[issue42765] Introduce new data model method __iter_items__

[Richard Neumann]

Richard Neumann  added the comment:

Okay, I found the solution. Not using super() works:

from typing import NamedTuple


class Spamm(NamedTuple):

foo: int
bar: str

def __getitem__(self, index_or_key):
if isinstance(index_or_key, str):
try:
return getattr(self, index_or_key)
except AttributeError:
raise KeyError(index_or_key) from None

return tuple.__getitem__(self, index_or_key)

def keys(self):
yield 'foo'
yield 'bar'


def main():

spamm = Spamm(12, 'hello')
print(spamm.__getitem__)
print(spamm.__getitem__(1))
d = dict(spamm)
print(d)


if __name__ == '__main__':
main()

Result:


hello
{'foo': 12, 'bar': 'hello'}

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[issue42765] Introduce new data model method __iter_items__

[Richard Neumann]

Richard Neumann  added the comment:

Thank you all for your input.
I had a look at aforementioned discussion and learned something new.
So I tried to implement the dict data model by implementing keys() and 
__getitem__() accordingly:

from typing import NamedTuple


class Spamm(NamedTuple):

foo: int
bar: str

def __getitem__(self, item):
if isinstance(item, str):
try:
return getattr(self, item)
except AttributeError:
raise KeyError(item) from None

return super().__getitem__(item)

def keys(self):
yield 'foo'
yield 'bar'


def main():

spamm = Spamm(12, 'hello')
print(spamm.__getitem__)
print(spamm.__getitem__(1))
d = dict(spamm)


if __name__ == '__main__':
main()


Unfortunately this will result in an error:

Traceback (most recent call last):
  File "/home/neumann/test.py", line 4, in 
class Spamm(NamedTuple):
RuntimeError: __class__ not set defining 'Spamm' as . 
Was __classcell__ propagated to type.__new__?

Which seems to be caused by the __getitem__ implementation.
I found a corresponding issue here: https://bugs.python.org/issue41629
Can I assume, that this is a pending bug and thusly I cannot implement the 
desired behaviour until a fix?

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[issue42765] Introduce new data model method __iter_items__

[Eric V. Smith]

Change by Eric V. Smith :


--
nosy: +eric.smith

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[issue42765] Introduce new data model method __iter_items__

[Steven D'Aprano]

Steven D'Aprano  added the comment:

Hi Richard,


> Also, using _asdict() seems strange as an exposed API, since it's an 
> underscore method and users hence might not be inclined to use it.

I don't consider this a strong argument. Named tuple in general has to use a 
naming convention for public methods that cannot clash with field names, hence 
the single underscore, but your concrete named tuple class can offer any 
methods you like since you know which field names are used and which are not. 
Just add a public method "asdict" or any name you prefer, and delegate to the 
single underscore method.



> It would be nicer to have my type just return this appropriate dict when 
> invoking dict(BasicStats(…)).

As we speak there is a discussion on Python-Ideas about this.

https://mail.python.org/archives/list/python-id...@python.org/thread/2HMRGJ672NDZJZ5PVLMNVW6KP7OHMQDI/#UYDIPMY2HXGL4OLEEFXBTZ2T4CK6TSVU

Your input would be appreciated.


> This would require me to override the __iter__() method to yield key / value 
> tuples for the dict.

The dict constructor does not require that. See discussion on the thread above.

If you search the Python-Ideas archives, I am sure you will find past proposals 
for a `__json__` protocol. If I recall correctly, there was some concern about 
opening the flood-gates for dunder protocols (will this be followed with 
demands for __yaml__, __xml__, __cson__, __toml__, etc?) but perhaps the time 
is right to revisit this idea.

--
nosy: +steven.daprano

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[issue42765] Introduce new data model method __iter_items__

[Raymond Hettinger]

Change by Raymond Hettinger :


--
nosy: +bob.ippolito

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[issue42765] Introduce new data model method __iter_items__

[Raymond Hettinger]

Raymond Hettinger  added the comment:

This core of this idea is plausible.  It is a common problem for people to want 
to teach a class how to convert itself to and from JSON.

Altering the API for dicts is a major step, so you would need to take this to 
python-ideas to start getting buy-in.   A much smaller API change would be to 
just teach the JSON module to recognize a __json__ method.

Presumably if a robust serialization solution is created, people will need a 
way to deserialize back into a named tuple, data class, or custom class.  
Offhand, the only way I can think of to do this would be to add a field that 
could be recognized by json.load().  Some care would be needed to not create a 
pickle-like risk of arbitrary code execution.

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[issue42765] Introduce new data model method __iter_items__

[Karthikeyan Singaravelan]

Change by Karthikeyan Singaravelan :


--
nosy: +rhettinger

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[issue42765] Introduce new data model method __iter_items__

[Richard Neumann]

New submission from Richard Neumann :

I have use cases in which I use named tuples to represent data sets, e.g:

class BasicStats(NamedTuple):
"""Basic statistics response packet."""

type: Type
session_id: BigEndianSignedInt32
motd: str
game_type: str
map: str
num_players: int
max_players: int
host_port: int
host_ip: IPAddressOrHostname

I want them to behave as intended, i.e. that unpacking them should behave as 
expected from a tuple:

type, session_id, motd, … = BasicStats(…)

I also want to be able to serialize them to a JSON-ish dict.
The NamedTuple has an _asdict method, that I could use.

json = BasicStats(…)._asdict()

But for the dict to be passed to JSON, I need customization of the dict 
representation, e.g. set host_ip to str(self.host_ip), since it might be a 
non-serializable ipaddress.IPv{4,6}Address. Doing this in an object hook of 
json.dumps() is a non-starter, since I cannot force the user to remember, which 
types need to be converted on the several data structures.
Also, using _asdict() seems strange as an exposed API, since it's an underscore 
method and users hence might not be inclined to use it.

So what I did is to add a method to_json() to convert the named tuple into a 
JSON-ish dict:

def to_json(self) -> dict:
"""Returns a JSON-ish dict."""
return {
'type': self.type.value,
'session_id': self.session_id,
'motd': self.motd,
'game_type': self.game_type,
'map': self.map,
'num_players': self.num_players,
'max_players': self.max_players,
'host_port': self.host_port,
'host_ip': str(self.host_ip)
}

It would be nicer to have my type just return this appropriate dict when 
invoking dict(BasicStats(…)). This would require me to override the __iter__() 
method to yield key / value tuples for the dict.
However, this would break the natural behaviour of tuple unpacking as described 
above.

Hence, I propose to add a method __iter_items__(self) to the python data model 
with the following properties:

1) __iter_items__ is expected to return an iterator of 2-tuples representing 
key / value pairs.
2) the built-in function dict(), when called on an object, will attempt to 
create the object from __iter_items__ first and fall back to __iter__.

Alternative names could also be __items__ or __iter_dict__.

--
components: C API
messages: 383897
nosy: conqp
priority: normal
severity: normal
status: open
title: Introduce new data model method __iter_items__
type: enhancement
versions: Python 3.10

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