guilted by cash getting thrown in your direction into making this your job. Well, I like what bountysource.com and others are doing, maybe we will get there.

It's the tragedy of open source. See - https://news.ycombinator.com/item?id=10905845

Re: Show HN: 1M rows/s from Postgres to Python

#93
post #90

Earlier quoted context omitted.

The tone used is indeed not the proper one, but while I'm a big asyncio advocate, I think it would be beneficial if you would split your project in 2, separating the IO from the rest (like hyper does https://github.com/Lukasa/hyper ). The rational being: - Python is not just async. It currently majoritarly sync. A lot of the community would benefit from your awesome project; - You'd have contrib from the async and sy…

> I think it would be beneficial if you would split your project in 2, separating the IO from the rest (like hyper does https://github.com/Lukasa/hyper ). I'd like to do that, but we don't have resources. If we had a couple capable devs volunteering on the GH to do this, I'd be glad to review patches and guide the development.

I get that. I have the same problem. And it's not just the ressources, what you need are skilled enough ressources, and that's even harder.

Re: Show HN: 1M rows/s from Postgres to Python

#94
post #21

Earlier quoted context omitted.

"usually deployed" where? Every Python app I've seen in Prod don't use multi process to bypass the limitation of GIL/#cores.

GIL only applies to multi-threaded, not multi-process. Multi-process is a great way to overcome the GIL

At a cost of memory.
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