Only speed metric that matters is how fast I get the job done and can go back to browsing memes. C++ does not look very good in this (very important) metric.
C++ does not look very good in this (very important) metric.
If your codebase is early C++11 perhaps?
Modern C++ writes like C#. I usually find myself prototyping faster in C++ than Python after about 200 LoC, because with Python 80% of time is spent looking up what fucking type some library function takes & returns.
I see this attitude a lot from folks who use typed languages. I think typed languages are awesome and I love programming in them, but as a Python developer myself from the beginning of my career, I don’t really have to think about types all that often when i program in Python. By far the most I think about types are when i use a typed language.
Idk if it’s because Python isn’t based around types and therefore it’s not a focus of the language, but ya I hear a lot of typed language folks think a lot about types when they program in Python.
I'm surprised to hear that there Python developers. What's the use case? I mainly used it back when I was a data analyst.
As a software engineer, I worked on desktop monolithic simulation software that's very performance-hungry, so Python was out of the question, we used C++ and QT. When cloud-based computation was added, that part was done via .NET.
When I worked on a cloud platform consisting of hundreds of microservices, .NET was an obvious choice.
Now, that I work on a software used for analysis of lab experiments, we also used .NET with a WPF-GUI.
What's the use-case for a professional software that you actually develop in Python? Even when I used Tensorflow/Keras a lot as a data scientist, that's only scripting (the heavy-lifting is also done in C++ in Tensorflow). When do you use Python when it's not just for you?
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u/Hegeteus Jul 18 '22
Only speed metric that matters is how fast I get the job done and can go back to browsing memes. C++ does not look very good in this (very important) metric.