Lastly, people think C++ is not user friendly. No, it certainly is. It needs being careful, yes, but a lot of things can be done in less lines then people expect.
Typescript (by way of comparison with other non-low-level languages) just feels far more solid wrt type system, type safety, tooling etc. C# (which I've used for years) is faster by orders of magnitude and IMO safer/easier to maintain.
> or try to get debug information for a segfault
what's the problem with opening the core dump with gdb and looking at the backtrace?
It uses debuginfod for fetching symbols - here it "just works".
No, it's even worse -- there are even MORE ways of doing the same thing now.
I'm no hater of any programming language, but a strong proponent of using the right one for the job at hand. I write a lot of Python these days, because I neither need the speed, nor have the time to write a small utility which will help a user with C++. Similarly, I'd rather use Java if I'm going to talk with bigger DBs, do CRUD, or develop bigger software which is going to be used in an enterprise or similar setting.
However, if I'm writing high performance software, I'll reach for C++ for the sheer speed and flexibility, despite all the possible foot guns and other not-so-enjoyable parts, because I can verify the absence of most foot-guns, and more importantly, it gets the job done the way it should be done.
Writing good C++ is hard. People who think they can write good C++ are surprised to learn about certain footguns (static initialization before main, exception handling during destructors, etc).
I found this reference which I thought was a pretty good take on the C++ learning curve.
https://www.reddit.com/r/ProgrammerHumor/comments/7iokz5/c_l...
Ah, don't remind me Java people write C++ like they write Java, I've seen my fair share, thank you.
> Writing good C++ is hard.
I concur, however writing good Java is also hard. e.g. Swing has a fixed and correct initialization/build sequence, and Java self-corrects if you diverge, but you get a noticeable performance hit. Most developers miss the signs and don't fix these innocent looking mistakes.
I've learnt C++ first and Java later. I also tend to hit myself pretty hard during testing (incl. Valgrind memory sanity and Cachegrind hotpath checks), so I don't claim I write impeccable C++. Instead I assume I'm worse than average and try to find what's wrong vigorously and fix them ruthlessly.
I always find this remark amusing, given that Java adopted the common patterns in C++ toolkits that precedded Java.
If anything they are writting C++ like it used to be on Turbo Vision, Object Windows Library, MPW, PowerPlant, MFC, wxWindows,....
The code was math-heavy, and became completely unreadable and un-followable. He remarked "I'm a java developer, I do what I do, and as long as it works, I don't care".
That was really bad. It was a serious piece of code, in production.
If your C++ program exhibit undefined behaviour, the compiler is allowed to format your entire hard drive. Or encrypt it and display a "plz pay BTC" message. That's called a vulnerability. Real and meaningful security checks have been removed as "dead code" because of signed integer overflow (which is undefined behaviour by default).
If anything, I would guess the gross misunderstanding sprouted somewhere between the specs and the compiler writers. Originally, UB was mostly about bailing out when the underlying platform couldn't handle this particular case, or explicitly ignoring edge cases to simplify implementations. Now however it's also a performance thing, and if anything is marked as UB then it's fair game for the optimiser — even if it could easily be well defined, like signed integer overflow on 2's complement platforms.
No, it isn't. That's a completely made up fabrication. And if you had a compiler that was going to do that, then what the standard says or if there's undefined behavior is obviously not relevant or significant in the slightest.
The majority of the UB optimization complaints are because the compiler couldn't tell that UB was happening. It didn't detect UB and then make an evil laugh and go insane. That's not how this works.
Compilers cannot detect UB and then do things in response within the rules of the standard. Rather, they are allowed to assume UB doesn't happen. That's it, that's all they do. They just behave as though your source has no UB at all. As far as the compiler is concerned, UB doesn't exist and can't happen.
When a compiler can detect that UB is happening it'll issue a warning. It never silently exploits it.
> Real and meaningful security checks have been removed as "dead code" because of signed integer overflow (which is undefined behaviour by default).
Real and meaningful security checks have been removed because the security check happened after the values were already used in specific ways, not because of UB. The values were already specified in the source code to be a particular thing via earlier usage. UB is just the shield for developers who wrote a bug to hide behind to avoid admitting they had a bug.
Use UBSAN next time.
> even if it could easily be well defined, like signed integer overflow on 2's complement platforms.
Signed integer overflow is defined behavior, that's not UB. Also platform specific behavior is something the standard doesn't define - that's why it was UB in the first place.
