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I'm sure Chapel has its merits, but one of the main selling points of Mojo is the aspiration to be part of the Python ecosystem, and so far I haven't seen any o

I'm sure Chapel has its merits, but one of the main selling points of Mojo is the aspiration to be part of the Python ecosystem, and so far I haven't seen any other programming language offering a similar promise, other than Python itself coupled with DSLs or other extensions for high performance.

bradcray 3y ago
Those interested in the intersection between Python, HPC, and data science may want to take a look at Arkouda, which is a Python package for data science at massive scales (TB of memory) at interactive rates (seconds), powered by Chapel: * https://github.com/Bears-R-Us/arkouda https://github.com/Bears-R-Us/arkouda * https://twitter.com/ChapelLanguage/status/1688588977732001793 https://twitter.com/ChapelLanguage/status/168858897773200179...
behnamoh 3y ago
> to be part of the Python ecosystem I'd rather use Python if I'm in the Python ecosystem. So many attempts were made in the past to make a new language compatible with the Python ecosystem (look up hylang and coconu -- https://github.com/evhub/coconut https://github.com/evhub/coconut). But at the end of the day, I'd come back to Python because if there's one thing I've learnt in recent years it's this: minimize dependencies at all costs.
- EnergyAmy 3y ago
  I don't think those fill the same niche. They're nice-to-haves on top of Python. The promise of Mojo is that it's for when Python isn't good enough and you need to go deeper, but you want the Python ecosystem and don't want to write C.
- skdotdan 3y ago
  I believe the main Mojo use cases are scenarios in which you'd need dependencies anyway. Code that you can't write in Python due to performance concerns, so you'd need to call C/C++/Rust/CUDA/Triton/etc anyway.
adgjlsfhk1 3y ago
honestly that is the main thing that makes me pretty sure Mojo will fail. Right now, the types of things it doesn't support include keyword arguments and lists of lists. The place where python compatibility really matters is C API compatibility and they are hilariously far away from that for now.

bradcray 3y ago

Those interested in the intersection between Python, HPC, and data science may want to take a look at Arkouda, which is a Python package for data science at massive scales (TB of memory) at interactive rates (seconds), powered by Chapel: * https://github.com/Bears-R-Us/arkouda https://github.com/Bears-R-Us/arkouda * https://twitter.com/ChapelLanguage/status/1688588977732001793 https://twitter.com/ChapelLanguage/status/168858897773200179...

behnamoh 3y ago

> to be part of the Python ecosystem I'd rather use Python if I'm in the Python ecosystem. So many attempts were made in the past to make a new language compatible with the Python ecosystem (look up hylang and coconu -- https://github.com/evhub/coconut https://github.com/evhub/coconut). But at the end of the day, I'd come back to Python because if there's one thing I've learnt in recent years it's this: minimize dependencies at all costs.

EnergyAmy 3y ago
I don't think those fill the same niche. They're nice-to-haves on top of Python. The promise of Mojo is that it's for when Python isn't good enough and you need to go deeper, but you want the Python ecosystem and don't want to write C.
skdotdan 3y ago
I believe the main Mojo use cases are scenarios in which you'd need dependencies anyway. Code that you can't write in Python due to performance concerns, so you'd need to call C/C++/Rust/CUDA/Triton/etc anyway.

adgjlsfhk1 3y ago

honestly that is the main thing that makes me pretty sure Mojo will fail. Right now, the types of things it doesn't support include keyword arguments and lists of lists. The place where python compatibility really matters is C API compatibility and they are hilariously far away from that for now.