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.
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:
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). 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:
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.
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.
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.
