what it has is "type hints" which is way to have richer integration with type checkers and your IDE, but will never offer more than that as is
what it has is "type hints" which is way to have richer integration with type checkers and your IDE, but will never offer more than that as is
Python is strongly typed and it's interpreter is type aware of it's variables, so you're probably overreaching with that statement. Because Python's internals are type aware, it's how folks are able to create type checkers like mypy and pydantic both written in Python. Maybe you're thinking about TS/JSDoc, which is just window dressing for IDEs to display hints as you described?
https://stackoverflow.com/questions/2690544/what-is-the-diff...
https://wiki.python.org/moin/Why%20is%20Python%20a%20dynamic...
https://github.com/mypyc/mypyc
You can compile python to c. Right now. Compatibility with extensions still needs a bit of work. But you can write extremely strict python.
That's without getting into things like cython.
def plus(x, y):
return x+y
If your answer is among the lines of "It returns the sum x and y" then I would ask you who said that x and y are numbers. If these are strings, it concatenates them. If instead you pass a string and a number, you will get a runtime exception. So not only you can't tell what a function does just by looking at it, you can't even know if the function is correct (in the sense that will not raise an exception).On a more serious note, your comment actually hints at an issue: unit testing is less effective without static type checking. Let's assume I would like to sum x and y. I can extensively test the function and see that it indeed correctly sums two numbers. But then I need to call the function somewhere in my code, and whether it will work as intended or not depends on the context in which the function is used. Sometimes the input you pass to a function depends from some external source outside your control, an if that's the case you have to resort to manual type checking. Or use a properly typed language.
Python types are strictly specified, but also dynamic. You don't need static types in order to have strict types, and indeed just because you've got static types (in TS, for example) doesn't mean you have strict types.
A Python string is always a string, nothing is going to magically turn it into a number just because it's a string representation of a number. The same (sadly) can't be said of Javascript.
Your answer doesn't solve the problem, it just moves it: can you tell me what x. __add__(y) does?
Dynamic typing, but strong typing.
There's no magic going on here, just an attribute lookup. It's still possible to write terrible Python code -- as it is in any language -- and the recommendation is still "don't write terrible code", just as it is in any language. You don't have to like it, but not liking it won't make it any different.
The older I get, the more I like writing statically-typed code. I wrote a lot more Python (for my own use) in my youth, and tend towards Rust nowadays. Speaking of which: if you dislike the dynamic typing of Python then you must hate the static typing of Rust -- what does
fn add<T:Add<U>, U>(a: T, b: U) -> T::Output { a + b }
do?The plus function you wrote is not more confusing than any generic function in a language that supports that.
You just did tell us what it does by looking at it, for the 90% case at least. It might be useful to throw two lists in there as well. Throw a custom object in there? It will work if you planned ahead with dunder add and radd. If not fix, implement, or roll back.
The problem is that you can't know if the function is going to do what you want it to do without also looking at the context in which it is used. And what you pass as input could be dependent on external factors that you don't control. So I prefer the languages that let me know what happens in 100% of the cases.
Not yet been a real world concern in my career, outside webforms, which are handled by framework.
Sure, but some languages make it easier than others. And that was just one example, another example could be having a branch where the input to your function depends on some condition. You could have one of the two branches passing the wrong types, but you will only notice when that branch gets executed.
Indeed assuming it adds two things is correct, and knowing that concatenation is how Python defines adding strings is important for using the language in the intended way.