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This seems to be an increasingly growing niche where D is gaining popularity. I see more and more people turning to D where they would normally use python or R

by Neku42 7y ago

This seems to be an increasingly growing niche where D is gaining popularity. I see more and more people turning to D where they would normally use python or R for adhoc data crunching

bachmeier 7y ago
It doesn't even need to be an alternative to Python or R, since it's really easy to interoperate with both languages. This is in addition to tools like eBay's tsv-utils. http://code.dlang.org/packages/pyd http://code.dlang.org/packages/pyd https://embedr.netlify.com/ https://embedr.netlify.com/ http://code.dlang.org/packages/autowrap http://code.dlang.org/packages/autowrap https://github.com/eBay/tsv-utils https://github.com/eBay/tsv-utils
mhh__ 7y ago
I try to use D for that (difficult because the libraries are fairly low level, I would say sparse but calling into C and C++ is pretty trivial) because, for the same effort I put into bullying python to do what I want, I can write type safe (generic) code that is both actually readable and ready to be reused if needs be. And sometimes orders of magnitude faster. That and ranges (D/Andrei's preferred model for iteration) are excellent - in my view at least.
z3c0 7y ago
As one of those people, I can say the reason is for the C-level processing power with the approachable syntactic sugar. Out of all the languages gaining popularity for their ability to run natively (Rust, Go, D, etc), I've felt that D is the most natural continuation of C/C++, at least syntactically. I haven't touched the language in about a year, but I'm personally rooting for it.
- WalterBright 7y ago
  And with D as Better C, (-betterC switch), it's easy to convert your C project to D, one file at a time, and not require the D runtime library (only the standard C library is required). The original impetus for this was so I could incrementally convert the D compiler backend itself from "C with Classes" to D.
mochomocha 7y ago
I also use D for data & ML at work (Netflix) when standard python workflow doesn't cut it anymore. There's just so far you can go with the typical "call a popular python lib interfacing with a C++ backend" paradigm before hitting a brick wall.
- Demiurge 7y ago
  How far is that? What about Cython?
chromatin 7y ago
We are using D for high performance computational biology -- I brought a Go dev and a python dev both onboard with minimal learning curve. Even the powerful template metaprogramming seemed really easy for the team to pick up. I believe this is because it really has a nice design (compared with, say, C++, which I would never, ever use in general bioinformatics unless team had specific past expertise)
jondegenhardt 7y ago
eBay's tsv-utils author here. A fair bit of performance benchmarking was done on the tools with the goal of exploring this type of use (data crunching). D did really well (tsv-utils are fast!). There's more info on the benchmarks page in the github repo. Perhaps the best summary is the slides from a talk I did at 2018 DConf. Links: - tsv-utils repo: https://github.com/eBay/tsv-utils https://github.com/eBay/tsv-utils - Performance studies: https://github.com/eBay/tsv-utils/blob/master/docs/Performance.md https://github.com/eBay/tsv-utils/blob/master/docs/Performan... - Talk slides: https://github.com/eBay/tsv-utils/blob/master/docs/dconf2018.pdf https://github.com/eBay/tsv-utils/blob/master/docs/dconf2018...

by Neku42 7y ago

This seems to be an increasingly growing niche where D is gaining popularity. I see more and more people turning to D where they would normally use python or R for adhoc data crunching

bachmeier 7y ago

It doesn't even need to be an alternative to Python or R, since it's really easy to interoperate with both languages. This is in addition to tools like eBay's tsv-utils. http://code.dlang.org/packages/pyd http://code.dlang.org/packages/pyd https://embedr.netlify.com/ https://embedr.netlify.com/ http://code.dlang.org/packages/autowrap http://code.dlang.org/packages/autowrap https://github.com/eBay/tsv-utils https://github.com/eBay/tsv-utils

mhh__ 7y ago

I try to use D for that (difficult because the libraries are fairly low level, I would say sparse but calling into C and C++ is pretty trivial) because, for the same effort I put into bullying python to do what I want, I can write type safe (generic) code that is both actually readable and ready to be reused if needs be. And sometimes orders of magnitude faster. That and ranges (D/Andrei's preferred model for iteration) are excellent - in my view at least.

z3c0 7y ago

As one of those people, I can say the reason is for the C-level processing power with the approachable syntactic sugar. Out of all the languages gaining popularity for their ability to run natively (Rust, Go, D, etc), I've felt that D is the most natural continuation of C/C++, at least syntactically. I haven't touched the language in about a year, but I'm personally rooting for it.

WalterBright 7y ago
And with D as Better C, (-betterC switch), it's easy to convert your C project to D, one file at a time, and not require the D runtime library (only the standard C library is required). The original impetus for this was so I could incrementally convert the D compiler backend itself from "C with Classes" to D.

mochomocha 7y ago

I also use D for data & ML at work (Netflix) when standard python workflow doesn't cut it anymore. There's just so far you can go with the typical "call a popular python lib interfacing with a C++ backend" paradigm before hitting a brick wall.

Demiurge 7y ago
How far is that? What about Cython?

chromatin 7y ago

We are using D for high performance computational biology -- I brought a Go dev and a python dev both onboard with minimal learning curve. Even the powerful template metaprogramming seemed really easy for the team to pick up. I believe this is because it really has a nice design (compared with, say, C++, which I would never, ever use in general bioinformatics unless team had specific past expertise)

jondegenhardt 7y ago

eBay's tsv-utils author here. A fair bit of performance benchmarking was done on the tools with the goal of exploring this type of use (data crunching). D did really well (tsv-utils are fast!). There's more info on the benchmarks page in the github repo. Perhaps the best summary is the slides from a talk I did at 2018 DConf. Links: - tsv-utils repo: https://github.com/eBay/tsv-utils https://github.com/eBay/tsv-utils - Performance studies: https://github.com/eBay/tsv-utils/blob/master/docs/Performance.md https://github.com/eBay/tsv-utils/blob/master/docs/Performan... - Talk slides: https://github.com/eBay/tsv-utils/blob/master/docs/dconf2018.pdf https://github.com/eBay/tsv-utils/blob/master/docs/dconf2018...