deltasevennine

A lot of people don't agree. But I feel category theory is the Maxwells Equation for software.

What is the shortest distances between two points? A straight line. I calculate the solution to that problem. I don't design it. What's the best way to travel between two points? Do I take a car or plane? Which is cheaper, faster, or more comfortable? I can't calculate a solution because the problem is to complex. Instead I design the solution to the problem. That is the fundamental difference between design and calculation.

Whenever you use the word "design" you are operating in a zone where humans have no foundational optimization theory. You are guessing, using your instincts, your common sense and your gut to find solutions for the problem. It's unlikely you'll hit the most optimal solution, but you can very likely arrive at a "good" solution.

If you squint, Category theory looks to fill this gap for designing programs. Depending on how you look at it, category theory looks like a fundamental theory on how to organize code. It can be thought of as a fundamental theory on abstraction or a fundamental theory on interfaces.

Maybe another way to put it is that the concept of interfaces are the maxwells equations of software..

Even turing machines/lambda caculus seem oddly specific let alone lisp. If we want something fundamental and general I think Category theory is it.

My guess is, if the advancement of computer science was allowed to play out for centuries and we got rid of all the historical baggage, some form of category theory would lie at the heart of it all.

Bro. If someone was truly disturbing and you truly wanted to help them wouldn't walk up to them and tell them to speak to a mental health professional. Telling them that is even more offensive. We both know this.

You're not joking. You're just being an even bigger ass, but now instead of jokes, you're feigning concern. It's stupid.

There's subtle motivations behind everything. A genuine apology comes without insulting the other party. Clearly you didn't do that here, and clearly you and everyone else knows what a genuine apology should NOT look like: "go get help with your mental problems, I'm really sorry."

It shows just what kind of person you are. It's not me who's disturbing... it's you, the person behind a mask.

Also clearly my words are from a place of anger and seriousness not mental issues. Mental problems are a very grave issue and it's a far bigger problem and the symptoms are far more extreme then what's happening here. But you know this. And you're trying to falsely re-frame the situation by disgustingly using mental issues as some kind of tool to discredit the other party. It's just vile.

I don't wish you the best of luck. I think someone like you doesn't deserve it.

Why stop at the c-suite? We may not be close to being ready to disrupt software engineering but the trend is heading in that direction. We already passed a milestone for code generation.

Realistically, C-suite probably will probably target engineers first before letting themselves get replaced by AI. It may be fractionally partially responsible for the current layoff.

Of course. It's not about the best move or what looks better. Nobody cares for that.

It's about the truth. That's what people care about in the end. And if none of it was said here, parent is pointing out that Mark is truly an ass. Something like "laying off people because other companies are doing it" is pretty fucked up.

>Sure, sorry about my little previous joke[1], meant no factual offense. The very best of luck to you as a programmer and a wonderfully polite human being with a great sense of humor.

Jokes are supposed to be funny. Not offensive. Your intent was offense under the guise of humor. Common tactic. Anyone serious doesn't take well to the other party being sarcastic or joking, you know this, yet you still play games. It's a typical strategy to win the crowd by making someone overly serious look like a fool. But there is no crowd here, nobody is laughing. Just me and you.

So your real intent is just to piss me off given that you know nobody is here to laugh at your stupid joke. Your just a vile human being. Go ahead crack more jokes. Be more sarcastic, it just shows off your character. We're done.

Sure there are forks and there are spoons. But there are also lumps of coal.

You have a problem: You need to eat soup and steak. So you use a spoon or a fork. The lump of coal is useless. You can probably smash the steak with it then eat the remains or lick the soup off the wet coal you dipped into it. Possible but a horrible tool overall.

There is an argument to be made whether certain languages are lumps of coals rather then a spoon or a fork =).

>Incorrect. Have a look at the Swift OpenCombine library. Multiple Publishers of a particular type that emits a single boolean value

First off types can't emmit values. Types don't exist at run time. They're simply meta info for the compiler to run checks. Thus they can't emmit anything. Second if you're talking about something that emmits a value then it involves logic that doesn't have to do with UI. A UI is not about logic, it is simply a presentation given to the user, all logic is handled by things that AREN'T UI based.

