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Comment by z9znz | Hacker News Reader

Use any language you like to build a proof of concept.

But one you need to take that POC and build a real product which needs to be supported, extended, and maintained, then you must choose tools which fit that long term need.

Many of use first experienced school in kindergarten. Kindergarten was an important step in our education and socialization. But we didn't refuse to move on to the next level, no matter how much fun it was or how nice our teachers were. Maybe some people felt unsure about leaving their comfort zone, but there's no progress without risk and effort.

Is a university student elitist because they know something a kindergarten kid doesn't? Should they stop trying to promote continued growth through the educational levels?

If you were to use production Python on any decent sized project, and you had also used Ruby (just one example... some other languages can be even more succinct), then you would hate Python.

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The issue with a lot of the gripes with Python is that there's no other language that combines mature linear algebra libraries, scientific computing libraries, and industry standard computer vision libraries with easy to use basic tools like csv reading, dataframes, json parsing, etc., while also providing easy syntax and fast iteration time. I work in C++ and Python, and things that are completely trivial in Python have a lead time measured in days, if not weeks when moving to C++. This is before even getting into the weeds of writing bug-free C++ code; you need to be familiar with the nitty-gritty details of the library you're working with, because things you might take for granted may not work the way you think.

Sure, maybe we should be rewriting POC code in a language that's more fit-for-purpose if we're talking about a large project, but for that you need mature libraries, or a team with some fairly serious chops (i.e. decent math background, senior coders, expensive to hire, and hard to replace). There's a lot to be said for a language that makes it easy to be productive on technically demanding problems, while also making it easy to find new talent. As someone who's written code relying on linear algebra and CV in Rust and C#, and I'd honestly pick Python every time for those types of jobs. It's not perfect, but that's not the benchmark.

I would not advocate for rewriting everything in non-Python. It is what it is, and it excels at tasks related to the important libraries discussed in this topic.

Just as Python wraps the libraries which do the heavy lifting in C, I would try to keep the Python wrapper as minimal as possible and stick some interface in front of that. Instead what happens often is people choose to either build more and more around this important stuff, staying with Python, or they say, "We're better off just supporting one language in-house, and Python is required already; so we are a Python shop."

It truly does depend on what you’re building, in which organization and with whom you’re doing it.

If you’re building a production system with a small, stable team, and Python is a good fit for the work, then there is no reason not to use it.

If you’re doing programming in the large with a large and constantly changing team, then you’d be wise to pick a statically typed language that many people know (basically C# or Java)

Your education example is off base. Python is not a more basic form of programming that one passes through on the way to enlightenment. It’s hand screwdrivers vs hammer drills or diesel pickups vs electric sedans. Different tools for different contexts.

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