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A look at the Mojo language for bioinformatics (viralinstruction.com)
22 points by jakobnissen 7 months ago | hide | past | favorite | 5 comments



>However, in my opinion, this lack of validation (really, lack of parsing in any meaningful sense) means that the performance between this parser and Needletail is incomparable. So what exactly does it demonstrate? You get to claim your implementation is faster than someone else if you do the same task in less time, but not if you skip half the job.

Yeah, this makes the original post just incredibly misleading. Sure, meaningful benchmarks are hard, but before you go writing "woah, look how much faster we are!", a bit more due dilligence should be required.


> I think there is only one real conclusion here:

> JULIA IS FASTER THAN MOJO!!!!111

<3


Julia is an example of a dynamic language that is fast. I would like to see Mojo and Julia compared for interoperability with Python.


Calling julia code from python or python code from julia is relatively straightforward. I haven't spent much time doing the former, but love the ergonomics of the later with PythonCall.jl and CondaPkg.jl to manage python dependencies.

The syntax is just totally different though.


I would hesitate to say Julia has better support for Python interoperability, since I haven’t tried out Mojo’s support, but this interoperability is a goal of Mojo.




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