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by sterlind
695 days ago
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it sounds like the ideal solution would be something functional (so you have a computation graph), pure (so you can cache results) and lazy (so order of expressions doesn't matter.) why not Haskell? or even a pure/lazy subset/variant of Julia, if you want to ditch the baggage of Haskell's type bondage? you could ditch explicit cells entirely, and implement your "scope" by selecting a (sub)expression and spying on the inputs/outputs. |
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I jest a bit, but there's a very rich ecosystem of really useful data analysis libraries with Python that do somewhat exist in other ecosystems (R, Julia, etc) but aren't nearly as... I would use the word polish, but a lot of the Python libraries have sharp edges as well. Well trodden might be a better word. My experience with doing heavy data analysis with Python and Julia is that both of them are often going to require some Googling to understand a weird pattern to accomplish something effectively but there's a much higher probability that you're going to find the answer quickly with Python.
I also don't really want to reinvent the universe on the first go.
It has occurred to me that it might be possible to do this in a style similar to org-mode though where it actually doesn't care what the underlying language is and you could just weave a bunch of languages together. Rust code interfacing with some hardware, C++ doing the Kalman filter, Python (via geopandas) doing geospatial computation, and R (via ggplot2) rendering the output. There's a data marshalling issue there of course, which I've also not spent too many cycles thinking about yet :)
Edit: I did copy and paste your comment into my notebook for chewing on while I'm travelling this weekend. Thanks for riffing with me!