On Tue, Nov 20, 2018 at 3:08 AM Iwo Herka <iwohe...@gmail.com> wrote:
>
> Hello everyone,
>
> I've been looking for something in the documentation
> (https://docs.python.org/3.8/reference/datamodel.html) recently
> and I've noticed something weird. Documentation states that every
> object has a value, but doesn’t provide any definition
> whatsoever of what the value is. Now, I'm sure that every reasonably
> fluent Python programmer has an intuitive
> understanding of the term, nonetheless, I would expect the
> documentation defines it somehow (not necessarily
> in a formal fashion), especially considering that "the value of an
> object" is used to explain other concepts, such as
> mutability:
>
> > The value of some objects can change. Objects whose value can change are
> > said to be mutable; objects whose
> value is unchangeable once they are created are called immutable.
>
> So, why is documentation silent on this? One reason I can think of is
> to avoid answering inconvenient questions.
Sorta kinda, yeah. There is one very simple definition of "value"
which is entirely accurate, but probably not helpful, and that is: An
object's value is whatever it is equal to. That is to say, you can ask
two basic questions about an object:
x is y # identity: are x and y the SAME object?
x == y # equality: do x and y have the same value?
Value and equality are intrinsically linked, but unfortunately that
doesn't really explain what either one actually IS. As Rhodri says,
you can ask a philosopher about that, and will be stuck for weeks :)
The concept of "immutable" vs "mutable" object, therefore, is that
some objects may compare equal now and unequal later. Since the same
object is able to change in "value" over time, it may become (un)equal
to something while still being the same object. Thus mutable objects
can't be used as dict keys, as their values could change, and dict
lookups have to match based on equality. (Imagine putting two keys
into a dict while they have different values, and then mutating one of
them to have the same value. Now try to look up that new value using a
third object. The Logic Police will arrest you before you can say
"hashability"!)
Generally, Python objects have their values defined by an abstract
concept that is being represented. For instance, the integer 32 and
the float 32.0 have the same value, even though they're different
types; they both represent the abstract number equal to
two-to-the-fifth. But right here in that sentence, you can see how
hard it is to actually *define* that value. At best, all you can
really say is that the value is equal to the value of int("32") or
some other way of getting an object with that value.
Yep, it's hard. But the cool thing is, it usually doesn't matter - you
can say "x has the value 32" without worrying about representations,
data types, etc.
ChrisA
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