It's perfectly general: arb, market making, signal trading, ml, etc. Whatever strategy class you're thinking of, you can probably implement it on Gryphon.

Can you please explain to me how a tool written in python can be used for HFT or market making?

I’m asking because we generally used ASICS and c++ in the past, or more recently rust. Even GPUs are often difficult because they introduce milliseconds of latency.

If you want to restrict the definition of HFT to only sub-millisecond strategies you're correct. But then, all HFT is impossible in crypto, since with web request latency and rate limits, it would be very difficult to get tick speeds even in the 10s of milliseconds. It's fine if you want to call this "algo trading" instead of HFT, but I think a common understanding of the term would include Gryphon's capabilities.

In any case Gryphon uses Cython to compile itself down to C, which isn't quite as good as writing in native C but is a good chunk of the way there.

> In any case Gryphon uses Cython to compile itself down to C, which isn't quite as good as writing in native C but is a good chunk of the way there.

Would there be any advantage to asyncio with uvloop (also written in Cython (on libuv like Node) like Pandas)? https://github.com/MagicStack/uvloop

IDK how many e.g. signals routines benefit from asyncio yet.

I don't believe true crypto HFT strategies exist (i.e. sub-millisecond tick to trade). It's just not possible with websockets and http requests being the standard for data feeds and order placement on crypto exchanges.