It is kinda ridiculous it took until C++20 for this change, though
> No, it isn't. That's a completely made up fabrication.
Ever heard of viruses exploiting buffer overflows to make arbitrary code execution? One cause of that can be a clever optimisation that noticed that the only way the check fails is when some UB is happening. Since UB "never happens", the check is dead code and can be removed. And if the compiler noticed after it got past error reporting, you may not even get a warning.
You still get the vulnerability, though.
> UB is just the shield for developers who wrote a bug to hide behind to avoid admitting they had a bug.
C is what it is, and we live with it. Still, it would be unreasonable to say that the amount of UB it harbours isn't absolutely ludicrous. It's like asking children to cross a poorly mapped minefield and blame them when they don't notice a subtle cue and blow themselves up.
Also, UBSan is not enough. I ran some of my code unde ASan, MSan, and UBSan, and the TIS interpreter still found a couple things. And I'm talking about pathologically straight-line code where once you test for all input sizes you have 100% code path coverage.
> Signed integer overflow is defined behavior, that's not UB.
The C99 standard explicitly states that left shift is undefined on negative integers, as well as signed integers when the result overflows. I had to get around that one personally by replacing x<<n by x(1<<n) on carry propagation code.
Strangely enough I cannot find explicit mentions of signed integer overflow for regular arithmetic operators, but apparently the C++ standard has an explicit mention: https://stackoverflow.com/questions/16188263/is-signed-integ...
> Also platform specific behavior is something the standard doesn't define - that's why it was UB in the first place.*
One point I was making is, compiler writers didn't get that memo. They treat any UB as fair game for their optimisers. It doesn't matter that signed integer overflow was UB because of portability, it still "never happens".
There's a lot of ludicrous stuff about C and I wouldn't recommend anyone use it for anything. Not when Rust and C++ exist.
But UB really isn't the scary boogie man. There could probably stand to be a `as-is {}` block extension for security checks, but that's really about it.
Granted, C is underpowered and I would like namespaces and generics. But from a safety standpoint nowadays, C++ is just as bad. Not only is is monstrously complex, it still has all the pitfalls of C. C++ may have been "more strongly typed" back in the day, but now compiler warnings made up for that small difference.
Granted, C++ can be noticeably safer if you go RAII pointer fest, but then you're essentially programming in Java with better code generation and a worse garbage collector.
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There's also a reason to still write C today: its ubiquity. Makes it easier to deploy everywhere and to talk to other languages. It's mostly a library thing though, and the price in testing effort and bugs is steep.
C++ had a defined multithreaded memory model and 2's compliment behavior before C did. Since you're all about UB, that kinda matters. A lot.
Point taken about multi threading.
This is why valgrind, asan and friends exist. They move the error diagnostic to the place where error actually happened.
The “forget to check an error” one is valid, but rare (usually a function will return data and an error, and you can’t touch the data without handling the error)—moreover, once you use Go for a bit, you sort of expect errors by default (most things error). But yeah, a compilation failure would be better. Personally, the things that really chafe me are remembering to initialize maps, which is a rarer problem in Python because there’s no distinction between allocation and instantiating (at least not in practice). I do wish Go would ditch zero types and adopt sum types (use Option[T] where you need a nil-like type), but that ship has sailed.
I’ve operated services in both languages, and Python services would have tons of errors that Go wouldn’t have, including typos in identifiers, missing “await”s, “NoneType has no attribute ‘foo’”, etc but also considerably more serious issues like an async function accidentally making a sync call under the covers, blocking the event loop, causing health checks to fail, and ultimately bringing down the entire service (same deal with CPU intensive endpoints).
In Go, we would see the occasional nil pointer error, but again, Python has those too.
It is memory safe but otherwise I think it was an imitation, not a reaction, to ObjC features.
But I do have to say that I never managed to really get into python, it always just felt like to much of a hassle, thus I always avoided it if possible.
https://www.synopsys.com/blogs/software-security/understandi...
I think Go gets this right: it consistently uses braces for structure, but has an idiomatic reformatting tool that is applied automatically by most IDEs. This ensures that the format and indentation always perfectly matches the code structure, without needing to use invisible characters.
I’m gonna need an example because I do not believe this whatsoever.
Let's say I'm making a lot of numerical calculations which are fed from a lockless queue with atomic operations to any number of cores you want, where your performance is limited by the CPU cores' FPU performance and the memory bandwidth (in terms of both transfer speed and queries that bus can handle per second).
