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Seq – A programming language for computational genomics and bioinformatics

github.com

1–10 of 59 posts

Re: Seq – A programming language for computational genomics and bioinformatics

#4
post #3

Looks great, will definitely give this a try since it does sequence manipulations that I otherwise have to write myself. Will this be available via conda? And how would seq integreate with Snakemake, since that is also based on Python?

Seems like there's a conda package in the works: https://github.com/bioconda/bioconda-recipes/pull/29660

Re: Seq – A programming language for computational genomics and bioinformatics

#6
> Seq is a Python-compatible language, and the vast majority of Python programs should work without any modifications

> Seq is able to outperform Python code by up to 160x.

So ... a reimplementation of Python that can outperform cpython by over 100 times? I know literally nothing about this project, but I have to say that rings pretty false for me. Hell, even PyPy has trouble with many applications. (Plus they're claiming to outperform "equivalent" C code by 2x.)

Even if the performance claims are overblown, it's always nice to see new work on compiled languages with easy-to-read syntax. It's hard to beat Python for an education / prototyping language, so I will definitely be giving this a look.

Re: Seq – A programming language for computational genomics and bioinformatics

#7
post #6

> Seq is a Python-compatible language, and the vast majority of Python programs should work without any modifications > Seq is able to outperform Python code by up to 160x. So ... a reimplementation of Python that can outperform cpython by over 100 times? I know literally nothing about this project, but I have to say that rings pretty false for me. Hell, even PyPy has trouble with many applications. (Plus they're cla…

I also know literally nothing about this particular project, but why not? If you support a small restricted subset of Python it's completely doable under certain conditions for specific types of programs. E.g., Numba can easily outperform Python 100-1000x in numerical applications (done it myself multiple times), simply because it jit-compiles the code by first translating it to LLVM IR.

Re: Seq – A programming language for computational genomics and bioinformatics

#8
post #7
post #6

> Seq is a Python-compatible language, and the vast majority of Python programs should work without any modifications > Seq is able to outperform Python code by up to 160x. So ... a reimplementation of Python that can outperform cpython by over 100 times? I know literally nothing about this project, but I have to say that rings pretty false for me. Hell, even PyPy has trouble with many applications. (Plus they're cla…

I also know literally nothing about this particular project, but why not? If you support a small restricted subset of Python it's completely doable under certain conditions for specific types of programs . E.g., Numba can easily outperform Python 100-1000x in numerical applications (done it myself multiple times), simply because it jit-compiles the code by first translating it to LLVM IR.

> If you support a small restricted subset of Python

That's why I quoted their claim that the "vast majority" of Python programs run unmodified. Even PyPy barely achieves that. To really get 100x performance over Python (and even supposedly beat C) with a compiler that works on most unmodified Python code would be an extraordinary achievement.

Re: Seq – A programming language for computational genomics and bioinformatics

#10
post #6

> Seq is a Python-compatible language, and the vast majority of Python programs should work without any modifications > Seq is able to outperform Python code by up to 160x. So ... a reimplementation of Python that can outperform cpython by over 100 times? I know literally nothing about this project, but I have to say that rings pretty false for me. Hell, even PyPy has trouble with many applications. (Plus they're cla…

Probably, it can outperform generic python specifically for genomics payloads, versus python code/C code.
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