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Python-based compiler achieves orders-of-magnitude speedups

news.mit.edu

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Re: Python-based compiler achieves orders-of-magnitude speedups

#121
Since this is highly incompatible with most python ecosystem right now, may I plug nuitka?

https://nuitka.net/index.html

It's a compiler for python code that can create stand alone executables, and up to 4 times the speed of the initial code.

Best of all, it's extremely reliable, with a high level of support of event the tricky things like the scientic and gui stacks.

Re: Python-based compiler achieves orders-of-magnitude speedups

#124

Earlier quoted context omitted.

Ye well if you remove the dynamic feutures of a dynamic language it gets fast. It would be really impressive of they can achieve those feutures with the sameish speed.

I dont necessarily need all that dynamism though, and would happily use a Python subset that removed some stuff (and forced type hinting) in exchange for better compilation. Yes there are already subsets like this, but its not as helpful if it isnt standard.

[deleted]

Re: Python-based compiler achieves orders-of-magnitude speedups

#125

Earlier quoted context omitted.

I dont necessarily need all that dynamism though, and would happily use a Python subset that removed some stuff (and forced type hinting) in exchange for better compilation. Yes there are already subsets like this, but its not as helpful if it isnt standard.

Depends of the work you have to do. If you code a website, fast api and django, the two most popular framework to do so, heavily rely on them to make you productive.

If you code a website, your speed issues probably come from the database layer. Not your Python.

Re: Python-based compiler achieves orders-of-magnitude speedups

#126

Since this is highly incompatible with most python ecosystem right now, may I plug nuitka? https://nuitka.net/index.html It's a compiler for python code that can create stand alone executables, and up to 4 times the speed of the initial code. Best of all, it's extremely reliable, with a high level of support of event the tricky things like the scientic and gui stacks.

Seconded, I deploy large packages with gigabytes of deep learning and GIS dependencies in single executables with Nuitka and it works very well. Also handles including data files into the executable if needed.

Re: Python-based compiler achieves orders-of-magnitude speedups

#127
post #56

Paper here: "Codon: A Compiler for High-Performance Pythonic Applications and DSLs": https://dl.acm.org/doi/pdf/10.1145/3578360.3580275 "Currently, there are several Python features that Codon does not support. They mainly consist of runtime polymorphism, runtime reflection and type manipulation (e.g., dynamic method table modification, dynamic addition of class members, metaclasses, and class decorators). There are…

Ye well if you remove the dynamic feutures of a dynamic language it gets fast. It would be really impressive of they can achieve those feutures with the sameish speed.

[deleted]

Re: Python-based compiler achieves orders-of-magnitude speedups

#128
Second post on this in two days? Had a show HN yesterday. We appreciate the info but dont plug an incomplete product so hard, especially one that doesn't really give other options a fair assessment on their website. Eg. no mention/discussion of nuitka, jax, etc.

Re: Python-based compiler achieves orders-of-magnitude speedups

#129
post #98
post #84

Earlier quoted context omitted.

> This seems easier to get right than if( x = *p++ ) For people with native or fluent English, for sure. For the others, probably not.

What level of English fluency should we expect of professors at MIT and writers for their site?

_The Shaft_, a Georgia Tech periodical (similar to _The Onion_ in spirit), interviewed a local associate professor: "How can I be expected to teach math if my students don't speak basic Mandarin?"

Re: Python-based compiler achieves orders-of-magnitude speedups

#130
This is super cool and useful. I know that Instabase , which also came from MIT got really popular and useful within finance communities because they allowed for really fast and efficient compute through their own Python DSL. Good to see this as an open source project which everyone can now use.
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