UI would be like html and css. Can you type check html and css make sure the hackernews UI is correct? There is no definition of correctness in UI thus it can't be type checked. The example you're talking about is actually type checking the logic UNDERNEATH the UI.

>Effectively, it is not possible to even compile a program that incorrectly ignores multi-threading or incorrectly accesses memory in a race condition with other threads thus possibly corrupting that memory. Moreover, it is also not possible for a thread not to properly release a lock once the MutexGuard type goes out of scope.

This is different. It's not type checking memory corruption. It's preventing certain race conditions by restricting your code such that you can't create a race condition. There's a subtle difference here. You can violate Rusts constraints in C++ yet still have correct code. Type checking memory corruption would involve code that actually HAS a memory corruption, and some checker proving it has a memory violation. My statement still stands Memory corruption cannot be type checked.

Think about it. A memory corruption is an error because we interpret to be an error. Logically it's not an error. The code is doing what you told it to do. You can't check for an error that's interpreted.

At best you can only restrict your code such that ownership lives in a single thread and a single function which prevents certain race conditions. which is what rust does. This has a cost such that implementing doubly linked lists are a hugely over complicated in rust: https://news.ycombinator.com/item?id=16442743. Safety at the cost of highly restricting the expressiveness of the language is very different from type checking. Type checking literally finds type errors in your code, borrow checking does NOT find memory corruption... it prevents certain corruption from happening that's about it.

>Unlikely. Without feeding strong type information that describes your problem domain into a checker, the checker cannot reason about your code and figure out possible errors. A strong type system is a "language" for a programmer to communicate with his or her checker.

No no, you're literally ignorant about this. There's a whole industry out there of automated proof checking of code via type theory and type systems and there's technology that enables this. It's just not mainstream. It's more obscure then haskell but it's very real.

It's only unlikely to you because you're completely ignorant about type theory. You're unaware of how "complex" that "language" can get. Dependent types is one example of how that "type language" can actually "type check" your entire program to be not just type correct but logically correct. Lean, Idris, Coq, Agda, literally are technologies that enable proof checking at the type level. It's not unlikely at all. it's reality.

>Please do not hold it against me if I do not continue commenting here - you must be from a different, parallel Universe. (How is Elvis doin' on your end? ;) J/K)

Wow. This is just fucking rude. I'm sorry but you're ignorant and you're about to have a rude awakening about just how ignorant you are. Take a look at this: https://www.ben-sherman.net/posts/2014-09-20-quicksort-in-id...

It's quick sort implemented in a language called idris. The implementation is long because not only is it just quick sort, the programmer is utilizing the type system to PROVE that quick sort actually does what it's suppose to do (sort ordinal values).

I'd appreciate an apology if you had any gall. But you likely won't "continue commenting here". Wow just wow. I am holding it against you 100%. I didn't realize how stupid and rude people can actually be.

Well sometimes people don't. I know I've done this on occasion. Just read the title and dive in with my own opinion.

>Perhaps, like any other tool-set... C has an optimal problem domain not everyone can understand

Maybe this is true specifically for C. However you imply this is true for "any other tool-set".

This is also a form of bias. It is illogical and irrational to think that every tool set is good for something. Things that exist can be horribly bad for everything and things that exist can in theory be good for almost anything.

There is not magical rule that says all tool-sets are great because they're always optimal for some niche problem domain.

The universe is not made up of apples and oranges. There are rotten oranges and rotten apples as well.

Another thing you're not addressing here is basically Type checking solves none of the problems you describe. You claim it's extraordinarily hard to write tests for UI and for memory corruption. And that's your argument for type checkers? It's next to impossible to type check UI and memory corruption. So your argument has no point here.

SQlite is written in C. It has type checking. Yet people still write unit tests for it. Why? Because type checking is mostly practically inconsequential. All your points don't prove anything. It proves my point.

