Lazarus is the FOSS counterpart to Delphi's IDE, based on Free Pascal
I haven't encountered too much difficulty with IPython that I haven't with some other REPL. Also Jupyter Notebooks are there too.
I think you'd really like nand2tetris. It's a great idea though I think the pedagogy is a bit rushed. It can give you good ideas at the very least.
personally i just use cppreference and watch cppcon/cpponsea talks
std::string_view instead of std::string const& and std::span instead of std::vector for non-owning parametersstd::vectors will implicitly cast into std::spans
That looks really interesting, it uses the same method the game "Turing Complete" uses which is a very powerful method but this course goes much further then just a simple machine that runs assembly. This one even teaches you to build an operating system which I think is really cool. I should spend my time on this.
This is a problem you will inevitably run into when you have to use anything outside of the stdlib in any language. When I'm reading docs, I'm never asking myself "what's the most idomatic way to do this?" or "how can I do this in a way where fags on stackoverflow won't berate and belittle me?". Instead, I'm asking myself what tools I need for the job, not necessarily what the best one is. You develop a feel for whether the function you're writing is held together by duct tape and prayers. You'll find hundreds of ways to achieve the same result, and you'll quickly figure out which ones are the least painful and slow to work with for a given task.
Why "PERL" in all caps? My understanding is that "Perl" is the language (and
perl is the executable).
I prefer the backronym: Practical Extraction and Report Language.
Matlab is an 80s thing that embedded itself into academia and just kind of coasts along off inertia, especially when some niche library is written only for Matlab. If you have the choice to use something like Python with Numpy, there's no reason not to.
It feels like a strange transitional fossil for roughly late 80s to 90s, an era after people (university students) largely stopped doing Fortran and Pascal and before widespread adoption of Python. My STEMcel experience with it mostly involved occasionally being being paid to translate old MATLAB code to Python (lol), but maybe the situation is different in the more engineering lands within STEM where it seems more prevalent. Good riddance I say, total proprietoid death
What exactly are you trying to achieve? If you want to prevent allocations or GC scavenging during a certain section, object pools might help, but generally, fighting the GC is asking for trouble.
Also very curious what exactly you're trying to achieve, but would venture that you just manually manage your memory in C and call it with JNI.
From my very limited exposure and hearsay, it's two-fold. First, social momentum. There's a bunch of Matlab stuff already out there and pirating it is very easy. Second, it's a good base for people who aren't necessarily programmers and specialize in theoretical concepts/prototypes. Once they get a working MVP, the code gets translated to C++ by the tool that's available together with Matlab and then actual hardcore programmers optimize that into the real deal. At least that's how a professor explained it to me some years ago.
I almost wonder if package management being ass in languages like C++ is a blessing in disguise
it's almost like if every dependency is mildly painful, you won't want to add 200 of them for your hello world app
My enthusiasm was a little premature, I spent most of the day figuring out how to build an ocaml program with libraries, then pull that into a c static library compilation
This is kind of a quibble, but I'm pretty sure that includes transitive dependencies (since NPM duplicates them in node_modules.)
there's your issue, and it's the little "npm" between "type" and "install"