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by named-user 1684 days ago
FastAPI is hard to contend with for anything marginally complex, without having to dig deep in its internals.

If you want performance, or to apply more rigorous (read: enterprisey) development practices, you really are better off looking elsewhere.

However, you can get a Data Science python developer to front their code behind an API with minimal ceremony.

Type safety does not exist in Python. Type hinting does not solve this problem, neither does Pydantic. These are bandaids for huge shortcomings of using the wrong tool for the job.
2 comments
gmfawcett 1684 days ago
Sure, but there's a continuum at play here. Haskell leaves some correctness on the table, right? -- you should be using Idris 2; or better yet, proving your API in Coq and extracting the code. From some perspectives, Haskell is the "worse" in "worse is better".

Personally I find python-is-wrong arguments to be a bit naive. "It's a crappy language that's only good enough to build prototypes..." -- like YouTube, for example? :) Ultimately, smart developers are smart, and can get work done with whatever tools they have at hand.

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fiedzia 1684 days ago
Take computer away from them and see how far they'll go.

Tools matter. However the community and ecosystem behind Python makes it extremely hard to beat at many games.

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gmfawcett 1684 days ago
LOL, I agree that YouTube would be hard to build if you only had a hammer and chisel. :P
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mrtranscendence 1684 days ago
Just continually saying Python is the wrong tool for the job doesn't cut it. I've gotten a lot of mileage out of type hints in Python and have caught my share of bugs statically, so I disagree with your contention that it's merely a "bandaid for huge shortcomings". It's a helpful tool that serves a purpose.

You could pick at every tool, every language. What's better than Python at (since you brought it up) data science? Julia? That's hardly any more type safe, if that's an issue for you. Haskell? Good luck getting non-CS types to buy in to the restrictions, and good luck porting everything you need. R? Slower than Python, even! I mean, I dunno, if you have something in mind that's better in every way than Python then I'd love to hear it.

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Mikeb85 1684 days ago
R is way better than Python for most (all?) data science things. It's better at data munging, has more packages, it's array based so way more terse while being easy to reason about, has super easy C++ FFI, etc...

And no environment really beats RStudio.

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mrtranscendence 1681 days ago
I dispute at least some of that. R has more statistical packages, perhaps, but can't compete with Python in terms of sheer array of packages and developer mindshare in general. This is no different for data science, where major tools are either Python-only or are accessed in R only through Python (like Tensorflow).

R is also hardly more terse in my experience, though perhaps that depends on style; I'm a tidyverse fan but it's not particularly concise.

Finally ... RStudio. It's just okay. If you're willing to use a language-specific editor that may not get keybindings right (I hope you're not an emacs user), it works fine. I like the RMarkdown integration. I don't use it, though, and I don't feel like I'm missing that much.

BTW, you don't mention what actually does make R better than Python: lazy evaluation allowing something close to syntactical macros. You'll never get a magrittr or a dplyr in Python.

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