All the problems you talk about can be solved with more advanced proof based checkers. These systems can literally proof check your entire program to be fully in spec precompile time. It goes far beyond just types. Agda, Idris, Coq, and Microsofts lean have facilities to prove your programs to be fully correct 100% of the time. They exist. But they're not popular. And there's a reason for that.

You say it's paramount to move error detection to compile time. I say, this problem is ALREADY solved, but remains unused because these methods aren't PRACTICAL.

><<Java and C# can have loong compile times.>> Yes, for initial build. After, it is only incremental.

I work with C++ currently. Even the incremental build is too slow. Also eventually you have to clear the cache for various reasons including debugging, a new library, etc, etc/

1M line python is 0s compilation time. You hit the runtime section instantaneously.

Go was created with fast compilation times to get around this problem. I would say in terms of compilation, go basically is the closest in terms of the python experience.

Basically when things are fast enough "5x compilation time" isn't even thought about because things are too fast to matter anyway. Go hits this area as well as python (given no compilation)

If you had jobs in both stacks as I have you'll see that the differences are trivial. Python can get just as complex as either c# and java.

Those other people your copying your argument from likely only had jobs doing Java or C# and they did some python scripts on the side and came to their conclusions like that. I have extensive experience for production work in both and I can assure you my conclusions are much more nuanced.

Python and java stack up pretty similarly in my experience. There's no hard red flags that make either language a nightmare to use when compared to the other. People panic about runtime errors, but like I said those errors happen anyway.

Python does however have a slight edge in the fact that it promotes a more humane style of coding by not enforcing the oop style. Java programmers on the otherhand are herded into doing oop so you have all kinds of service objects with dependency injection and mutating state everywhere. So what happens is in Java you tend to get more complex code, while python code can be more straightforward as long as the programmer doesn't migrate their oop design patterns over to python.

That's the difference between the two in my personal experience. You're mostly likely thinking about types. My experience is that those types are not that important, but either way, modern python with external type checkers actually has a type system that is more powerful then Java or C#. So in modern times there is no argument. Python wins.

But prior to that new python type system my personal anecdotal experience is more relevant and accurate then other people's given my background in both Java and python And C++. Types aren't that important period. They are certainly better then no types but any practical contribution to safety is minimal.

Well there's an irony to your statement. Those programmers who write embedded systems (I'm one of them) tend to use C++. C++ lacks memory safety and has segfaults, python doesn't. They literally used the most unsafe programming language ever that literally doesn't even alert you to errors either at compile time or runtime.

C++ is chosen for speed. Not for safety. The amount of run-time and compile time checks C++ skips is astronomical. The passengers may think it matters, but the programmers of those systems by NOT using a program that does compile time or run time checks are saying it doesn't matter.

Sure but the time delta is inconsequential. Why? because you're going to run that program anyway. You're going to at the very least manually test it to see if it works. The error will be caught. You spend delta T time to run the program. Either you catch the error after delta T or at the beginning of delta T. Either way you spent delta T time.

Additionally something like your example code looks like data science work as nobody loads huge databases into memory like that. Usually web developers will stream such data or preload it for efficiency. You'll never do this kind of thing in a server loop.

I admit it is slightly better to have type checking here. But my point still stands. I talk about practical examples where code usually executes instantly. You came up with a specialized example here where code blocks for what you imply to be hours. I mean it has to be hours for that time delta to matter, otherwise minutes of extra execution time is hardly an argument for type checking.

Let's be real, you cherry picked this example. It's not a practical example unfortunately. Most code executes instantaneously from the human perspective. Blocking code to the point where you can't practically run a test is very rare.

Data scientists, mind you, from the one I've seen, they don't use types typically with their little test scripts and model building that they do. They're the ones most likely to write that type of code. It goes to show that type checking gives them relatively little improvement over their workflow.

