Julia 1.9

When I see people describing viable alternatives to python and or C I personally look at C++ and Rust. Julia's GC is good for most academic embarrassingly parallel number crunching things, but is rough for large scale applications. I've only been able to use Julia in a vacuum for research. For product development, every effort I've seen has eroded insanely fast due to things other languages control much more easily. Those languages can often also do the math fast enough too, especially when the cost of failed experiments is accounted for. All those wait three hours to find out your first gradient descent iteration had a type error that propagated to 1000 compute nodes($) moments are gone. It just can't happen in other paradigms, and in some paradigms it's far less likely to happen and when it does the cost is minor because the cost of compilation was already amortized.

I'm not typing these things out for FUD to slow Julia developers role or something. Actually I hope they listen and actually work to fix things that matter. I invested a lot of time and effort into the language. Currently I'm looking at it as a complete waste with mostly negative side effects to my career and where I could have invested my time. Trying to do one of two things, encourage change, get people on the fence about trying it to wait until it's actually ready.

We use zeroMQ to move data around so to get it into a python script is very easy for us. We "were" going to create a dash/plotly app to consume the data stream and create a trading augmentation tool as we find dash a pleasure to work with. We also find that it's very well supported using videos so not even we ( non web developers) can mess it up. We adhere to the Tufte approach to graphical representation of complex data sets and python allows us to take a minimalist approach to doing that.

We are also discussing the implementation of async components in a python specific hosting company that seems to address the same market as GENIE. That would give us the GUI approach should we chose to use it. We have experienced some problems with streaming data into Stipple but I would expect that they will provide a MWE that we can modify. I have high hopes for the GENIE team, they seem like excellent people.

All that said we are progressing out Carbon discussions with various people. In Chicago we are very lucky that we have a deep pool of people skilled at kernel latency avoidance, this helps us consider what we can expect from Carbon and if there are any advantages to what we want to achieve.

I hope this answers your question.