Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

A look at the Mojo language for bioinformatics

viralinstruction.com

Post reply on HN
Print view View original

81–90 of 124 posts

Re: A look at the Mojo language for bioinformatics

#81

Post by coderedart »

breather wrote: post #61
latenightcoding wrote: post #57

Earlier quoted context omitted.

I can't take this language or company serious after reading stuff like: "Mojo may be the biggest programming language advance in decades" https://www.fast.ai/posts/2023-05-03-mojo-launch.html

Hard to remember the last language that felt so obviously sold by something other than an actual community. Even Swift tried its best to exist outside of xcode and mac/i os EDIT: perhaps I'm being too harsh—this was literally just announced. I'm just taken aback by the blatant marketing as everyone else is.

There was v lang in recent memory which made grand claims.

Re: A look at the Mojo language for bioinformatics

#82

Post by aldanor »

WeatherBrier wrote: post #29

The language is far from stable, but I have had a LOT of fun writing Mojo code. I was surprised by that! The only promising new languages for low-level numerical coding that can dislodge C/C++/Fortran somewhat, in my opinion, have been Julia/Rust. I feel like I can update that last list to be Julia/Rust/Mojo now. But, for my work, C++/Fortran reign supreme. I really wish Julia had easy AOT compilation and no GC, that…

Well, there's some big DS projects written in rust that are now very widely used in Python world - e.g., polars.

Re: A look at the Mojo language for bioinformatics

#83

Post by dr_kiszonka »

Folks using multiple languages, what is your workflow?

I do most DS/ML work in Python but move to R for stats, and publication-ready plots and tables (gt is really great). I often switch between them frequently, which is a hassle in the EDA and prototyping stages, especially when using notebooks. I enjoy Quarto in RStudio, but the VS Code version is not that great.

How do you make it work?

Also, after so many years using Python and R, I would love to learn a new language, even if only for just a couple of use cases. I considered Elixir for parallel processing and because it has a nice syntax, but ultimately decided against it because it can be a little slow and isn't used much in my area (sadly!). Rust seems to require too much time to get decent at it. Any recommendations? (Prolog?)

Re: A look at the Mojo language for bioinformatics

#84

Post by mianos »

latenightcoding wrote: post #57
jdiaz97 wrote: post #30

Great post. I think Mojo's claims like the speedup over Rust are a problem, like the 65000x speedup over Python. How can we differentiate between good new tech and Silicon Valley shenanigans when they use claims like that? They do nice titles and slogans but are shady in substance

I can't take this language or company serious after reading stuff like: "Mojo may be the biggest programming language advance in decades" https://www.fast.ai/posts/2023-05-03-mojo-launch.html

My answer to the deleted comment and to this.

It is a bunch of incremental improvements to the Python like language environment.

That's no big programming language advance to me. A biggie would be to Haskel or even Rust.

That's not to say it won't be wildly more successful as it gives a lot of what people want in a number of areas all in one go.

I'd jump on board except for the vibe around the current licensing. Maybe that will change and I'll be one of those Rust people who comment 'but Rust' on every C and C++ article, except I'll be saying "but Mojo" :)

Re: A look at the Mojo language for bioinformatics

#85

Post by carbocation »

dr_kiszonka wrote: post #83

Folks using multiple languages, what is your workflow? I do most DS/ML work in Python but move to R for stats, and publication-ready plots and tables (gt is really great). I often switch between them frequently, which is a hassle in the EDA and prototyping stages, especially when using notebooks. I enjoy Quarto in RStudio, but the VS Code version is not that great. How do you make it work? Also, after so many years u…

My workflow is similar to yours: python for deep learning and surface reconstruction. R for stats and plots.

I use go extensively for data preprocessing. Sounds weird but it works well for highly repetitive conversion tasks like DICOM parsing, converting EKGs to numpy, etc.