One other possibility is that expensive_computation() can live in a worker processing jobs off a queue. A possible but not the most common use case. Again for this, likely the end to end or your manual testing procedures will test loading a very small dataset which will in turn make the computation fast. Typical engineering practices and common sense lead you to uncover the error WITHOUT type checking being involved.

To prove your point you need to give me a scenario where the programmer won't ever run his code. And this scenario has to be quite common for it to be a practical scenario as that's my thesis. Practicality is a keyword here: Types are not "practically" that much better.

The comparison isn't happening because everyone is getting caught up in some language war.

I compare C++ and python because I'm trying to make a statement about types. How types are actually not as important as people think.

C++ and python are good examples because python is safer and easier to use then C++ yet python doesn't have type checking.

First off python now has types (you can place type annotations on the interpreter and run an external type checker) and javascript people use typescript. In terms of type safety i would argue python and javascript are now EQUAL to C# and Java.

Developer productivity in these scripting languages is also even higher. Simply because of how much faster they are to program in with the code then run/test loop. Java and C# can have loong compile times. Python and typescript are typically much much more quicker. With the additional type safety python and typescript are actually categorically higher in developer productivity then C# or Java.

But that's besides my point. Let's assume we aren't using modern conventions and javascript and python are typeless. My point is that whether or not C# or java crushes python and javascript over maintenance it doesn't win because of type checking.

>I try to add typing in Python where it makes sense (especially external interfaces), mostly as documentation, but am not overly zealous about them like some others I know. Mostly I look at them as better comments.

See you don't type everything because it doesn't improve things from a practical standpoint. You view it as better comments rather then additional type safety. You leave holes in your program where certain random parts aren't type checked. It's like if only half of C++ was type checked, one would think that it'd be a nightmare to program in given that we can't assume type correctness everywhere in the code. but this is not the case.

Your practical usage of types actually proves my point. You don't type everything. You have type holes everywhere and things still function just fine.

I type everything for that extra 1% in safety. But I'm not biased. I know 1% isn't a practical number. I do it partly out of habit from my days programming in haskell.

Of course. I'm a python guru. I know the python type annotation inside and out. I'm a type nazi when it comes to writing python.

That's why I know exactly what I'm talking about. I can unbiasedly say that from a practical standpoint the type checker simply let's you run and the "python" application less, and the "mypy" application more.

Example:

   def addOne(x: int) -> int:
       return x + 1

   addOne(None)

The above... if you run the interpreter on it, you get a type error. Pretty convenient, you can't add one to None.

But if you want to add type checking you run mypy on it. You get the SAME type error if you run mypy. They are effectively the same thing. One error happens at runtime the other happens at before runtime. No practical difference. Your manual testing and unit testing should give you practically the amount of safety and coverage you need.

Keyword here is "practically." yes type checking covers more. But in practice not much more.

> I don't understand why you're talking about statistical sampling. Aside from random functions, functions are deterministic, unit testing isn't about random sampling. That's not the problem here.

Completely and utterly incorrect. You are not understanding. Your preconceived notion that unit testing has nothing to do with random sampling is WRONG. Unit Testing IS Random sampling.

If you want 100% coverage on your unit tests you need to test EVERY POSSIBILITY. You don't. Because every possibility is too much. Instead you test a few possibilities. How you select those few possibilities is "random." You sample a few random possibilities OUT OF a domain. Unit Testing IS random sampling. They are one in the same. That random sample says something about the entire population of possible inputs.

>Next month some code elsewhere changes and that function ends up getting called with a string containing json instead, so now it blows up in production, you have an outage until someone fixed it. Not great. You might think maybe you were so careful that you actually earlier had unit tests passing a string instead, so maybe it could've been caught before causing an outage. But unlikely.

Rare. In theory what you write is true. In practice people are careful not to do this; and unit tests mostly prevent this. I can prove it to you. Entire web stacks are written in python without types. That means most of those unit tests were successful. Random Sampling statistically covers most of what you need.

If it blows up production the fix for python happens in minutes. A seg fault in C++, well that won't happen in minutes. Even locating the offending line, let alone the fix could take days.

