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Most programmers don't actually need to know about that stuff, either. And most programmers who do need to know about that stuff, don't know about it.
Solving race conditions is QA's problem right? ;)
Garbages keep growing, too. It's really hard to trace a Python bug based on codebase, due to its stricly bugly indentation sensitive for space/tabs. I rather work on a JS codebase than a python codebase. But i consider Python coders genius, because they can go deep into rabbit hole really well.
That may only prove that you are not proficient in either.
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Realistically something that takes 1 second in C++ will take 10 seconds (if you write efficient python and lean heavily on fast libraries) to 10 minutes in python. But the rest of your point stands
Damn! Is the rule of thumb really a 10x performance hit between Python/C++? I don’t doubt you’re correct, I’m just thinking of all the unnecessary cycles I put my poor CPU through.
And OCaml (which offers a productivity comparable to Python) is sensibly slower than Rust or C++.
Comparing Python to Java 8 and saying it’s more readable isn’t showing much. And it’s not very portable the second dependencies with native code (which is common since pure Python is too inefficient for many tasks) are used. I think Python is popular for two reasons: - it’s believed to be beginner friendly compared to other languages. I’m not really sure why - maybe the whitespace? - it has an enormous set of librari…
I started in Python, as a Biologist (hooray for Jupyter-lab, coding so visually, in small steps, with output just there is so great when starting to learn Python). I ventured into other languages every now and then. For example I tried to make an Android app in Kotlin that gets info from some API. I expect something like this but with more brackets everywhere: import request data = request.get(https://some.api/get_so…
Python keeps growing in number of users because it’s easy to get started, has libraries to load basically any data, and to perform any task. It’s frequently the second best language but it’s the second best language for anything. By the time a python programmer has «graduated» to learning a second language, exponential growth has created a bunch of new python programmers, most of which don’t consider themselves progr…
Your comment is super interesting because it suggests Python has evolved in a direction opposite to the Python Paradox - http://www.paulgraham.com/pypar.html Whereas before you could get smarter programmers using Python, now because of the exponential growth of Python, the median Python programmer is likely someone with little or no software engineering or computer architecture background who is basically just gluing…
Comparing Python to Java 8 and saying it’s more readable isn’t showing much. And it’s not very portable the second dependencies with native code (which is common since pure Python is too inefficient for many tasks) are used. I think Python is popular for two reasons: - it’s believed to be beginner friendly compared to other languages. I’m not really sure why - maybe the whitespace? - it has an enormous set of librari…
> - it’s believed to be beginner friendly compared to other languages. I’m not really sure why - maybe the whitespace? Good bait. I'll take it. - dynamic, weak (really "duck") typing, meaning users don't have to worry about conversion between things. Want to print() a dictionary of whatever? Sure! - no semicolons to terminate a statement. End of line, that's it - rich standard library, so you can actually get going o…
Ability to do structural printing of arbitrary structures is not restricted to dynamically typed languages.
However, I actually think a good beginner language could be dynamic or static.
Earlier quoted context omitted.
Realistically something that takes 1 second in C++ will take 10 seconds (if you write efficient python and lean heavily on fast libraries) to 10 minutes in python. But the rest of your point stands
And how much code is generally written that actually is compute heavy? All the code I've ever written in my job is putting and retrieving data in databases and doing some basic calculations or decisions based on it.
But sometimes, you do end up writing that compute heavy piece of code. At that stage, you have to learn how to write your own native library :)
Speaking of which, I've written some Python modules in Rust using PyO3, its' a very agreeable experience.
One thing I’d add to this conversation, though I’m certain it’s already been stated: As many have mentioned, there is a large subset of the user base that uses Python for applied purposes in unrelated fields that couldn’t care less about more granular aspects of optimization. I work as a research assistant for international finance faculty and I would say that compared to the average Hackernews reader, I’m technologi…
You’ll find everyone from philosophy PhDs to Biologists to Journalists who use pandas because its so easy to learn it and work with it. It’s amazing how you can become productive in python/pandas without any experience or even basic understanding of programming because of how accessible jupyter, colab and blogs/docs on pandas are.
The other thing people don’t talk about is that a lot of these organizations can hire a CS student part time or a full time software engineer/data engineer/data scientist who can optimize their scripts once they are written. Pretty much any software engineer can read and debug python code without needing to learn python. So for example, I know some engineers working in genomics who have turned biologist-written scripts that take several days to run in python into scripts that take hours or minutes to run by doing basic optimizations like removing quadratic algorithms from the script or applying pyspark or dask to add parallelism.
The fact that python can be used as a bridge between technical and non-technical people is amazing and I think it has provided a better bridge between these groups than SQL was ever able to provide.
Python keeps growing in number of users because it’s easy to get started, has libraries to load basically any data, and to perform any task. It’s frequently the second best language but it’s the second best language for anything. By the time a python programmer has «graduated» to learning a second language, exponential growth has created a bunch of new python programmers, most of which don’t consider themselves progr…
There are also programmers who are tired of chasing pointers and simply want to get stuff done. E.g. people who once wrote "robust" code in Rust but were "outcompeted" left and right by coworkers who churn out shiny new things at 10x the speed.
That's when rewriting the hot path in Go or Rust or Java or C or C++, can pay off and make those skills very valuable to the company. Making contributions to databases, operating systems, queueing systems, interpreters, Kubernetes etc. also fall into that category.
But yeah if you are churning out a MVP for a new business, yeah starting with Python or Ruby or Javascript is a better bet.
(Erlang/Elixir is also an interesting point in the design space, as it's very high level and concise, but also scales better than anything else, although not especially efficient for code executing serially. And Julia offers the concision of Python with much higher performance for numerical computing.)