It's a big jump from C++ to Python. If you want a midway, use Go.
Was a really big part of Kafka and Spark ecosystems until they supported Python well enough that a lot of people just stuck with that instead of teaching their devs to write Scala.
Kotlin feels like it has a much better plan and it seems like so far it won't suffer the same death.
[f(x) for x in xs]
Java has immutable bindings with the final keyword.
Java variables are lexically scoped, which discourages mutation of globals.
I've been writing C# for over a decade, and 99% of it has deployed in Docker containers to Linux VM's (via k8s etc).
This post seems nonsensical.
Edit: nvm, see jibal’s comment below
Game engines: Unreal - C++, Unity - C#, Godot - GDScript (Python) + second-class C# support
Frameworks: Raylib - C, Bevy - Rust, Love2D - Lua, Monogame - C#, Phaser - JS, PyGame - Python
We don't know for sure what AAA companies rolling their own engines use, but the industry standard would be written in C++, exposing C++ for programmers and Lua for non-programmers/modders.
C# is basically the midpoint between Lua and C++ which is why it’s so popular with game devs imo
I also don't agree with the fact that ruby is just like PHP.. for web backends.
Haskell → dunno, but it’s pretty cool
Erlang → dunno again, maybe some low-level stuff for Elixir?
F# → business apps for MS when you get sick from C#
Crystal → web, I guess?
Ruby is good for web, but it’s also useful when metaprogramming tricks work for you in your particular domain. Same with Python (it’s also insanely good for web!).
(and that being said, you can also use Erlang libraries in Elixir, so there’s a path for incremental adoption)
Or at least that was the case some year ago. Haven't checked lately. I know there are ongoing efforts towards convergence.
Neither option allows you to use Phoenix without writing Elixir code, though. But since you’re integrating an Elixir lib, writing at least some glue code doesn’t seem like a big deal?
(I’ve got to say that I’m not proficient at all neither in Erlang nor in Elixir – I’ve played around with both, but nothing serious.)
You might not be worried about these and that's okay but it's a real measurable factor by which you can evaluate languages.
CXX[0] is fine. Personally, I just always use a C ABI to communicate between the two. I've had to do it for every other language anyway. Languages that have native C++ interop are significantly more rare than ones that don't. Most languages have some way of talking to C, though.
[0]: https://cxx.rs/
Would you pick Brainfuck over Java for anything (real)?
along with Turing Tape machine coding, corewars, that one from Knuth ..
outside of that domain of interest, not so much.
But that is one domain of interest.
It's also true that real world industrial scale dam control isn't a killer application domain for Brainf*ck .. but FGS, have you seen many SCADA implementations?
Concrete examples: Dart with Flutter, Elixir with Phoenix,
Arguable ones: JavaScript and browsers, Go and Kubernetes
I kind of disagree with the "killer app" concept because most languages can work in a lot of domains, but there are more examples if you're willing to think about it
I have yet to see any software that rivals dplyr, data.table, and ggplot2 in the balance of power and ease of use. It also has all the auxiliary packages you need to fetch your data (DBI, httr, rvest), model it if necessary (parsnip, caret) and visualise it (ggplot2, plotly, shiny)
I know python is more popular here but I would choose R in a heartbeat 19 times out of 20
1. It's easier to get up and running as RStudio is much more 'batteries included' than other popular IDEs, it's harder to get into the case of multiple different python versions, and you install packages through the R interpreter rather than via pip at the command line
2. I would say R data analysis packages are easier to learn than the python equivalents. Because the dataframe is a native structure in R there has been a lot more packages that have tried alternative syntax approaches to try and find the 'optimal' one. Python has really only had pandas, polars, and pyspark (all of which have implemented their own data structures and therefore have focused more on performance than syntax)
3. This doesn't hold if you're studying a language to be a general purpose programmer. Then python is much better. Anything to avoid the hell of the R standard lib. But if you need to do a bit of coding to analyse data and you've never done any before, my vote would be for R.
However, these are thoughts from my own personal anecdotes rather than any pedagogical theory
Folks, it’s 2025. This stereotype should have died at least five years ago. C#+.NET is open source and cross-platform since 2016 or so.
While it is technically possible to use C# on Linux and MacOS, it doesn't seem to have a significant mind share.
Python → Scientific computing and machine learning.
PHP → Web backend.
Not sure how to figure it out. Google trends maybe?
https://trends.google.com/trends/explore?date=all&q=python%2...
e.g.
* Ruby had Rails
* PHP had mod_php and a strong Apache-oriented community
* Java had strong support from Sun
* Python for scientific computing because of numpy, etc.
If numpy and friends were made for Ruby instead, I think we’d be in a different world.
Java → Business applications
Kotlin → Android
throwaway519•1mo ago