>Following month some code elsewhere ends up pulling a different json library which produces subtly incompatible json objects and one of those gets passed in, again blowing up in production. You definitely didn't have unit tests for this one because two months ago when the code was written you had never heard of this incompatible json library. Another outage, CEO is getting angry.

Yeah except first off in practice most people tend to not be so stupid as to do this, additionally unit tests will catch this. How do I know? Because companies like yelp have had typeless python as webstacks for years and years and years and this mostly works. C++ isn't used because it's mostly a bigger nightmare.

There are plenty of companies for years and years have functioned very successfully using python without types. To say that those companies are all wrong is a mistake. Your company is likely doing something wrong... python functions just fine with or without types.

>And this is one of the 5 arguments, same applies for all of them so there is exponential complexity in attempting to cover every scenario with unit tests. So you can't.

I think you should think very carefully about what I said. You're not understanding it. Unit testing Works. You know this. It's used in industry, there's a reason why WE use it. But your logic here is implying something false.

You're implying that because of exponential complexity it's useless to write unit tests. Because you are only covering a fraction of possible inputs (aka domain). But then this doesn't make sense because we both know unit testing works to an extent.

What you're not getting is WHY it works. It works because it's a statistical sample of all possible inputs. It's like taking a statistical sample of the population of people. A small sample of people says something about the ENTIRE population of people. Just like how a small amount of unit tests Says something about the correctness of the entire population of Possible inputs.

>This isn't a theoretical example, it's happening in our service very regularly. It was a huge mistake to use python for production code but it's too expensive to change now, at least for now.

The problem here is there are practical examples of python in production that do work. Entire frameworks have been written in python. Django. You look at your company but blindly ignore the rest of the industry. Explain why this is so popular if it doesn't work: https://www.djangoproject.com/ It literally makes no sense.

Also if you're so in love with types you can actually use python with type annotations and an external type checker like mypy. These types can be added to your code base without changing your code. Python types with an external checker are actually more powerful then C++ types. It will give you equivalent type safety (with greater flexibility then C++) to a static language if you choose to go this route. I believe both yelp and Instagram decided to do add type annotations and type checking to their code and CI pipeline to grab the additional 10% of safety you get from types.

But do note, both of those companies handled production python JUST FINE before python type annotations. You'd do well do analyze why your company has so many problems and why yelp and instagram supported a typeless python stack just fine.

>Yes. But for the runtime error to occur, you need to trigger it by passing the wrong object. Unless you have a test case for every possible wrong object in every possible call sequence (approximately nobody has such thorough test coverage)

And I'm saying from a practical standpoint manual tests and unit tests PRACTICALLY cover most of what you need.

Think about it. Examine addOne(x: int) -> int. The domain of the addition function is huge. Almost infinite. Thus from a probabilistic standpoint why would you write unit tests with one or two numbers? it makes no sense as the your only testing a probability of 2 out of infinite of the domain. But that probability is flawed because it is in direct conflict with our behavior and intuition. Unit tests are an industry standard because it works.

The explanation for why it works is statistical. Let's say I have a function f:

   assert(f(6) == 5).

The domain and the range are practically infinite. Thus for f(6) to randomly produce 5 is a very low probability because of the huge number of possibilities. This must mean f is not random. With a couple of unit tests verifying confirming that f outputs non-random low probability results demonstrates that the statistical sample you took has high confidence. So statistically unit tests are basically practically almost as good as static checking. They are quite close.

This is what I'm saying. Yes static checks catch more. But not that much more. Unit tests and manual tests cover the "practical" (keyword) majority of what you need to ensure correctness without going for an all out proof.

>If you had been catching these during compile time, like a static type system allows, that can never happen. >I started developing in C++ in 1992, so I have a few years with it.

The other part of what I'm saying is that most errors that are non-trivial happen outside of a type system. Seg faults, memory leaks, race conditions etc... These errors happen outside of a type system. C++ is notorious for hiding these types of errors. You should know about this if you did C++.

