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Cake day: June 18th, 2023

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  • The whitespace doesn’t bother me at all, but holy hell! Any time I’m trying to understand a Python program/library that’s anything above a couple thousand lines of code, I instantly feel a burning hate for dynamic typing.

    I love Python for scripting- in large part because of dynamic typing. IMO it’s just not a language made for building large infrastructures.



  • For someone starting out, I would say that a major advantage of Python over any compiled language is that you can just create a file and start writing/running code. With C++ (which I’m also a heavy user of) you need to get over the hurdle of setting up a build system, which is simple enough when you know it, but can quickly be a high bar for an absolute beginner. That’s before you start looking at things like including/linking other libraries, which in Python is done with a simple import, but where you have to set up your build system properly to get things working in C++.

    Honestly, I’m still kind of confused that the beginner course at my old university still insists on giving out a pre-written makefile and vscode config files for everyone instead of spending the first week just showing people how to actually write and compile hello world using cmake. I remember my major hurdle when leaving that course was that I knew how to write basic C++, I just had no idea how to compile and link it when I could no longer use the makefile that we were explicitly told to never touch…



  • Yes, it’s a field. Specifically, a field containing human-readable information about what is going on in adjacent fields, much like a comment. I see no issue with putting such information in a json file.

    As for “you don’t comment by putting information in variables”: In Python, your objects have the __doc__ attribute, which is specifically used for this purpose.


  • My test suite takes quite a bit of time, not because the code base is huge, but because it consists of a variety of mathematical models that should work under a range of conditions.

    This makes it very quick to write a test that’s basically “check that every pair of models gives the same output for the same conditions” or “check that re-ordering the inputs in a certain way does not change the output”.

    If you have 10 models, with three inputs that can be ordered 6 ways, you now suddenly have 60 tests that take maybe 2-3 sec each.

    Scaling up: It becomes very easy to write automated testing for a lot of stuff, so even if each individual test is relatively quick, they suddenly take 10-15 min to run total.

    The test suite now is ≈2000 unit/integration tests, and I have experienced uncovering an obscure bug because a single one of them failed.


  • This is a very “yes but still no” thing in my experience. Typically, I find that if I write “naive” C++ code, where I make no effort to optimise anything, I’ll outperform python code that I’ve spent time optimising by a factor of 10-30 (given that the code is reasonably complex, this obviously isn’t true for a simple matrix-multiplication where you can use numpy). If I spend some time on optimisation, I’ll typically be outperforming python by a factor of 50+.

    In the end, I’ve found it’s mostly about what kind of data structures you’re working with, and how you’re passing them around. If you’re primarily working with arrays of some sort and doing simple math with them, using some numpy and scipy magic can get you speeds that will beat naive C++ code. On the other hand, when you have custom data structures that you want to avoid unnecessarily copying, just rewriting the exact same code in C++ and passing things by reference can give you massive speedups.

    When I choose C++ over python, it’s not only because of speed. It’s also because I want a more explicitly typed language (which is easier to maintain), overloaded functions, and to actually know the memory layout of what I’m working with to some degree.




  • thebestaquaman@lemmy.worldtoMemes@lemmy.mlPiracy
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    6 months ago

    A professor at my university tried that, but the students quite quickly made a huge fuss, got the principals office involved, and the universities lawyers informed said professor that what she was doing was illegal, and that she should stop before she got any more trouble. She stopped.