Re: A look at the Mojo language for bioinformatics

#86

Post by hayley-patton »

celrod wrote: post #48
adgjlsfhk1 wrote: post #38

Earlier quoted context omitted.

> I really wish Julia had easy AOT compilation and no GC, that would be perfect I pretty strongly disagree with the no gc part of this. A well written GC has the same throughout (or higher) than reference counting for most applications, and the Rust approach is very cool, but a significant usability cliff for users that are domain first, CS second. A GC is a pretty good compromise for 99% of users since it is a minor…

Too bad Julia doesn't have this theoretical "well written GC". I do not like GCs, so I agree with OP's sentiment. Why solve such a hard problem when you don't have to? I don't find ownership models that difficult. It's things one should be thinking of anyway. I think this provides a good example of where stricter checking/an ownership model like Rust has makes it easier than languages that do not have it (in this cas…

There's work on porting MMTk to Julia, which will provide some well written GCs: https://github.com/mmtk/mmtk-julia

Re: A look at the Mojo language for bioinformatics

#87

Post by a_bonobo »

eyegor wrote: post #75
a_bonobo wrote: post #73

Earlier quoted context omitted.

Yeah that's how it ended up for me: large datasets get churned through for speed in Python, but I then usually switch over to R with the summary data because there's just way more biology-specific ecosystem in R than in Python. R/Bioconductor has packages for human genome-specific analyses so it's easy to download gene positions etc., there are packages for read simulation, amplicon sequence variant detection, gene d…

To your last point, have you tried plotnine? It's meant to be ggplot2 for python. https://github.com/has2k1/plotnine

I've looked at it yes!! but there's heaps of ggplot-based libraries that I also like to use; things like cowplot, ggsignif, ggtree etc. It would be a cat-and-mouse game for plotnine to keep up with the ggplot-based ecosystem!

Re: A look at the Mojo language for bioinformatics

#88

Post by mcqueenjordan »

SushiHippie wrote: post #55
mcqueenjordan wrote: post #9

Another point of clarification that is of great importance to the results, and is a common Rust newcomer error: The benchmarks for the Rust implementation (in the original post that got all the traction) were run with a /debug/ build of rust, i.e. not an optimized binary compiled with --release. So it was comparing something that a) didn't do meaningful parsing against b) the full parsing rust implementation in a non…

Am I missing something? In the git repository [0] it says: > needletail_benchmark folder was compiled using the command cargo build --release and ran using the following command ./target/release/ . Or are you talking about something else here? [0] https://github.com/MoSafi2/MojoFastTrim

It was later edited, after it had basically made the rounds.

Re: A look at the Mojo language for bioinformatics

#89

Post by chaxor »

gandalfgeek wrote: post #76

> It does grate me then, when someone else manages to raise 100M dollars on the premise of reinventing the wheel to solve the exact same problem, but from a worse starting point because they start from zero and they want to retain Python compatibility. Think of what money like that could do to Julia! Python is a juggernaut with total control of the ML space and is a huge part (even if less dominant) in modern scienti…

I was interested in trying our mojo. Then I looked at it booked out quick.

No one will use a language that isn't free and open source.

If mojo was free and open source (wasn't a company), and didn't just give out binaries with a 'trust me bro' stamp if approval, then I would have worked with it. But it's not, so I will never use it.

Re: A look at the Mojo language for bioinformatics

#90

Post by robinsonrc »

chromatin wrote: post #66
fwip wrote: post #26

For what it's worth, I couldn't reproduce the benchmarks cited in the post, which claimed a 50% speedup over Rust on M1. The rust implementation was consistently about two to three times as fast as Mojo with the provided test scripts and datasets. It's possible I was compiling the Mojo program suboptimally, though. hyperfine -N --warmup 5 test/test_fastq_record 'needletail_test/target/release/rust_parser data/fastq_t…

It was later noted on Twitter/X by someone that the rust version was not compiled with `--release`

That’s a fairly big omission for such an attention grabbing performance comparison
Post reply on HN