Python solves the problem of segfaults completely and reduces the prevalence of memory leaks with the GC.

So to give a rough anecdotal number, I'm saying a type system practically only catches roughly 10% of errors that otherwise would not have been caught by a dynamically typed system. That is why the type checker isn't the deal breaker in my opinion.

> We get that you hate C++.

You just can't stop can you? There's really zero need to say this other then trying to be an ass. I don't hate C++. I chose to write C++ as my day to day job after quite some time doing python because it's a challenge. There is no hate. But I have no loyalty to the language either. That is my way. No loyalty and therefore no bias. C++ is definitively less safe then python. This is fact and that is why I program in it.

I am also talking about type systems. Not just C++. However I AM using C++ as an example. It is flawed despite a stronger type system then python. The paradoxical dichotomy between the two languages is the quintessential example of my point. The type system is not essential to safety. It's an illusion. Types are simply sugar on top of it all because in essence you're just relying on error messages to resolve all the errors. Whether those errors happen at compile time or runtime aren't a big deal.

That is the point. I'm not waging a war against C++. I'm EXPLAINING to people like you who don't bother to read carefully or think carefully.

>But the topic here is type systems, and Rust's is more like C++'s than any other, and vice versa.

Categorically wrong. Rust's type system is derived from the Hindley Milner. See: https://en.wikipedia.org/wiki/Hindley%E2%80%93Milner_type_sy.... Haskell is the the language famous for using this type system. In short Rust's type system comes from functional programming and C++'s type system is derived from OOP origins.

>but competition between compilers has improved them.

I use C++ everyday for my work. It may have improved but it's still overall horrible.

I agree with you, but I'm saying things from a practicality standpoint.

Let me put it this way. If you have type checking I'm saying that from my anecdotal experience you probably catch 10% more errors then you would normally catch before deployment. The reason is you're bound to run runtime tests anyway and these tests cause you to correct all your little type bugs anyway.

And this isn't even errors you would'nt've caught. It's just about catching the errors earlier.

That's it. Catching 10% of errors after deployment rather then before... that is not a huge deal breaker. Type checking benefits are marginal in this sense. Yes agreed it's better, but it's not the deal breaker.

I'm trying to point out the deal breaker feature. The delta difference that causes python to be BETTER then C++ in terms of usability and safety. Type checking is a negligible factor in that delta is basically my thesis. This is subtle. A lot of people are going on tangents but that is my point.

>but I suspect your assumption that "100,000 lines of code of python tend to be safer and more manageable then 100,000 lines of C++" might be wrong.

I can give you my anecdotal experience on this aka "authoritative" in your words. I am a really really really good python engineer with over a decade of experience. For C++ I have 4 years of experience, I would say I'm just ok with it.

Python is indeed safer then C++. Basically when you check for type errors at runtime, you actually easily hit all reasonable use cases pretty quickly. This is why unit testing works in reality even though your only testing a fraction of the domain.

Sure this isn't a static proof but in Practical terms static type checking is only minimally better then run-time type checking. You can only see this once you have extensive experience with both languages and you see how trivial type errors are. Practicality of technologies isn't a property you can mathematically derive, it's something you get a feel for once you've programmed enough in the relevant technologies. It helps you answer the question of "How often and how easy do type errors occur uncaught by tests?" Not that much more often and not hard at all to debug.

The thing that is actually making C++ less usable are the errors outside of type checking. The memory leaks, the segfaults, etc. The GC basically makes memory leaks nearly impossible and python doesn't have segfaults period. What python does is fail fast and hard once you write something outside of memory bounds. Basically it has extra run time checks that aren't zero cost that make it much much more safe.

All of this being said, I am talking about type-less python above... when I write python, I am in actuality a type Nazi. I extensively use all available python type hints including building powerful compositional sum types to a far more creative extent then you can with C++. I am extremely familiar with types and python types. I have a very detailed viewpoint from both sides of the spectrum from both languages. That's why I feel I'm qualified to say this.

