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A minor headache for a beginner coder (lemmy.dbzer0.com)
submitted 1 year ago by to c/python@programming.dev
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if var1 equals 1, and you run var2 = var1, that sets var2 to 1.

if list1 equals [1, 2, 3], and you run list2 = list1, that sets list2 to list1

so if you then run var1 = 2, var2 will still be 1

but if you run list1 = [3, 2, 1], list2 will give [3, 2, 1]

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[–] 1 point 1 year ago (1 child)

True. Since it's all interpreted, it doesn't act like primitives in things like C and everything is an object, that is a ref of some sort. However, there is a difference between how Python "primitives" and Python collections work within the language syntax.

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  • [–] 1 point 1 year ago (1 child)

    Now I'm curious what differences you are talking about, because I'm no Python expert, but I can't think of any. If you mean identity representation, no, it's not different:

    >>> a = 65535
>>> b = 65535
>>> a is b
False
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  • [–] 0 points 1 year ago* (last edited 1 year ago) (2 children)

    I was meaning how they behave in when copying and similar behavior. One basically just needs to remember that assignment of a Python primitives var to another will copy the value, whereas doing the same thing with a collection will generally make a reference instead.

    As for this:

    >>> b = 65535
>>> a is b
False

    I'd expect that behavior in must programming languages. It effectively translates to:

    Allocate a variable "a" and assign it the value 65535

    Allocate a variable "b" and assign it the value 65536

    Is variable "a" literally the variable "b"? No

    One could test with == to see if the values are equivalent but, unless "b" is assigned as "a", a is b should evaluate as false because they are two different variables.

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  • [–] 1 point 1 year ago (1 child)

    It doesn't seem to copy the value, just make another reference:

    >>> a = 65535
>>> b = a
>>> b is a
True

    One thing I know that Python does is optimize the value away for the few smallest values of the primitives. But that's on optimizations.

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  • [–] 2 points 1 year ago (1 child)

    Oh right! You are indeed correct. It is effectively just seeing a pointer there. What Python considers that to be is a shallow copy. But this only applies to "primitive" types. If you change the value of either, it will cease to act as a pointer to the same object but instead allocate a new one. It's a bit weird if one isn't used to all of that abstraction between oneself and the memory.

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  • [–] 2 points 1 year ago

    As I said, it's because you can't change the value of a primitive value. (That is, unless you abuse the C interface.)

    Because Python doesn't protect classes, you just can't do the same with the types you create. But that's what is special, not the way if handles variables.

    And this is different from languages like Java/C#, PHP/Perl, etc. Most imperative languages have primitive atomic values that go directly into your variables. But Python has only references (except for some complicated optimizations). Anyway, it is weird, and it's one of the reasons people should learn C or Rust eventually.

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