As I noted below, that code can complete 1.7 million complete evaluations per core, per second on older (2014 level) hardware, until your memory controller congests with all the requests. I need to run benchmarks on a newer set of hardware to get new numbers, however I seriously lack the time today to do so and provide you new numbers.
That much is obvious from Python providing a bunch of C-based primitives in stdlib (otherwise they'd just be written in pure Python).
In many cases, you can make use of the existing primitives to get huge improvements even with pure Python, but you are not beating optimized C++ code (which almost has direct access to CPU vector operations as well).
Python's advantage is in speed of development, not in speed of execution. And I say that as a firm believer that majority of the Python code in existence today could be much faster only if written with the understanding of Python's internal structures.
Try writing a matmul operation in C++ and profile it against the same thing done in Numpy/Pytorch/TensorFlow/Jax. You’ll be surprised.
The code I've written can complete 1.7 million evaluations per core, per second, on older hardware, which is used to evaluate things up to 1e-6 accuracy, which pretty neat for what I'm working on.
As soon as you step out of the happy path and need to do any calculation that isn't at least n^2 work for every single python call you are looking at order of magnitude speed differences.
Years ago now (so I'm a bit fuzzy on the details) a friend asked me to help optimize some python code that took a few days to do one job. I got something like a 10x speedup using numpy, I got a further 100x speedup (on the entire program) by porting one small function from optimized numpy to completely naive rust (I'm sure c or c++ would have been similar). The bottleneck was something like generating a bunch of random numbers, where the distribution for each one depended on the previous numbers - which you just couldn't represent nicely in numpy.
What took 2 days now took 2 minutes, eyeballing the profiles I remember thinking you could almost certainly get down to 20 seconds by porting the rest to rust.
There's nothing here for a DB to really help with, the data access patterns are both trivial and optimal. IIRC it was also more like a billion rows so I'd have some scaling questions (a big enough instance could certainly handle it, but the hardware actually being used was a cheap laptop).
Even if there was though - I would have been very hesitant to do so. The not-a-fulltime-programmer PhD student whose project this was really needed to be able to understand and modify the code. I was pretty hesitant to even introduce a second programming language.
Call overhead and loop overhead is pretty big in Python though. The way to work around that in Python is to use C-based "primitives", like the stuff from itertools and all the builtins for set/list/hash processing (thus avoiding the n^2 case in pure Python). And when memory is an issue (preallocating large data structures can be slow as well), iterators! (Eg. compare use of range() in newer Python with use of list(range())).
And if I recall correctly there was no allocation in the hot loop, with a single large array being initialized via numpy to store the values before hand. Certainly that's one of the first things I would think to fix.
I was strongly convinced at the time that there was no significant improvement left in python. With >99% of the time being spent in this one function, and no way to move the loop into native code given the primitives available from numpy. Admittedly I could have been wrong, and I'm not about to revisit the code now, since it has been years and it is no longer in use - so everything I'm saying is based off of years old memories.
Sounds like a Numba use case.
In essence, doing what you did is the way to get performance out of Python when nothing else works.
https://github.com/numpy/numpy/blob/main/numpy/core/src/mult...
Your assertion was that numpy etc will be faster than something else despite being python:
> Try writing a matmul operation in C++ and profile it against the same thing done in Numpy/Pytorch/TensorFlow/Jax. You’ll be surprised.
I mean TensorFlow is c++/cuda!
No. When I write Tensorflow code I write Python. I don’t care what TF does under the hood just like I don’t care that Python itself might be implemented in C. Though I got to say TF is quite ugly and not a good example of Python’s user friendliness. But that’s another topic.
In the early days, Python tutorial warned against adding to strings by doing "+" even though it works because that performed a new allocation and string copy.
What you were asked to do was use fast, optimized C-based primitives like "\n".join(list_of_strings) etc.
Basically, Python is an "ergonomic" language built in C. Saying how something is implemented in C at the lower level is pointless, because all of Python is.
Yes, doing loops over large data sets in Python is slow. Which is why it provides itertools (again, C-based functions) in stdlib.
https://www.boost.org/doc/libs/1_75_0/libs/numeric/ublas/doc...
I think BLAS (a C version, not the boost one) is also the library numpy is using, as numpy is not written in python. That's why it is fast, it is C.
Have you ever tried Rust? Compared to C++, it's like heaven
Have you ever tried Rust? Compared to C++, it's like lawyer speech vs poetry