>No contradiction, really, it's just that we are talking about two different programming goals: I emphasize the goal of producing well-behaved software (especially when it comes to large software systems), while you emphasize the goal of producing software in an easier (more productive) manner.

I'm actually partly saying both. Python is both easier and more well-behaved and more safe. The "well-behaved" aspect has a causal relationship to "easier". It makes sense if you think about it. Python behaves as expected more so then C++.

Literally I repeat: Python (even without types) is categorically safer then C++. I have a total of 14 years of experience in both. I would say that's enough to form a realistic picture.

>GC is not just for memory leaks, but memory safety in general.

No this is not true. Memory safety and memory leaks are different concepts. You can trigger a memory leak without violating memory safety. In fact a memory leak is not really an error recognized by an interpreter or a compiler or a GC. It is a logic error. A memory leak is only a leak because you interpret it as a leak. Otherwise the code is literally doing what you told it to do. It's similar to a logic error. I mean think about it, the interpreter can't know whether you purposefully allocated 1gb of memory or whether you accidentally allocated it.

Memory safety on the other hand is protection against violation of certain runtime protocols. The interpreter or runtime knows something went wrong and immediately crashes the program. It is a provable violation of rules and it is actually not open to interpretation like the memory leak was.

See python: https://docs.python.org/3/library/gc.html. You can literally disable the GC (during runtime) and the only other additional crash error that becomes more frequent is OOM. The GC literally just does reference counting and generational garbage collection... that's it.

I can tell you what makes python MORE memory safe then C++. It's just an additional runtime checks that are not zero cost.

  x = [1,2]
  print(x[2])

The above triggers an immediate exception that names the type of error (out of bounds) and the exact line that triggered it. This error will occur regardless of whether or not you disabled the GC. It happens because every index access to a list also checks against a stored length. If you're above that length it raises an exception. It's not zero cost but it's more safe.

For C++:

   int x[] = {1,2};
   std::cout<<x[2]<<std::endl;

This triggers nothing. It will run even though index 2 is beyond the bounds of the array. There is no runtime check because to do so would make the array data structure not zero cost. This is what happens during buffer overflows. It's one of the things that makes C++ a huge security problem.

Let's look at the type issue.

    def head(input_list: List[int]) -> Optional[int]:
        return input_list[0] if len(input_list) > 0 else None

    x: int = head(2)

--------------------

    #include <optional>
    #include <vector>
    std::Optional<int> head(const std::vector<int>& input_list){
         return (input_list.length() > 0) ? input_list[0] : std::nullopt; 
    }
    
    int main(){
       auto x = head(2)
       return 0;
    }

Both pieces of code are identical. Python is type annotated for readability (not type checked). But both literally produce the same error messages (wrong input type on the call to head). Both will tell you there's a type error. It's just python happens at runtime and C++ happens at compile time. C++ has a slight edge in the fact that the error is caught as a static check. But this is only a SLIGHT advantage. Hopefully this example will allow you to see what I'm talking about as both examples literally have practically the exact same outcome of a type error. A minority of bugs are exclusively caught with type checking because runtime still catches a huge portion of the same bugs... and in general this is why overall C++ is still MUCH worse in terms of usability then python despite type checking.

This is offensive. To suggest my opinion has no connection to reality?

Read what I wrote carefully. I'm not talking about type errors. I'm talking about errors in GENERAL.

Your comment is carefully tailored to incite flame war. You represent HN bias at it's finest, reading something and giving a casual dismissal without really interpreting it.

My point here is that static types didn't do much to improve C++. We should be focusing on what made C++ bad. The things that made C++ bad and the fixes for those things are what makes python Good.

I'm saying type checking is not one of those things.

>I think it's better to catch errors sooner than later. This is where type checking helps.

Agreed. It is better. But it's not that much better. That's why python is able to beat out C++ by leagues in terms of usability and ease of debugging and safety. This is my entire point. That type checking is not the deal breaker here. Type checking is just some extra seasoning on top of good fundamentals, but it is NOT fundamental in itself.

