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Oddly enough, "except" variables don't remain bound!

    try:
        x = int('cat')
    except Exception as e:
        pass
    print(e)  # <- NameError: name 'e' is not defined
So, it appears Python actually has three variable scopes (global, local, exception block)?


Nope, it's more complicated than that:

    e = 'before'
    try:
        x = int('cat')
    except Exception as e:
        e2 = e
        print(e)
    print(e2) # <- This works!
    print(e)  # <- NameError: name 'e' is not defined
It's not a scoping thing, the bound exception variable is actually deleted after the exception block, even if it was already bound before!


lol - raku maybe weird, but at least it has sane variable scoping


Also true of JavaScript pre-ES5, another language that on first glance seems to only have function scope: it actually does have block scope, but only for variables introduced in `catch` blocks. AFAIU that was the standard way for a dumb transpiler to emulate `let`.


I wonder if that was ever popular, considering the deoptimization effects of try/catch, and given that block scope can also be managed by renaming variables.


exceptions being the exception is funny somehow


very recursive


you can say that again.


Exception blocks don't create a different scope. Instead, the name is explicitly (well, implicitly but deliberately) deleted from the scope after the try/except block runs. This happens because it would otherwise produce a reference cycle and delay garbage collection.

https://stackoverflow.com/questions/24271752

https://docs.python.org/3/reference/compound_stmts.html#exce...


This is the type of things that make me roll my eyes at all the wtf JavaScript posts[0], yes there are a lot of random things that happen with type conversions and quite a few idiosyncrasies (my favourite is that document.all is a non empty collection that is != from false but convert to false in an if)

But the language makes sense at a lower level, scopes, values, bindings have their mostly reasonable rules that are not hard to follow.

In comparison python seems like an infinite tower of ad-hoc exceptions over ad-hoc rules, sure it looks simpler but anywhere you look you discover an infinite depth of complexity [1]

[0] and how half of the complaints are a conjugation of "I don't like that NaNs exist

[1] my favourite example is how dunder methods are a "synchronized view" of the actual object behaviour, that is in a + b a.__add__ is never inspected, instead at creation time a's add behaviour is defined as its __add__ method but the association is purely a convention, eg any c extension type need to reimplement all these syncs to expose the correct behaviour and could for funzies decide that a type will use __add__ for repr and __repr__ for add


> yes there are a lot of random things that happen with type conversions and quite a few idiosyncrasies... the language makes sense at a lower level, scopes, values, bindings have their mostly reasonable rules

The "random things" make it practically impossible to figure out what will happen without learning a whole bunch of seemingly arbitrary, corner-case-specific rules (consider the jsdate.wtf test currently making the rounds). And no, nobody is IMX actually simply complaining about NaNs existing (although the lack of a separate integer type does complicate things).

Notice that tests showcasing JavaScript WTFery can work just by passing user data to a builtin type constructor. Tests of Python WTFery generally rely on much more advanced functionality (see e.g. https://discuss.python.org/t/quiz-how-well-do-you-know-pytho...). The only builtin type constructor in Python that I'd consider even slightly surprising is the one for `bytes`/`bytearray`.

Python's scoping is simple and makes perfect sense, it just isn't what you're used to. (It also, unlike JavaScript, limits scope by default, so your code isn't littered with `var` for hygiene.) Variables are names for objects with reference semantics, which are passed by value - exactly like `class` types in C# (except you don't have to worry about `ref`/`in`/`out` keywords) or non-primitives in Java (notwithstanding the weird hybrid behaviour of arrays). Bindings are late in most places, except notably default arguments to functions.

I have no idea what point you're trying to make about __add__; in particular I can't guess what you think it should mean to "inspect" the method. Of course things work differently when you use the C API than when you actually write Python code; you're interacting with C data structures that aren't directly visible from Python.

