I'm not certain of memory usage. But using 'make_dataclass' makes the "noise" pretty much no worse than namedtuple.

Person = namedtuple("Person", "name age address")
Person = make_dataclass("Person", "name age address".split())

Unless you have millions of there's objects, memory probably isn't that important. But I guess you might... and namedtuple did sell itself as "less memory than small dictionaries"

On Sat, Jan 26, 2019, 1:26 PM Christopher Barker <pythonchb@gmail.com wrote:
On Sat, Jan 26, 2019 at 10:13 AM David Mertz <mertz@gnosis.cx> wrote:
Indeed! I promise to use dataclass next time I find myself about to use namedtuple. :-)

Indeed IIUC, namedtuple was purposely designed to be able to replace tuples as well as adding the named access.

But that does indeed cause potential issues. However, dataclasses see kind of heavyweight to me -- am I imagining that, or could one make a named_not_tuple that was appreciably lighter weight? (in creation time, memory use, that sort of thing)

-CHB





 

I'm pretty sure that virtually all my uses will allow that.

On Sat, Jan 26, 2019, 1:09 PM Eric V. Smith <eric@trueblade.com wrote:


On 1/26/2019 12:30 PM, David Mertz wrote:
> On Sat, Jan 26, 2019 at 10:31 AM Steven D'Aprano <steve@pearwood.info
> <mailto:steve@pearwood.info>> wrote:
>
>     In what way is it worse, given that returning a namedtuple with named
>
>     fields is backwards compatible with returning a regular tuple? We can
>     have our cake and eat it too.
>     Unless the caller does a type-check, there is no difference. Sequence
>     unpacking will still work, and namedtuples unlike regular tuples can
>     support optional attributes.
>
>
> I suppose the one difference is where someone improperly relies on tuple
> unpacking.
>
> Old version:
>
>     def myfun():
>          # ...
>          return a, b, c
>
>     # Call site
>     val1, val2, val3 = myfun()
>
>
> New version:
>
>     def myfun():
>          # ...
>          return a, b, c, d
>
>
> Now the call site will get "ValueError: too many values to unpack". 
> Namedtuples don't solve this problem, of course.  But they don't make
> anything worse either.
>
> The better approach, of course, is to document the API as only using
> attribute access, not positional.  I reckon dataclasses from the start
> could address that concern... but so can documentation alone.  E.g.:
>
> Old version (improved):
>
>     def myfun():
>
>          mydata = namedtuple("mydata", "a b c")
>
>          # ...
>          return mydata(a, b, c)
>
>     # Call site
>     ret = myfun()
>
>     val1, val2, val3 = ret.a, ret.b, ret.c
>
>
> New version (improved)
>
>     def myfun():
>
>          mydata = namedtuple("mydata", "a b c d e")
>
>          # ...
>          return mydata(a, b, c, d, e)
>
> Now the call site is completely happy with no changes (assuming it
> doesn't need to care about what values 'ret.d' or 'ret.e' contain... but
> presumably those extra values are optional in some way.
>
> Moreover, we are even perfectly fine if we had created
> namedtuple("mydata", "e d c b a") for some reason, completely changing
> the positions of all the named attributes in the improved namedtuple.

Preventing this automatic unpacking (and preventing iteration in
general) was one of the motivating factors for dataclasses:
https://www.python.org/dev/peps/pep-0557/#id47

Eric
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