>As for C++ "non-determinism": If you write buggy code that overwrites memory, then of course you're going to get segfaults. This isn't C++'s fault.

This doesn't happen in python. You can't segfault in python. No language is at "fault" but in terms of safety python is safer.

This language of "which language is at fault" is the wrong angle. There is nothing at "fault" here. There is only what is and what isn't.

Also my point was that when you write outside of memory bounds, anything could happen. You can even NOT get a segfault. That's the problem with what makes C++ so not user friendly.

>I've seen plenty of code in all languages (including Python) that appears to exhibit chaotic run time behavior. At a previous company, we had apps that Python would bloat to gigabytes in size and eventually OOM. Is this "non-determinism"? No, it's buggy code or dependencies.

This is literally one of the few things that are non-deterministic in python or dynamic languages. Memory leaks. But these are Very very very hard to trigger in python. But another thing you should realize is that this error has nothing to do with type checking. Type checking is completely orthogonal to this type of error.

>I think it's better to catch errors sooner than later. This is where type checking helps. I've seen plenty of Python code that takes a poorly named argument (say "data").. is it a dict? list? something from a third party library like boto3? If it's a dict, what's in the dict? What if someone suddenly starts passing in 'None' values for the dict? Does the function still work? Almost nobody documents this stuff. Unless you read the code, you have no idea. "Determinism" of code is determined based on inputs. Type checking helps constrain those inputs.

When you get a lot of experience, you realize that "sooner" rather then "later" is better but not that much. Again the paradox reels it's head here. Python forwards ALL type errors to "later" while C++ makes all type errors happen sooner and Python is STILL FAR EASIER to program in. This is evidence for the fact that type checking does not improve things by too much. Other aspects of programming have FAR more weight on the the safety and ease of use of the language. <-- That's my thesis.

If it does matter to the conversation then it's evidence supporting my point. I'm saying type checking isn't a key differentiator between something like JS/ruby/python vs. C++. You're implying the GC is the key differentiator.

If you're saying that you CAN'T compare the python to C++ because of the GC then I disagree. GC only stops memory leaks. That is not the most frequent error that happens with C++. Clearly if you just subtract memory leak issues from C++ there's still a usability issue with just C++.

>I don't know what this means? You seem to be suggesting that code in a statically typed language cannot be debugged?

You don't know what it means probably because you don't have experience with C++. These types of errors are littered throughout C++. What you think I'm suggesting here was invented by your own imagination. I am suggesting no such thing.

You talk about strawmen? Literally what you said can be viewed as an aspect of deception at it's finest. I literally in no way suggested what you accused me of suggesting. Accusatory language is offensive. Just attack the argument... don't use words like "strawman" to accuse people of being deliberately manipulative here. We both believe what we're saying, no need to accuse someone of an ulterior agenda when ZERO motive for one exists.

What I am suggesting here is that there is an EXAMPLE of a statically typed language that is FAR less safe and FAR harder to debug then a dynamically typed language (C++ and python). This EXAMPLE can function as evidence for the fact that static type checking is not a key differentiator for safety or ease of use or ease of debugging.

>Debugging is in fact usually easier because you can rule out the type errors that can't happen.

You don't get it. Type errors that happen at runtime or compile time contain the same error message. You get the same information. Therefore you rule out the same thing. Type checking is only doing extra checking in the sense that it checks code that doesn't execute while runtime checks code that does execute.

Python was programmed with sane error messages and runtime checks that immediately fail the program and gives you relevant logic about where the error occurred. This is the key differentiator that allows it to beat out a language like C++ which has none of this. C++ does have static type checking but it does little to make it better then python in terms of safety and ease of use.

That's fine. A type checker won't catch everything. Run time errors happen regardless. I find it unlikely that all the errors your code base is experiencing is the result of type errors.

Something like c++. You get a runtime errors. You have no idea where it lives or what caused it.

Your python code base delivers an error but a patch should trivial because python tells you what happened. Over time these errors should become much less.