When you work at the Python level, __add__/__iadd__/__radd__ implement addition, following a well-defined protocol. Nothing happens "at creation time"; methods are just attributes that are looked up at runtime. It is true that the implementation of addition will overlook any `__add__` attribute attached directly to the object, and directly check the class (unlike code that explicitly looks for an attribute). But there's no reason to do that anyway. And on the flip side, you can replace the `__add__` attribute of the class and have it used automatically; it was not set in stone when the class was created.

I'll grant you that the `match` construct is definitely not my favourite piece of language design.


> methods are just attributes that are looked up at runtime

At runtime when evaluating a + b no dunder method is looked up and there is no guarantee that a + b === a.__anydunder__(b) https://youtu.be/qCGofLIzX6g

What i mean with weird scoping is

    def foo():
      e = 'defined'
      try:
        raise ValueError
      except Exception as e:
        print(e)
      print(e) # this will error out

    foo()
I also dislike how local/global scopes work in python but that is more of a personal preference.

I agree that that Javascripts standard library is horrible the jsdate.wtf is an extreme but apt example, IMO most of these are solved with some "defensive programming" but I respect other opinions here.

> And no, nobody is IMX actually simply complaining about NaNs existing

I watched many Javascript WTF! videos on youtube and NaNs and [2] == "2" were usually 90% of the content.


Anyway actually my biggest gripe with python is that i find the module/impor/export system counterintuitive


> Oddly enough

It's not that odd, since it's the only situation where you cannot keep it bounded, unless you enjoy having variables that may or may not be defined (Heisenberg variable?), depending on whether the exception has been raised or not?

Compare with the if statement, where the variable in the expression being tested will necessarily be defined.


> Compare with the if statement, where the variable in the expression being tested will necessarily be defined.

    if False:
        x = 7
    print(x)

    print(x)
          ^
    NameError: name 'x' is not defined
Ruby does this sort of stuff, where a variable is defined more or less lexically (nil by default). Python doesn't do this. You can have local variables that only maybe exist in Python.


While somewhat true, what would this be bound to?

    for i in range(0):
        pass


Well, after writing my comment, I realized that a python interpreter could define the variable and set it to None between the guarded block and the except block, and implicitly assign it to the raised exception right before evaluating the except block, when the exception as been raised. So technically, it would be possible to define the variable e in GP example and have it scoped to "whatever is after the guarded block", just like what is done with for blocks.

Is there any chance this would cause trouble though? Furthermore, what would be the need of having this variable accessible after the except block? In the case of a for block, it could be interesting to know at which point the for block was "passed".

So, maybe "None" answers your question?


The answer is: it is unbound. Intellisense will most likely tell you it is `Unbound | <type>` when you try to use the value from a for loop. Would it be possible that it could be default initialized to `None`? Sure, but `None` is a destinctivly different value than a still unbound variable and may result in different handling.


Are you saying that this should result in a name error?

   if <true comparison here>:
       x = 5
   print(x)  # <- should give name error?


I stand corrected, the exception case is definitely an oddity, both as being an outlier and as a strange behaviour wrt Python's semantics. Or is it a strange behaviour?

In the case of an if like in your example, no provision is made about the existence of x. It could have been defined earlier, and this line would simply update its value.

Your example:

   if True:
       x = 5
   print(x)  # 5

Same with x defined prior:

   x = 1
   if False:
       x = 5
   print(x)  # 1
What about this one?

   if False:
       x = 5
   print(x)  # ???


On the other hand, the notation "<exception value> as <name>" looks like it introduces a new name; what if that name already existed before? Should it just replace the content of the variable? Why the "as" keyword then? Why not something like "except <name> = <exception value>" or the walrus operator?

While investigating this question, I tried the following:

    x = 3
    try:
        raise Exception()
    except Exception as x:
        pass
    print(x)  # <- what should that print?


In any sane language it would, yes.


Heisenbug is the word you are looking but may not find.


I may be rusty, but wasn't there a "finally" scope for those situations?

edit: writing from phone on couch and the laptop... looks far, far away...




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